terra_mhub/papermill_notebooks/sr_dicom_generation.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "view-in-github"
   },
   "source": [
    "<a href=\"https://colab.research.google.com/github/ccosmin97/idc-prostate-mri-analysis/blob/main/terra_mhub/papermill_data/sr_dicom_generation.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9d66f855",
   "metadata": {
    "id": "9d66f855",
    "papermill": {
     "duration": 0.008699,
     "end_time": "2024-09-10T04:38:19.072984",
     "exception": false,
     "start_time": "2024-09-10T04:38:19.064285",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "Myw8MvN7khmz",
   "metadata": {
    "id": "Myw8MvN7khmz"
   },
   "outputs": [],
   "source": [
    "# from google.colab import auth\n",
    "# auth.authenticate_user()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "7438a39a",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "execution": {
     "iopub.execute_input": "2024-09-10T04:38:19.089996Z",
     "iopub.status.busy": "2024-09-10T04:38:19.089585Z",
     "iopub.status.idle": "2024-09-10T04:38:19.094536Z",
     "shell.execute_reply": "2024-09-10T04:38:19.093711Z"
    },
    "id": "7438a39a",
    "outputId": "41baeaeb-c0a5-4e23-b596-e3e76ccfd53d",
    "papermill": {
     "duration": 0.015936,
     "end_time": "2024-09-10T04:38:19.096576",
     "exception": false,
     "start_time": "2024-09-10T04:38:19.080640",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reading package lists... Done\n",
      "Building dependency tree... Done\n",
      "Reading state information... Done\n",
      "The following NEW packages will be installed:\n",
      "  lz4\n",
      "0 upgraded, 1 newly installed, 0 to remove and 49 not upgraded.\n",
      "Need to get 90.0 kB of archives.\n",
      "After this operation, 236 kB of additional disk space will be used.\n",
      "Get:1 http://archive.ubuntu.com/ubuntu jammy/main amd64 lz4 amd64 1.9.3-2build2 [90.0 kB]\n",
      "Fetched 90.0 kB in 0s (415 kB/s)\n",
      "Selecting previously unselected package lz4.\n",
      "(Reading database ... 123621 files and directories currently installed.)\n",
      "Preparing to unpack .../lz4_1.9.3-2build2_amd64.deb ...\n",
      "Unpacking lz4 (1.9.3-2build2) ...\n",
      "Setting up lz4 (1.9.3-2build2) ...\n",
      "Processing triggers for man-db (2.10.2-1) ...\n"
     ]
    }
   ],
   "source": [
    "# !apt-get install lz4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "IDZcNC2zB2O6",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "IDZcNC2zB2O6",
    "outputId": "c124a9fd-ad22-45ce-ef55-ee114ae84a5d"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting pylibjpeg\n",
      "  Downloading pylibjpeg-2.0.1-py3-none-any.whl.metadata (7.8 kB)\n",
      "Collecting pylibjpeg-openjpeg\n",
      "  Downloading pylibjpeg_openjpeg-2.3.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (5.7 kB)\n",
      "Collecting pylibjpeg-libjpeg\n",
      "  Downloading pylibjpeg_libjpeg-2.2.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (4.7 kB)\n",
      "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from pylibjpeg) (1.26.4)\n",
      "Downloading pylibjpeg-2.0.1-py3-none-any.whl (24 kB)\n",
      "Downloading pylibjpeg_openjpeg-2.3.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.3 MB)\n",
      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.3/1.3 MB\u001b[0m \u001b[31m19.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[?25hDownloading pylibjpeg_libjpeg-2.2.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.4 MB)\n",
      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m3.4/3.4 MB\u001b[0m \u001b[31m82.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[?25hInstalling collected packages: pylibjpeg-openjpeg, pylibjpeg-libjpeg, pylibjpeg\n",
      "Successfully installed pylibjpeg-2.0.1 pylibjpeg-libjpeg-2.2.0 pylibjpeg-openjpeg-2.3.0\n"
     ]
    }
   ],
   "source": [
    "# !pip install pylibjpeg pylibjpeg-openjpeg pylibjpeg-libjpeg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e0d58ac2",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "execution": {
     "iopub.execute_input": "2024-09-10T04:38:19.113557Z",
     "iopub.status.busy": "2024-09-10T04:38:19.112695Z",
     "iopub.status.idle": "2024-09-10T04:38:19.116674Z",
     "shell.execute_reply": "2024-09-10T04:38:19.115802Z"
    },
    "id": "e0d58ac2",
    "outputId": "c1604822-f854-4640-d451-e713a506c6b0",
    "papermill": {
     "duration": 0.0146,
     "end_time": "2024-09-10T04:38:19.118637",
     "exception": false,
     "start_time": "2024-09-10T04:38:19.104037",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting dcm2niix\n",
      "  Downloading dcm2niix-1.0.20220715.tar.gz (451 kB)\n",
      "\u001b[?25l     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/451.4 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K     \u001b[91m━━━━━━━━━━━━━\u001b[0m\u001b[91m╸\u001b[0m\u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m153.6/451.4 kB\u001b[0m \u001b[31m4.5 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m451.4/451.4 kB\u001b[0m \u001b[31m7.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[?25h  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
      "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
      "  Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
      "Collecting pyaml\n",
      "  Downloading pyaml-24.9.0-py3-none-any.whl.metadata (11 kB)\n",
      "Collecting idc-index\n",
      "  Downloading idc_index-0.7.3-py3-none-any.whl.metadata (8.5 kB)\n",
      "Collecting pyradiomics\n",
      "  Downloading pyradiomics-3.1.0.tar.gz (34.5 MB)\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m34.5/34.5 MB\u001b[0m \u001b[31m60.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[?25h  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
      "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
      "  Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
      "Discarding \u001b[4;34mhttps://files.pythonhosted.org/packages/03/c1/20fc2c50ab1e3304da36d866042a1905a2b05a1431ece35448ab6b4578f2/pyradiomics-3.1.0.tar.gz (from https://pypi.org/simple/pyradiomics/)\u001b[0m: \u001b[33mRequested pyradiomics from https://files.pythonhosted.org/packages/03/c1/20fc2c50ab1e3304da36d866042a1905a2b05a1431ece35448ab6b4578f2/pyradiomics-3.1.0.tar.gz has inconsistent version: expected '3.1.0', but metadata has '3.0.1a1'\u001b[0m\n",
      "  Downloading pyradiomics-3.0.1.tar.gz (34.5 MB)\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m34.5/34.5 MB\u001b[0m \u001b[31m64.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
      "Collecting SimpleITK==2.3.0\n",
      "  Downloading SimpleITK-2.3.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (7.9 kB)\n",
      "Collecting pyplastimatch==0.4.2\n",
      "  Downloading pyplastimatch-0.4.2-py3-none-any.whl.metadata (9.4 kB)\n",
      "Collecting highdicom==0.21.0\n",
      "  Downloading highdicom-0.21.0-py3-none-any.whl.metadata (3.8 kB)\n",
      "Collecting pydicom==2.4.3\n",
      "  Downloading pydicom-2.4.3-py3-none-any.whl.metadata (7.8 kB)\n",
      "Collecting itk (from pyplastimatch==0.4.2)\n",
      "  Downloading itk-5.4.0-cp310-cp310-manylinux_2_28_x86_64.whl.metadata (22 kB)\n",
      "Requirement already satisfied: matplotlib in /usr/local/lib/python3.10/dist-packages (from pyplastimatch==0.4.2) (3.7.1)\n",
      "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from pyplastimatch==0.4.2) (1.26.4)\n",
      "Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from pyplastimatch==0.4.2) (2.2.2)\n",
      "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from pyplastimatch==0.4.2) (2.32.3)\n",
      "Requirement already satisfied: scikit-image in /usr/local/lib/python3.10/dist-packages (from pyplastimatch==0.4.2) (0.24.0)\n",
      "Requirement already satisfied: pillow>=8.3 in /usr/local/lib/python3.10/dist-packages (from highdicom==0.21.0) (10.4.0)\n",
      "Collecting pillow-jpls>=1.0 (from highdicom==0.21.0)\n",
      "  Downloading pillow_jpls-1.3.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (3.1 kB)\n",
      "Collecting miutil[web] (from dcm2niix)\n",
      "  Downloading miutil-0.12.0-py3-none-any.whl.metadata (4.7 kB)\n",
      "Requirement already satisfied: PyYAML in /usr/local/lib/python3.10/dist-packages (from pyaml) (6.0.2)\n",
      "Requirement already satisfied: click in /usr/local/lib/python3.10/dist-packages (from idc-index) (8.1.7)\n",
      "Collecting duckdb<1.1.0,>=0.10.0 (from idc-index)\n",
      "  Downloading duckdb-1.0.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (762 bytes)\n",
      "Collecting idc-index-data==19.0.2 (from idc-index)\n",
      "  Downloading idc_index_data-19.0.2-py3-none-any.whl.metadata (5.4 kB)\n",
      "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from idc-index) (24.1)\n",
      "Collecting pandas (from pyplastimatch==0.4.2)\n",
      "  Downloading pandas-2.1.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (18 kB)\n",
      "Requirement already satisfied: platformdirs in /usr/local/lib/python3.10/dist-packages (from idc-index) (4.3.6)\n",
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      "  Downloading s5cmd-0.2.0-py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (5.7 kB)\n",
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      "Collecting PyWavelets>=0.4.0 (from pyradiomics)\n",
      "  Downloading pywavelets-1.7.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (9.0 kB)\n",
      "Collecting pykwalify>=1.6.0 (from pyradiomics)\n",
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      "Requirement already satisfied: six>=1.10.0 in /usr/local/lib/python3.10/dist-packages (from pyradiomics) (1.16.0)\n",
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      "Collecting docopt>=0.6.2 (from pykwalify>=1.6.0->pyradiomics)\n",
      "  Downloading docopt-0.6.2.tar.gz (25 kB)\n",
      "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
      "Collecting ruamel.yaml>=0.16.0 (from pykwalify>=1.6.0->pyradiomics)\n",
      "  Downloading ruamel.yaml-0.18.6-py3-none-any.whl.metadata (23 kB)\n",
      "Collecting itk-core==5.4.0 (from itk->pyplastimatch==0.4.2)\n",
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      "Collecting itk-filtering==5.4.0 (from itk->pyplastimatch==0.4.2)\n",
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      "  Downloading itk_registration-5.4.0-cp310-cp310-manylinux_2_28_x86_64.whl.metadata (22 kB)\n",
      "Collecting itk-segmentation==5.4.0 (from itk->pyplastimatch==0.4.2)\n",
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      "  Downloading ruamel.yaml.clib-0.2.8-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_24_x86_64.whl.metadata (2.2 kB)\n",
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      "\u001b[?25hDownloading itk_segmentation-5.4.0-cp310-cp310-manylinux_2_28_x86_64.whl (15.8 MB)\n",
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      "\u001b[?25hDownloading s5cmd-0.2.0-py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (4.7 MB)\n",
      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m4.7/4.7 MB\u001b[0m \u001b[31m87.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[?25hDownloading ruamel.yaml-0.18.6-py3-none-any.whl (117 kB)\n",
      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m117.8/117.8 kB\u001b[0m \u001b[31m7.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[?25hDownloading miutil-0.12.0-py3-none-any.whl (18 kB)\n",
      "Downloading ruamel.yaml.clib-0.2.8-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_24_x86_64.whl (526 kB)\n",
      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m526.7/526.7 kB\u001b[0m \u001b[31m31.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[?25hBuilding wheels for collected packages: dcm2niix, pyradiomics, docopt\n",
      "  Building wheel for dcm2niix (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
      "  Created wheel for dcm2niix: filename=dcm2niix-1.0.20220715-cp310-cp310-linux_x86_64.whl size=559550 sha256=492fd7ee4e12e335457988d687f90b7b5201659bfef8fde39ba2e011bf561c32\n",
      "  Stored in directory: /root/.cache/pip/wheels/88/8d/9b/5ea20c0451a1acddef585757be7dfec121ee076e58503b267c\n",
      "  Building wheel for pyradiomics (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
      "  Created wheel for pyradiomics: filename=pyradiomics-3.0.1-cp310-cp310-linux_x86_64.whl size=169763 sha256=fbba56ea9996a00e81e20d38d2ffa420a0fbb273e1089308f62ddb846b79b212\n",
      "  Stored in directory: /root/.cache/pip/wheels/91/c5/13/c5fd4c5ad3edf4062bb3855bd66fad25871c9c6dc0b3fda544\n",
      "  Building wheel for docopt (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
      "  Created wheel for docopt: filename=docopt-0.6.2-py2.py3-none-any.whl size=13704 sha256=e0d61aff500bc858dd041657f70427b0f1805baf231adb2af5fb03b1057f8b33\n",
      "  Stored in directory: /root/.cache/pip/wheels/fc/ab/d4/5da2067ac95b36618c629a5f93f809425700506f72c9732fac\n",
      "Successfully built dcm2niix pyradiomics docopt\n",
      "Installing collected packages: SimpleITK, docopt, s5cmd, ruamel.yaml.clib, PyWavelets, pydicom, pyaml, pillow-jpls, miutil, itk-core, idc-index-data, duckdb, ruamel.yaml, pandas, itk-numerics, itk-io, highdicom, pykwalify, itk-filtering, idc-index, dcm2niix, pyradiomics, itk-segmentation, itk-registration, itk, pyplastimatch\n",
      "  Attempting uninstall: duckdb\n",
      "    Found existing installation: duckdb 1.1.1\n",
      "    Uninstalling duckdb-1.1.1:\n",
      "      Successfully uninstalled duckdb-1.1.1\n",
      "  Attempting uninstall: pandas\n",
      "    Found existing installation: pandas 2.2.2\n",
      "    Uninstalling pandas-2.2.2:\n",
      "      Successfully uninstalled pandas-2.2.2\n",
      "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
      "google-colab 1.0.0 requires pandas==2.2.2, but you have pandas 2.1.4 which is incompatible.\u001b[0m\u001b[31m\n",
      "\u001b[0mSuccessfully installed PyWavelets-1.7.0 SimpleITK-2.3.0 dcm2niix-1.0.20220715 docopt-0.6.2 duckdb-1.0.0 highdicom-0.21.0 idc-index-0.7.3 idc-index-data-19.0.2 itk-5.4.0 itk-core-5.4.0 itk-filtering-5.4.0 itk-io-5.4.0 itk-numerics-5.4.0 itk-registration-5.4.0 itk-segmentation-5.4.0 miutil-0.12.0 pandas-2.1.4 pillow-jpls-1.3.2 pyaml-24.9.0 pydicom-2.4.3 pykwalify-1.8.0 pyplastimatch-0.4.2 pyradiomics-3.0.1 ruamel.yaml-0.18.6 ruamel.yaml.clib-0.2.8 s5cmd-0.2.0\n",
      "PyPlastimatch Plastimatch installation utility.\n",
      "NOTE: this utility is not meant to be replace the normal install of Plastimatch via apt.\n",
      "Rather, it is meant to be used in case a Plastimatch binary is not available for a specific distribution.\n",
      "\n",
      "System distribution: Ubuntu 22.04\n",
      "\n",
      "Downloading meta JSON in the temp directory /tmp/tmpjly6dm2w/release_meta.json... Done.\n",
      "Matching distribution found in the latest PyPlastimatch release.\n",
      "\n",
      "Downloading binary in the temp directory /tmp/tmpjly6dm2w/plastimatch-ubuntu_22_04... Done.\n",
      "\n",
      "Installing binaries... Done.\n",
      "Installing dependencies... Done.\n"
     ]
    }
   ],
   "source": [
    "# !pip install dcm2niix pyaml idc-index pyradiomics SimpleITK==2.3.0  pyplastimatch==0.4.2 highdicom==0.21.0 pydicom==2.4.3\n",
    "# from pyplastimatch.utils.install import install_precompiled_binaries\n",
    "# install_precompiled_binaries()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9556f4af",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
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    "execution": {
     "iopub.execute_input": "2024-09-10T04:38:19.157509Z",
     "iopub.status.busy": "2024-09-10T04:38:19.156613Z",
     "iopub.status.idle": "2024-09-10T04:38:19.160837Z",
     "shell.execute_reply": "2024-09-10T04:38:19.159958Z"
    },
    "id": "9556f4af",
    "outputId": "32f46709-9282-41d9-cd6e-0d4713a55dda",
    "papermill": {
     "duration": 0.015328,
     "end_time": "2024-09-10T04:38:19.162895",
     "exception": false,
     "start_time": "2024-09-10T04:38:19.147567",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--2024-10-10 20:12:22--  https://github.com/QIICR/dcmqi/releases/download/v1.3.4/dcmqi-1.3.4-linux.tar.gz\n",
      "Resolving github.com (github.com)... 140.82.112.4\n",
      "Connecting to github.com (github.com)|140.82.112.4|:443... connected.\n",
      "HTTP request sent, awaiting response... 302 Found\n",
      "Location: https://objects.githubusercontent.com/github-production-release-asset-2e65be/50675718/100afc23-a279-4a81-9202-a77bf1e574b9?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=releaseassetproduction%2F20241010%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20241010T201222Z&X-Amz-Expires=300&X-Amz-Signature=3645cf7d7b4d0e173e0357cb3d15feba6976faa809e722d6bb62fe911dc2e79d&X-Amz-SignedHeaders=host&response-content-disposition=attachment%3B%20filename%3Ddcmqi-1.3.4-linux.tar.gz&response-content-type=application%2Foctet-stream [following]\n",
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      "Resolving objects.githubusercontent.com (objects.githubusercontent.com)... 185.199.108.133, 185.199.109.133, 185.199.111.133, ...\n",
      "Connecting to objects.githubusercontent.com (objects.githubusercontent.com)|185.199.108.133|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 40472151 (39M) [application/octet-stream]\n",
      "Saving to: ‘dcmqi-1.3.4-linux.tar.gz’\n",
      "\n",
      "dcmqi-1.3.4-linux.t 100%[===================>]  38.60M  90.5MB/s    in 0.4s    \n",
      "\n",
      "2024-10-10 20:12:23 (90.5 MB/s) - ‘dcmqi-1.3.4-linux.tar.gz’ saved [40472151/40472151]\n",
      "\n",
      "dcmqi-1.3.4-linux/lib/\n",
      "dcmqi-1.3.4-linux/lib/dcmqi-1.3/\n",
      "dcmqi-1.3.4-linux/lib/dcmqi-1.3/libITKniftiio-5.3.a\n",
      "dcmqi-1.3.4-linux/lib/dcmqi-1.3/libITKznz-5.3.a\n",
      "dcmqi-1.3.4-linux/share/\n",
      "dcmqi-1.3.4-linux/share/doc/\n",
      "dcmqi-1.3.4-linux/share/doc/ITK-5.3/\n",
      "dcmqi-1.3.4-linux/share/doc/ITK-5.3/itksys/\n",
      "dcmqi-1.3.4-linux/share/doc/ITK-5.3/itksys/Copyright.txt\n",
      "dcmqi-1.3.4-linux/bin/\n",
      "dcmqi-1.3.4-linux/bin/itkimage2paramap\n",
      "dcmqi-1.3.4-linux/bin/tid1500writer.xml\n",
      "dcmqi-1.3.4-linux/bin/paramap2itkimage.xml\n",
      "dcmqi-1.3.4-linux/bin/tid1500reader\n",
      "dcmqi-1.3.4-linux/bin/itkimage2paramap.xml\n",
      "dcmqi-1.3.4-linux/bin/paramap2itkimage\n",
      "dcmqi-1.3.4-linux/bin/segimage2itkimage.xml\n",
      "dcmqi-1.3.4-linux/bin/segimage2itkimage\n",
      "dcmqi-1.3.4-linux/bin/itkimage2segimage.xml\n",
      "dcmqi-1.3.4-linux/bin/tid1500reader.xml\n",
      "dcmqi-1.3.4-linux/bin/itkimage2segimage\n",
      "dcmqi-1.3.4-linux/bin/tid1500writer\n"
     ]
    }
   ],
   "source": [
    "# dcmqi_release_url = \"https://github.com/QIICR/dcmqi/releases/download/v1.3.4/dcmqi-1.3.4-linux.tar.gz\"\n",
    "# dcmqi_download_path = \"dcmqi-1.3.4-linux.tar.gz\"\n",
    "# dcmqi_path = \"dcmqi-1.3.4-linux\"\n",
    "# !wget -O $dcmqi_download_path $dcmqi_release_url\\\n",
    "# && tar -xvf $dcmqi_download_path\\\n",
    "# && mv $dcmqi_path/bin/* /bin\\\n",
    "# && rm -r $dcmqi_download_path $dcmqi_path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "271a85f2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-10T04:38:19.179890Z",
     "iopub.status.busy": "2024-09-10T04:38:19.179164Z",
     "iopub.status.idle": "2024-09-10T04:38:22.503594Z",
     "shell.execute_reply": "2024-09-10T04:38:22.502290Z"
    },
    "id": "271a85f2",
    "papermill": {
     "duration": 3.336256,
     "end_time": "2024-09-10T04:38:22.506622",
     "exception": false,
     "start_time": "2024-09-10T04:38:19.170366",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Imports\n",
    "\n",
    "import os\n",
    "import json\n",
    "import glob\n",
    "\n",
    "import numpy as np\n",
    "\n",
    "import shutil\n",
    "\n",
    "import pyplastimatch as pypla\n",
    "\n",
    "import math\n",
    "import pandas as pd\n",
    "import SimpleITK as sitk\n",
    "\n",
    "from os.path import abspath\n",
    "\n",
    "import pydicom\n",
    "\n",
    "from idc_index import index\n",
    "client = index.IDCClient()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "418fc7dc",
   "metadata": {
    "id": "418fc7dc",
    "papermill": {
     "duration": 0.007524,
     "end_time": "2024-09-10T04:38:22.522124",
     "exception": false,
     "start_time": "2024-09-10T04:38:22.514600",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Global Variables\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "b3a5f11a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-10T04:38:22.538981Z",
     "iopub.status.busy": "2024-09-10T04:38:22.538171Z",
     "iopub.status.idle": "2024-09-10T04:38:22.543154Z",
     "shell.execute_reply": "2024-09-10T04:38:22.542216Z"
    },
    "id": "b3a5f11a",
    "papermill": {
     "duration": 0.015778,
     "end_time": "2024-09-10T04:38:22.545195",
     "exception": false,
     "start_time": "2024-09-10T04:38:22.529417",
     "status": "completed"
    },
    "tags": [
     "parameters"
    ]
   },
   "outputs": [],
   "source": [
    "#absolute path output\n",
    "OUTPUT_PATH = \"\"#\"TEST\"#\"radiomics_task\"#\"\"\n",
    "#input MHUB zip file\n",
    "SEG_OUTPUT = \"\"#\"ai_combination_archive.tar.lz4\"#\"/content/radiomics_idc_output.tar.lz4\"#\"\"\n",
    "#segments parameters\n",
    "dicom_sr_CodeValues_lst = []#[ \"41216001\", \"279706003\", \"399384005\" ]\n",
    "dicom_sr_codeMeaning_lst = []#[ \"Prostatic_structure\", \"Structure_of_peripheral_glandular_zone_of_prostate_(body_structure)\", \"Structure_of_transition_zone_of_prostate_(body_structure)\" ]\n",
    "dicom_sr_CodingSchemeDesignator_lst = []#[ \"SCT\", \"SCT\", \"SCT\" ]\n",
    "#AlgorithmName\n",
    "terraRadSeriesDescription = \"\"#\"bamf_nnunet_mr_prostate\"\n",
    "res_scheme_format = \"\"#nii,nrrd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "679c81c6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-10T04:38:22.585223Z",
     "iopub.status.busy": "2024-09-10T04:38:22.584303Z",
     "iopub.status.idle": "2024-09-10T04:38:22.590385Z",
     "shell.execute_reply": "2024-09-10T04:38:22.589526Z"
    },
    "id": "679c81c6",
    "papermill": {
     "duration": 0.017031,
     "end_time": "2024-09-10T04:38:22.592311",
     "exception": false,
     "start_time": "2024-09-10T04:38:22.575280",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "SEG_OUTPUT_UNZIP = os.path.join(OUTPUT_PATH, \"seg_unzip\")\n",
    "\n",
    "seg_base_folder = os.path.join(OUTPUT_PATH, \"seg_objects\")\n",
    "\n",
    "seg_nii_folder = os.path.join(seg_base_folder, \"nii\")\n",
    "seg_nii_resampled_folder = os.path.join(seg_base_folder, \"nii_resampled\")\n",
    "seg_nii_resampled_renamed_folder = os.path.join(seg_base_folder, \"nii_resampled_renamed\")\n",
    "seg_sr_dicom_folder = os.path.join(seg_base_folder, \"dicom_sr\")\n",
    "seg_sr_json_dicom_folder = os.path.join(seg_base_folder, \"dicom_sr_json\")\n",
    "\n",
    "#IDC EVALUATION DATA\n",
    "## Image\n",
    "IDC_IMAGE_DICOM = os.path.join(OUTPUT_PATH, \"idc_image_data/dicom\")\n",
    "IDC_IMAGE_NII = os.path.join(OUTPUT_PATH, \"idc_image_data/nii\")\n",
    "IDC_IMAGE_NRRD = os.path.join(OUTPUT_PATH,\"idc_image_data/nrrd\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "9039b951",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-10T04:38:22.609862Z",
     "iopub.status.busy": "2024-09-10T04:38:22.609056Z",
     "iopub.status.idle": "2024-09-10T04:38:22.615376Z",
     "shell.execute_reply": "2024-09-10T04:38:22.614583Z"
    },
    "id": "9039b951",
    "papermill": {
     "duration": 0.017386,
     "end_time": "2024-09-10T04:38:22.617186",
     "exception": false,
     "start_time": "2024-09-10T04:38:22.599800",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def setup_folders():\n",
    "\t\"\"\"\n",
    "\tcreates environment data and results folder, first deletes current ones and then creates new ones\n",
    "\t\"\"\"\n",
    "\tfor folder_setup in [OUTPUT_PATH, SEG_OUTPUT_UNZIP, seg_base_folder,\n",
    "\t\t\t\t\t\t\t\t\t\t\t seg_nii_folder, seg_nii_resampled_folder,\n",
    "\t\t\t\t\t\t\t\t\t\t\t seg_sr_dicom_folder, seg_sr_json_dicom_folder,\n",
    "\t\t\t\t\t\t\t\t\t\t\t IDC_IMAGE_DICOM, IDC_IMAGE_NII, IDC_IMAGE_NRRD]:\n",
    "\t\t!rm -rf $folder_setup\n",
    "\t\t!mkdir -p $folder_setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "5e0ac0b5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-10T04:38:22.634226Z",
     "iopub.status.busy": "2024-09-10T04:38:22.633437Z",
     "iopub.status.idle": "2024-09-10T04:38:25.032586Z",
     "shell.execute_reply": "2024-09-10T04:38:25.031115Z"
    },
    "id": "5e0ac0b5",
    "papermill": {
     "duration": 2.411405,
     "end_time": "2024-09-10T04:38:25.036098",
     "exception": false,
     "start_time": "2024-09-10T04:38:22.624693",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "setup_folders()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "924ea23b",
   "metadata": {
    "id": "924ea23b",
    "papermill": {
     "duration": 0.00769,
     "end_time": "2024-09-10T04:38:25.059217",
     "exception": false,
     "start_time": "2024-09-10T04:38:25.051527",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Utility functions"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "869990f5",
   "metadata": {
    "id": "869990f5",
    "papermill": {
     "duration": 0.00729,
     "end_time": "2024-09-10T04:38:25.073964",
     "exception": false,
     "start_time": "2024-09-10T04:38:25.066674",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Conversion DICOM <---> NII"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "72c8ec12",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-10T04:38:25.091229Z",
     "iopub.status.busy": "2024-09-10T04:38:25.090846Z",
     "iopub.status.idle": "2024-09-10T04:38:25.098073Z",
     "shell.execute_reply": "2024-09-10T04:38:25.097125Z"
    },
    "id": "72c8ec12",
    "papermill": {
     "duration": 0.018701,
     "end_time": "2024-09-10T04:38:25.100165",
     "exception": false,
     "start_time": "2024-09-10T04:38:25.081464",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def convert_image_dcm_to_nii(input_path, output_path_root, prefix=\"\", format=\"nii\"):\n",
    "\t\"\"\"\n",
    "\tConversion of DICOM MR data to NIFTI using dcm2niix\n",
    "\tinput_path : str, folder containing DICOM instances .dcm\n",
    "\toutput_path_root : str, output folder\n",
    "\tprefix : str, prefix for output file name\n",
    "\t\"\"\"\n",
    "\tif not os.path.exists(output_path_root):\n",
    "\t\t!mkdir -p $output_path_root\n",
    "\t!dcm2niix -z y -m y -f %i_{prefix} -o $output_path_root $input_path"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d91c3b07",
   "metadata": {
    "id": "d91c3b07",
    "papermill": {
     "duration": 0.007366,
     "end_time": "2024-09-10T04:38:25.115078",
     "exception": false,
     "start_time": "2024-09-10T04:38:25.107712",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Resampling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8fa29eb8",
   "metadata": {},
   "outputs": [],
   "source": [
    "def resample_seg_with_sitk(input_seg_nifti_path, input_dicom_path, output_seg_path):\n",
    "  print(\"Reading Dicom directory:\", input_dicom_path)\n",
    "  reader = sitk.ImageSeriesReader()\n",
    "  dicom_names = reader.GetGDCMSeriesFileNames(input_dicom_path)\n",
    "  reader.SetFileNames(dicom_names)\n",
    "  target_dicom_img_itk = reader.Execute()\n",
    "  # define a sitk identity transform\n",
    "  identity_tfx = sitk.Transform(3, sitk.sitkIdentity)\n",
    "  seg_itk = sitk.ReadImage(input_seg_nifti_path)\n",
    "  # align the segmentation mask to the target dicom image (to get a uniform z height as per the target dicom image)\n",
    "  seg_aligned_itk = sitk.Resample(seg_itk, target_dicom_img_itk, identity_tfx, sitk.sitkNearestNeighbor, 0)\n",
    "  # overwrite output file with aligned image data\n",
    "  sitk.WriteImage(seg_aligned_itk, output_seg_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "6f192dc1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-10T04:38:25.132478Z",
     "iopub.status.busy": "2024-09-10T04:38:25.131626Z",
     "iopub.status.idle": "2024-09-10T04:38:25.139979Z",
     "shell.execute_reply": "2024-09-10T04:38:25.138800Z"
    },
    "id": "6f192dc1",
    "papermill": {
     "duration": 0.019664,
     "end_time": "2024-09-10T04:38:25.142074",
     "exception": false,
     "start_time": "2024-09-10T04:38:25.122410",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def resample_preds(input_path_nnunet_preds=\"\", input_path_t2_idc=\"\", output_path=\"\"):\n",
    "\t\"\"\"\n",
    "\tResampling of nnunet_preds to reference MR T2 volumes used as input image\n",
    "\tinput_path_nnunet_preds : str, folder containing nnunet preds\n",
    "\tinput_path_t2_idc : str, folder containing NIFTI IDC MR T2 volumes\n",
    "\toutput_path : str, folder output\n",
    "\t\"\"\"\n",
    "\tfor pred_path in sorted(glob.glob(os.path.join(input_path_nnunet_preds, \"*.nii.gz\"))):\n",
    "\t\tprint(f\"pred path : {pred_path}\")\n",
    "\t\tresample_args_to_t2_origin = {\"input\" : pred_path,#change to pred path if no largest_component_retrieval necessary\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\"output\" : os.path.join(output_path,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tf\"{pred_path.split('/')[-1][:-7]}.nii.gz\"),\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\"fixed\" : input_path_t2_idc,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\"interpolation\" : \"nn\"}\n",
    "\n",
    "\t\tpypla.resample(verbose = False, **resample_args_to_t2_origin)\n",
    "\t\tprint()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f3ef5cf",
   "metadata": {
    "id": "0f3ef5cf",
    "papermill": {
     "duration": 0.007378,
     "end_time": "2024-09-10T04:38:25.157032",
     "exception": false,
     "start_time": "2024-09-10T04:38:25.149654",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Combine segs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "aac8d52c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-10T04:38:25.174972Z",
     "iopub.status.busy": "2024-09-10T04:38:25.174039Z",
     "iopub.status.idle": "2024-09-10T04:38:25.182038Z",
     "shell.execute_reply": "2024-09-10T04:38:25.181045Z"
    },
    "id": "aac8d52c",
    "papermill": {
     "duration": 0.019369,
     "end_time": "2024-09-10T04:38:25.183975",
     "exception": false,
     "start_time": "2024-09-10T04:38:25.164606",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def add_segments_json(input_json, segmentAttributesProstate_lst):\n",
    "\tassert os.path.exists(input_json)\n",
    "\tinp_json = json.load(open(input_json)).copy()\n",
    "\tprint(inp_json[\"segmentAttributes\"])\n",
    "\tprint(type(inp_json[\"segmentAttributes\"]))\n",
    "\ttemp_lst = inp_json[\"segmentAttributes\"].copy()\n",
    "\ttemp_lst.append(segmentAttributesProstate_lst)\n",
    "\tinp_json[\"segmentAttributes\"] = temp_lst\n",
    "\tprint(inp_json[\"segmentAttributes\"])\n",
    "\n",
    "\treturn inp_json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "ff7c498f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-10T04:38:25.201790Z",
     "iopub.status.busy": "2024-09-10T04:38:25.201400Z",
     "iopub.status.idle": "2024-09-10T04:38:25.209733Z",
     "shell.execute_reply": "2024-09-10T04:38:25.208785Z"
    },
    "id": "ff7c498f",
    "papermill": {
     "duration": 0.020599,
     "end_time": "2024-09-10T04:38:25.212509",
     "exception": false,
     "start_time": "2024-09-10T04:38:25.191910",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def retrieve_meta_df_from_json(meta_json_path):\n",
    "\tout_segment_list = []\n",
    "\tjson_dic = json.load(open(meta_json_path))\n",
    "\tfor segment_iter in json_dic[\"segmentAttributes\"]:\n",
    "\t\ttemp_dic = {}\n",
    "\t\ttemp_dic = segment_iter\n",
    "\t\tout_segment_list.append(temp_dic[0])\n",
    "\tout_df = pd.DataFrame.from_dict(out_segment_list)\n",
    "\tdf_SegmentedPropertyTypeCodeSequence = pd.json_normalize(out_df['SegmentedPropertyTypeCodeSequence']).rename(columns={'CodeMeaning': 'FindingSite_CodeMeaning',\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t'CodeValue':'FindingSite_CodeValue',\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t'CodingSchemeDesignator': 'FindingSite_CodingSchemeDesignator'})\n",
    "\tdf_SegmentedPropertyCategoryCodeSequence = pd.json_normalize(out_df['SegmentedPropertyCategoryCodeSequence']).rename(columns={'CodeMeaning': 'Finding_CodeMeaning',\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t'CodeValue':'Finding_CodeValue',\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t'CodingSchemeDesignator': 'Finding_CodingSchemeDesignator'})\n",
    "\tdf_columns_lst = list(out_df.columns.values)\n",
    "\tcols_to_retrieve = []\n",
    "\tfor col_test in [\"SegmentAlgorithmName\",\"SegmentAlgorithmType\",\n",
    "\t\t\t\t\t\t\t\t\t \"SegmentDescription\",\"SegmentLabel\"]:\n",
    "\t\tif col_test in df_columns_lst:\n",
    "\t\t\t\tcols_to_retrieve.append(col_test)\n",
    "\t\telse:\n",
    "\t\t\tpass\n",
    "\tdf_final = df_SegmentedPropertyTypeCodeSequence.join(df_SegmentedPropertyCategoryCodeSequence).join(out_df[[\"labelID\"]\\\n",
    "\t\t+ cols_to_retrieve])\n",
    "\tdf_final[\"segment\"] = df_final[\"FindingSite_CodeMeaning\"]\n",
    "\tdf_final[\"SeriesDescription\"] = json_dic[\"SeriesDescription\"]\n",
    "\tdf_final[\"SeriesNumber\"] = json_dic[\"SeriesNumber\"]\n",
    "\tdf_final[\"BodyPartExamined\"] = json_dic[\"BodyPartExamined\"]\n",
    "\tdf_final = df_final.reset_index().drop(columns=[\"index\"])\n",
    "\treturn df_final"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "484865d1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-10T04:38:25.241187Z",
     "iopub.status.busy": "2024-09-10T04:38:25.240822Z",
     "iopub.status.idle": "2024-09-10T04:38:25.249081Z",
     "shell.execute_reply": "2024-09-10T04:38:25.248099Z"
    },
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    "papermill": {
     "duration": 0.023501,
     "end_time": "2024-09-10T04:38:25.251519",
     "exception": false,
     "start_time": "2024-09-10T04:38:25.228018",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def generateProstateDcmqiMetadata(labelID, SegmentAlgorithmType,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tSegmentAlgorithmName,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tSegmentLabel,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tSegmentDescription,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tSegmentedPropertyCategoryCodeSequenceCodeValue,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tSegmentedPropertyCategoryCodeSequenceCodingSchemeDesignator,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tSegmentedPropertyCategoryCodeSequenceCodeMeaning,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tSegmentedPropertyTypeCodeSequenceCodeValue,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tSegmentedPropertyTypeCodeSequenceCodingSchemeDesignator,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tSegmentedPropertyTypeCodeSequenceCodeMeaning,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\trecommendedDisplayRGBValue):\n",
    "\tout_lst = []\n",
    "\tif SegmentAlgorithmName is not None:\n",
    "\t\tout_lst.append({\"SegmentAlgorithmName\" : SegmentAlgorithmName,\n",
    "\t\t\t\t\t\t\t\t\t\t\"SegmentAlgorithmType\" : SegmentAlgorithmType,\n",
    "\t\t\t\t\t\t\t\t\t\t\"SegmentLabel\" : SegmentLabel,\n",
    "\t\t\t\t\t\t\t\t\t\t\"SegmentDescription\" : SegmentDescription,\n",
    "\t\t\t\t\t\t\t\t\t\t\"SegmentedPropertyCategoryCodeSequence\" : {\n",
    "\t\t\t\t\t\t\t\t\t\t\t\"CodeMeaning\" : SegmentedPropertyCategoryCodeSequenceCodeMeaning,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\"CodeValue\" : SegmentedPropertyCategoryCodeSequenceCodeValue,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\"CodingSchemeDesignator\" : SegmentedPropertyCategoryCodeSequenceCodingSchemeDesignator,\n",
    "\t\t\t\t\t\t\t\t\t\t},\n",
    "\t\t\t\t\t\t\t\t\t\t\"SegmentedPropertyTypeCodeSequence\" : {\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\"CodeMeaning\" : SegmentedPropertyTypeCodeSequenceCodeMeaning,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\"CodeValue\" : SegmentedPropertyTypeCodeSequenceCodeValue,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\"CodingSchemeDesignator\" : SegmentedPropertyTypeCodeSequenceCodingSchemeDesignator,\n",
    "\t\t\t\t\t\t\t\t\t\t},\n",
    "\t\t\t\t\t\t\t\t\t\t\"labelID\" : int(labelID),\n",
    "\t\t\t\t\t\t\t\t\t\t\"recommendedDisplayRGBValue\" : [int(x) for x in recommendedDisplayRGBValue]})\n",
    "\telse:\n",
    "\t\tout_lst.append({\"SegmentAlgorithmType\" : SegmentAlgorithmType,\n",
    "\t\t\t\t\t\t\t\t\t\t\"SegmentLabel\" : SegmentLabel,\n",
    "\t\t\t\t\t\t\t\t\t\t\"SegmentDescription\" : SegmentDescription,\n",
    "\t\t\t\t\t\t\t\t\t\t\"SegmentedPropertyCategoryCodeSequence\" : {\n",
    "\t\t\t\t\t\t\t\t\t\t\t\"CodeMeaning\" : SegmentedPropertyCategoryCodeSequenceCodeMeaning,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\"CodeValue\" : SegmentedPropertyCategoryCodeSequenceCodeValue,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\"CodingSchemeDesignator\" : SegmentedPropertyCategoryCodeSequenceCodingSchemeDesignator,\n",
    "\t\t\t\t\t\t\t\t\t\t},\n",
    "\t\t\t\t\t\t\t\t\t\t\"SegmentedPropertyTypeCodeSequence\" : {\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\"CodeMeaning\" : SegmentedPropertyTypeCodeSequenceCodeMeaning,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\"CodeValue\" : SegmentedPropertyTypeCodeSequenceCodeValue,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\"CodingSchemeDesignator\" : SegmentedPropertyTypeCodeSequenceCodingSchemeDesignator,\n",
    "\t\t\t\t\t\t\t\t\t\t},\n",
    "\t\t\t\t\t\t\t\t\t\t\"labelID\" : int(labelID),\n",
    "\t\t\t\t\t\t\t\t\t\t\"recommendedDisplayRGBValue\" : [int(x) for x in recommendedDisplayRGBValue]})\n",
    "\treturn out_lst"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "aec3d03c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-10T04:38:25.282043Z",
     "iopub.status.busy": "2024-09-10T04:38:25.281563Z",
     "iopub.status.idle": "2024-09-10T04:38:25.288203Z",
     "shell.execute_reply": "2024-09-10T04:38:25.287241Z"
    },
    "id": "aec3d03c",
    "papermill": {
     "duration": 0.022993,
     "end_time": "2024-09-10T04:38:25.290388",
     "exception": false,
     "start_time": "2024-09-10T04:38:25.267395",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def combine_ind_seg(input_nii_folder, output_file_path):\n",
    "\tassert os.path.exists(input_nii_folder)\n",
    "\tout_arr = np.zeros_like(sitk.GetArrayFromImage(sitk.ReadImage(glob.glob(os.path.join(input_nii_folder, \"*.nii.gz\"))[0])))\n",
    "\tfor segment_processed in sorted(glob.glob(os.path.join(input_nii_folder, \"*.nii.gz\"))):\n",
    "\t\tout_arr += sitk.GetArrayFromImage(sitk.ReadImage(segment_processed))\n",
    "\tres_img = sitk.GetImageFromArray(out_arr)\n",
    "\tres_img.CopyInformation(sitk.ReadImage(glob.glob(os.path.join(input_nii_folder, \"*.nii.gz\"))[0]))\n",
    "\t# Save output segment\n",
    "\tsitk.WriteImage(res_img, output_file_path)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9e10d843",
   "metadata": {
    "id": "9e10d843",
    "papermill": {
     "duration": 0.007904,
     "end_time": "2024-09-10T04:38:25.306199",
     "exception": false,
     "start_time": "2024-09-10T04:38:25.298295",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## DICOM metadata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "d6898f52",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-10T04:38:25.324407Z",
     "iopub.status.busy": "2024-09-10T04:38:25.323360Z",
     "iopub.status.idle": "2024-09-10T04:38:25.329098Z",
     "shell.execute_reply": "2024-09-10T04:38:25.328095Z"
    },
    "id": "d6898f52",
    "papermill": {
     "duration": 0.017169,
     "end_time": "2024-09-10T04:38:25.331122",
     "exception": false,
     "start_time": "2024-09-10T04:38:25.313953",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def retrieve_image_serieUID_dcm_seg(inp_dicom_seg):\n",
    "\treturn str(pydicom.dcmread(inp_dicom_seg).ReferencedSeriesSequence[0].SeriesInstanceUID)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "01ffe471",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-10T04:38:25.348700Z",
     "iopub.status.busy": "2024-09-10T04:38:25.348183Z",
     "iopub.status.idle": "2024-09-10T04:38:25.354087Z",
     "shell.execute_reply": "2024-09-10T04:38:25.352800Z"
    },
    "id": "01ffe471",
    "papermill": {
     "duration": 0.017189,
     "end_time": "2024-09-10T04:38:25.356158",
     "exception": false,
     "start_time": "2024-09-10T04:38:25.338969",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def get_tag_pydicom(path_dcm_file : str, tag_name : str):\n",
    "\tdataset = pydicom.dcmread(path_dcm_file)\n",
    "\treturn dataset[tag_name]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "70288c9b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-10T04:38:25.376557Z",
     "iopub.status.busy": "2024-09-10T04:38:25.376074Z",
     "iopub.status.idle": "2024-09-10T04:38:25.385176Z",
     "shell.execute_reply": "2024-09-10T04:38:25.383954Z"
    },
    "id": "70288c9b",
    "papermill": {
     "duration": 0.021994,
     "end_time": "2024-09-10T04:38:25.387155",
     "exception": false,
     "start_time": "2024-09-10T04:38:25.365161",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def retrieve_meta_df_from_json(meta_json_path):\n",
    "\tout_segment_list = []\n",
    "\tjson_dic = json.load(open(meta_json_path))\n",
    "\tfor segment_iter in json_dic[\"segmentAttributes\"]:\n",
    "\t\ttemp_dic = {}\n",
    "\t\ttemp_dic = segment_iter\n",
    "\t\tout_segment_list.append(temp_dic[0])\n",
    "\tout_df = pd.DataFrame.from_dict(out_segment_list)\n",
    "\tdf_SegmentedPropertyTypeCodeSequence = pd.json_normalize(out_df['SegmentedPropertyTypeCodeSequence']).rename(columns={'CodeMeaning': 'FindingSite_CodeMeaning',\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t'CodeValue':'FindingSite_CodeValue',\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t'CodingSchemeDesignator': 'FindingSite_CodingSchemeDesignator'})\n",
    "\tdf_SegmentedPropertyCategoryCodeSequence = pd.json_normalize(out_df['SegmentedPropertyCategoryCodeSequence']).rename(columns={'CodeMeaning': 'Finding_CodeMeaning',\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t'CodeValue':'Finding_CodeValue',\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t'CodingSchemeDesignator': 'Finding_CodingSchemeDesignator'})\n",
    "\tdf_columns_lst = list(out_df.columns.values)\n",
    "\tcols_to_retrieve = []\n",
    "\tfor col_test in [\"SegmentAlgorithmName\",\"SegmentAlgorithmType\",\n",
    "\t\t\t\t\t\t\t\t\t \"SegmentDescription\",\"SegmentLabel\"]:\n",
    "\t\tif col_test in df_columns_lst:\n",
    "\t\t\t\tcols_to_retrieve.append(col_test)\n",
    "\t\telse:\n",
    "\t\t\tpass\n",
    "\tdf_final = df_SegmentedPropertyTypeCodeSequence.join(df_SegmentedPropertyCategoryCodeSequence).join(out_df[[\"labelID\"]\\\n",
    "\t\t+ cols_to_retrieve])\n",
    "\tdf_final[\"segment\"] = df_final[\"FindingSite_CodeMeaning\"]\n",
    "\tdf_final[\"SeriesDescription\"] = json_dic[\"SeriesDescription\"]\n",
    "\tdf_final[\"SeriesNumber\"] = json_dic[\"SeriesNumber\"]\n",
    "\tdf_final[\"BodyPartExamined\"] = json_dic[\"BodyPartExamined\"]\n",
    "\tdf_final = df_final.reset_index().drop(columns=[\"index\"])\n",
    "\treturn df_final"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "af52ff09",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-10T04:38:25.404647Z",
     "iopub.status.busy": "2024-09-10T04:38:25.404326Z",
     "iopub.status.idle": "2024-09-10T04:38:25.412777Z",
     "shell.execute_reply": "2024-09-10T04:38:25.411687Z"
    },
    "id": "af52ff09",
    "papermill": {
     "duration": 0.019814,
     "end_time": "2024-09-10T04:38:25.414867",
     "exception": false,
     "start_time": "2024-09-10T04:38:25.395053",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def generateProstateDcmqiMetadata(labelID, SegmentAlgorithmType,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tSegmentAlgorithmName,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tSegmentLabel,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tSegmentDescription,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tSegmentedPropertyCategoryCodeSequenceCodeValue,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tSegmentedPropertyCategoryCodeSequenceCodingSchemeDesignator,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tSegmentedPropertyCategoryCodeSequenceCodeMeaning,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tSegmentedPropertyTypeCodeSequenceCodeValue,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tSegmentedPropertyTypeCodeSequenceCodingSchemeDesignator,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tSegmentedPropertyTypeCodeSequenceCodeMeaning,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\trecommendedDisplayRGBValue):\n",
    "\tout_lst = []\n",
    "\tif SegmentAlgorithmName is not None:\n",
    "\t\tout_lst.append({\"SegmentAlgorithmName\" : SegmentAlgorithmName,\n",
    "\t\t\t\t\t\t\t\t\t\t\"SegmentAlgorithmType\" : SegmentAlgorithmType,\n",
    "\t\t\t\t\t\t\t\t\t\t\"SegmentLabel\" : SegmentLabel,\n",
    "\t\t\t\t\t\t\t\t\t\t\"SegmentDescription\" : SegmentDescription,\n",
    "\t\t\t\t\t\t\t\t\t\t\"SegmentedPropertyCategoryCodeSequence\" : {\n",
    "\t\t\t\t\t\t\t\t\t\t\t\"CodeMeaning\" : SegmentedPropertyCategoryCodeSequenceCodeMeaning,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\"CodeValue\" : SegmentedPropertyCategoryCodeSequenceCodeValue,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\"CodingSchemeDesignator\" : SegmentedPropertyCategoryCodeSequenceCodingSchemeDesignator,\n",
    "\t\t\t\t\t\t\t\t\t\t},\n",
    "\t\t\t\t\t\t\t\t\t\t\"SegmentedPropertyTypeCodeSequence\" : {\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\"CodeMeaning\" : SegmentedPropertyTypeCodeSequenceCodeMeaning,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\"CodeValue\" : SegmentedPropertyTypeCodeSequenceCodeValue,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\"CodingSchemeDesignator\" : SegmentedPropertyTypeCodeSequenceCodingSchemeDesignator,\n",
    "\t\t\t\t\t\t\t\t\t\t},\n",
    "\t\t\t\t\t\t\t\t\t\t\"labelID\" : int(labelID),\n",
    "\t\t\t\t\t\t\t\t\t\t\"recommendedDisplayRGBValue\" : [int(x) for x in recommendedDisplayRGBValue]})\n",
    "\telse:\n",
    "\t\tout_lst.append({\"SegmentAlgorithmType\" : SegmentAlgorithmType,\n",
    "\t\t\t\t\t\t\t\t\t\t\"SegmentLabel\" : SegmentLabel,\n",
    "\t\t\t\t\t\t\t\t\t\t\"SegmentDescription\" : SegmentDescription,\n",
    "\t\t\t\t\t\t\t\t\t\t\"SegmentedPropertyCategoryCodeSequence\" : {\n",
    "\t\t\t\t\t\t\t\t\t\t\t\"CodeMeaning\" : SegmentedPropertyCategoryCodeSequenceCodeMeaning,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\"CodeValue\" : SegmentedPropertyCategoryCodeSequenceCodeValue,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\"CodingSchemeDesignator\" : SegmentedPropertyCategoryCodeSequenceCodingSchemeDesignator,\n",
    "\t\t\t\t\t\t\t\t\t\t},\n",
    "\t\t\t\t\t\t\t\t\t\t\"SegmentedPropertyTypeCodeSequence\" : {\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\"CodeMeaning\" : SegmentedPropertyTypeCodeSequenceCodeMeaning,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\"CodeValue\" : SegmentedPropertyTypeCodeSequenceCodeValue,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\"CodingSchemeDesignator\" : SegmentedPropertyTypeCodeSequenceCodingSchemeDesignator,\n",
    "\t\t\t\t\t\t\t\t\t\t},\n",
    "\t\t\t\t\t\t\t\t\t\t\"labelID\" : int(labelID),\n",
    "\t\t\t\t\t\t\t\t\t\t\"recommendedDisplayRGBValue\" : [int(x) for x in recommendedDisplayRGBValue]})\n",
    "\treturn out_lst"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "9be9380a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-10T04:38:25.433577Z",
     "iopub.status.busy": "2024-09-10T04:38:25.432548Z",
     "iopub.status.idle": "2024-09-10T04:38:25.439598Z",
     "shell.execute_reply": "2024-09-10T04:38:25.438527Z"
    },
    "id": "9be9380a",
    "papermill": {
     "duration": 0.018595,
     "end_time": "2024-09-10T04:38:25.441641",
     "exception": false,
     "start_time": "2024-09-10T04:38:25.423046",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def add_segments_json(input_json, segmentAttributesProstate_lst):\n",
    "\tassert os.path.exists(input_json)\n",
    "\tinp_json = json.load(open(input_json)).copy()\n",
    "\tprint(inp_json[\"segmentAttributes\"])\n",
    "\tprint(type(inp_json[\"segmentAttributes\"]))\n",
    "\ttemp_lst = inp_json[\"segmentAttributes\"].copy()\n",
    "\ttemp_lst.append(segmentAttributesProstate_lst)\n",
    "\tinp_json[\"segmentAttributes\"] = temp_lst\n",
    "\tprint(inp_json[\"segmentAttributes\"])\n",
    "\n",
    "\treturn inp_json"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d1a0068d",
   "metadata": {
    "id": "d1a0068d",
    "papermill": {
     "duration": 0.007978,
     "end_time": "2024-09-10T04:38:25.457680",
     "exception": false,
     "start_time": "2024-09-10T04:38:25.449702",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## SR reports creation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "d2219585",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-10T04:38:25.475420Z",
     "iopub.status.busy": "2024-09-10T04:38:25.475045Z",
     "iopub.status.idle": "2024-09-10T04:38:25.482005Z",
     "shell.execute_reply": "2024-09-10T04:38:25.480912Z"
    },
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    "papermill": {
     "duration": 0.018482,
     "end_time": "2024-09-10T04:38:25.484119",
     "exception": false,
     "start_time": "2024-09-10T04:38:25.465637",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def get_label_and_names_from_metadata_json(dicomseg_json):\n",
    "\n",
    "\t\"\"\"Returns two lists containing the label values and the corresponding\n",
    "\t\t CodeMeaning values\n",
    "\n",
    "\tInputs:\n",
    "\t\tdicomseg_json : metajson file\n",
    "\n",
    "\tOutputs:\n",
    "\t\tlabel_values  : label values from the metajson file\n",
    "\t\tlabel_names   : the corresponding CodeMeaning values\n",
    "\n",
    "\t\"\"\"\n",
    "\n",
    "\tf = open(dicomseg_json)\n",
    "\tmeta_json = json.load(f)\n",
    "\n",
    "\tprint(meta_json)\n",
    "\n",
    "\tnum_regions = len(meta_json['segmentAttributes'][0])\n",
    "\tprint ('num_regions: ' + str(num_regions))\n",
    "\n",
    "\tlabel_values = []\n",
    "\tlabel_names = []\n",
    "\tfor n in range(0,num_regions):\n",
    "\t\t# label_values.append(n)\n",
    "\t\tlabel_value = meta_json['segmentAttributes'][0][n]['labelID']\n",
    "\t\tlabel_name = meta_json['segmentAttributes'][0][n]['SegmentedPropertyTypeCodeSequence']['CodeMeaning']\n",
    "\t\tlabel_values.append(label_value)\n",
    "\t\tlabel_names.append(label_name)\n",
    "\n",
    "\treturn label_values, label_names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "5afc2bc3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-10T04:38:25.502045Z",
     "iopub.status.busy": "2024-09-10T04:38:25.501667Z",
     "iopub.status.idle": "2024-09-10T04:38:25.509124Z",
     "shell.execute_reply": "2024-09-10T04:38:25.508008Z"
    },
    "id": "5afc2bc3",
    "papermill": {
     "duration": 0.019029,
     "end_time": "2024-09-10T04:38:25.511302",
     "exception": false,
     "start_time": "2024-09-10T04:38:25.492273",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def split_nii(input_file, output_directory, label_names):\n",
    "\n",
    "\t\"\"\"Function to split a single multilabel nii into individual nii files. Used\n",
    "\t\t for pyradiomics feature extraction.\n",
    "\n",
    "\tInputs:\n",
    "\t\tinput_file       : input multi-label nii file\n",
    "\t\toutput_directory : where to save the individual nii segments\n",
    "\t\tlabel_names      : the names of the labels that correspond to the order of\n",
    "\t\t\t\t\t\t\t\t\t\t\t the values in the nii input_file\n",
    "\n",
    "\tOutputs:\n",
    "\t\tsaves the individual nii files to the output_directory\n",
    "\n",
    "\t\"\"\"\n",
    "\n",
    "\tif not os.path.isdir(output_directory):\n",
    "\t\tos.mkdir(output_directory)\n",
    "\n",
    "\t# save with the values in the files\n",
    "\tnii = nib.load(input_file)\n",
    "\theader = nii.header\n",
    "\timg = nii.get_fdata()\n",
    "\tunique_labels = list(np.unique(img))\n",
    "\tunique_labels.remove(0) # remove the background\n",
    "\n",
    "\t# split and save\n",
    "\tnum_labels = len(unique_labels)\n",
    "\tfor n in range(0,num_labels):\n",
    "\t\tind = np.where(img==unique_labels[n])\n",
    "\t\tvol = np.zeros((img.shape))\n",
    "\t\tvol[ind] = 1\n",
    "\t\tnew_img = nib.Nifti1Image(vol, nii.affine, nii.header)\n",
    "\t\toutput_filename = os.path.join(output_directory, label_names[n] + '.nii.gz')\n",
    "\t\tnib.save(new_img, output_filename)\n",
    "\n",
    "\treturn"
   ]
  },
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   "source": [
    "def compute_pyradiomics_3D_features(ct_nifti_path,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tlabel_values,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tlabel_names,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsplit_pred_nifti_path,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tnnunet_shape_features_code_mapping_df):\n",
    "\n",
    "\t\"\"\"Function to compute pyradiomics 3D features for each label in a nifti file.\n",
    "\n",
    "\tInputs:\n",
    "\t\tct_nifti_path            : the CT nifti file\n",
    "\t\tlabel_values             : the label value for each of the segments from the json file\n",
    "\t\tlabel_names              : the corresponding label name for each of the segments\n",
    "\t\tsplit_pred_nifti_path    : where to save the individual nii segments needed\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t for pyradiomics\n",
    "\t\tnnunet_shape_features_code_mapping_df : the df where we will obtain the\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tlist of the shape features to\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tcompute\n",
    "\n",
    "\tOutputs:\n",
    "\t\tWrites the features_csv_path_nnunet to disk.\n",
    "\t\"\"\"\n",
    "\n",
    "\t# Get the names of the features from the nnunet_shape_features_code_mapping_df\n",
    "\tshape_features = list(nnunet_shape_features_code_mapping_df['shape_feature'].values)\n",
    "\n",
    "\n",
    "\n",
    "\t# Calculate features for each label and create a dataframe\n",
    "\t# num_labels = len(label_names)#len([f for f in os.listdir(split_pred_nifti_path) if f.endswith('.nii.gz')])\n",
    "\tdf_list = []\n",
    "\tfor idxLabelValue, labelValue in enumerate(label_values):\n",
    "\t\tmask_path = os.path.join(split_pred_nifti_path, label_names[idxLabelValue] + '.nii.gz')\n",
    "\t\t# Run the extractor\n",
    "\t\tprint(f\"ct nifti path : {ct_nifti_path}\")\n",
    "\t\tprint(f\" mask path : {mask_path}\")\n",
    "\t\tprint(f\"labelValue : {labelValue}\")\n",
    "\t\tprint(f\"label_name : {str(label_names[idxLabelValue])}\")\n",
    "\t\t# Instantiate the extractor and modify the settings to keep the 3D shape features\n",
    "\t\textractor = featureextractor.RadiomicsFeatureExtractor(correctMask=True,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t geometryTolerance=float(1e-4),\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t label=int(labelValue))\n",
    "\t\textractor.settings['minimumROIDimensions'] = 2\n",
    "\t\textractor.disableAllFeatures()\n",
    "\t\textractor.enableFeaturesByName(shape=shape_features)\n",
    "\t\tresult = extractor.execute(ct_nifti_path, mask_path) # dictionary\n",
    "\t\t# keep only the features we want\n",
    "\t\t# Get the corresponding label number -- all might not be present\n",
    "\t\t# corresponding_label_value = labelValue#label_values[label_names.index(label_names[n])]\n",
    "\t\tdict_keep = {'ReferencedSegment': int(labelValue),\n",
    "\t\t\t\t\t\t\t\t 'label_name': str(label_names[idxLabelValue])}\n",
    "\t\tkeys_keep = [f for f in result.keys() if 'original_shape' in f]\n",
    "\t\t# Just keep the feature keys we want\n",
    "\t\tdict_keep_new_values = {key_keep: result[key_keep] for key_keep in keys_keep}\n",
    "\t\tdict_keep.update(dict_keep_new_values)\n",
    "\t\tdf1 = pd.DataFrame([dict_keep])\n",
    "\t\t# change values of columns to remove original_shape_\n",
    "\t\tdf1.columns = df1.columns.str.replace('original_shape_', '')\n",
    "\t\t# Append to the ReferencedSegment and label_name df\n",
    "\t\tdf_list.append(df1)\n",
    "\n",
    "\t# concat all label features\n",
    "\tdf = pd.concat(df_list)\n",
    "\n",
    "\treturn df"
   ]
  },
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    "def order_dicom_files_image_position(dcm_directory):\n",
    "\t\"\"\"\n",
    "\tOrders the dicom files according to image position and orientation.\n",
    "\n",
    "\tArguments:\n",
    "\t\tdcm_directory : input directory of dcm files to put in order\n",
    "\n",
    "\tOutputs:\n",
    "\t\tfiles_sorted   : dcm files in sorted order\n",
    "\t\tsop_all_sorted : the SOPInstanceUIDs in sorted order\n",
    "\t\tpos_all_sorted : the image position in sorted order\n",
    "\n",
    "\t\"\"\"\n",
    "\tfiles = [os.path.join(dcm_directory,f) for f in os.listdir(dcm_directory)]\n",
    "\n",
    "\tnum_files = len(files)\n",
    "\n",
    "\tpos_all = []\n",
    "\tsop_all = []\n",
    "\n",
    "\tfor n in range(0,num_files):\n",
    "\t\t# read dcm file\n",
    "\t\tfilename = files[n]\n",
    "\t\tds = dcmread(filename)\n",
    "\n",
    "\t\t# get ImageOrientation (0020, 0037)\n",
    "\t\t# ImageOrientation = ds['0x0020','0x0037'].value\n",
    "\t\tImageOrientation = ds.ImageOrientationPatient\n",
    "\n",
    "\t\t# get ImagePositionPatient (0020, 0032)\n",
    "\t\t# ImagePositionPatient = ds['0x0020','0x0032'].value\n",
    "\t\tImagePositionPatient = ds.ImagePositionPatient\n",
    "\n",
    "\t\t# calculate z value\n",
    "\t\tx_vector = ImageOrientation[0:3]\n",
    "\t\ty_vector = ImageOrientation[3:]\n",
    "\t\tz_vector = np.cross(x_vector,y_vector)\n",
    "\n",
    "\t\t# multiple z_vector by ImagePositionPatient\n",
    "\t\tpos = np.dot(z_vector,ImagePositionPatient)\n",
    "\t\tpos_all.append(pos)\n",
    "\n",
    "\t\t# get the SOPInstanceUID\n",
    "\t\t# sop = ds['0x0008', '0x0018'].value\n",
    "\t\tsop = ds.SOPInstanceUID\n",
    "\t\tsop_all.append(sop)\n",
    "\n",
    "\n",
    "\t#----- order the SOPInstanceUID/files by z value ----#\n",
    "\n",
    "\tsorted_ind = np.argsort(pos_all)\n",
    "\tpos_all_sorted = np.array(pos_all)[sorted_ind.astype(int)]\n",
    "\tsop_all_sorted = np.array(sop_all)[sorted_ind.astype(int)]\n",
    "\tfiles_sorted = np.array(files)[sorted_ind.astype(int)]\n",
    "\n",
    "\treturn files_sorted, sop_all_sorted, pos_all_sorted"
   ]
  },
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   "source": [
    "def create_structured_report_metajson_for_shape_features(SeriesInstanceUID,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t SOPInstanceUID_seg,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t seg_file,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t dcm_directory,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t segments_code_mapping_df,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t shape_features_code_mapping_df,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t df_features,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t SegmentAlgorithmName,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t SeriesDescriptionPrefix\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t ):\n",
    "\n",
    "\t\"\"\"Function that creates the metajson necessary for the creation of a\n",
    "\tstructured report from a pandas dataframe of label names and features for\n",
    "\teach.\n",
    "\n",
    "\tInputs:\n",
    "\t\tSeriesInstanceUID               : SeriesInstanceUID of the corresponding CT\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfile\n",
    "\t\tSOPInstanceUID_seg              : SOPInstanceUID of the corresponding SEG file\n",
    "\t\tseg_file                        : filename of SEG DCM file\n",
    "\t\tdcm_directory                   : ct directory that will be sorted in\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tterms of axial ordering according to the\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tImagePositionPatient and ImageOrientation\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfields\n",
    "\t\tsegments_code_mapping_df        : dataframe that holds the names of the\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsegments and the associated code values etc.\n",
    "\t\tshape_features_code_mapping_df  : dataframe that holds the names of the\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfeatures and the associated code values etc.\n",
    "\t\tdf_features                     : a pandas dataframe holding the segments and a\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset of 3D shape features for each\n",
    "\t\tSegmentAlgorithmName            : the name of the algorithm used to create the\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsegmentations - e.g. '3d_fullres_tta_nnUnet'\n",
    "\n",
    "\tOutputs:\n",
    "\t\tReturns the metajson for the structured report that will then be used by\n",
    "\t\tdcmqi tid1500writer to create a structured report\n",
    "\t\"\"\"\n",
    "\n",
    "\t# --- Get the version number for the pyradiomics package --- #\n",
    "\n",
    "\tpyradiomics_version_number = str(radiomics.__version__)\n",
    "\n",
    "\t# --- Sort the dcm files first according to --- #\n",
    "\t# --- ImagePositionPatient and ImageOrientation --- #\n",
    "\n",
    "\tfiles_sorted, sop_all_sorted, pos_all_sorted = order_dicom_files_image_position(dcm_directory)\n",
    "\tfiles_sorted = [os.path.basename(f) for f in files_sorted]\n",
    "\n",
    "\t# --- Create the header for the json --- #\n",
    "\n",
    "\tinputMetadata = {}\n",
    "\tinputMetadata[\"@schema\"]= \"https://raw.githubusercontent.com/qiicr/dcmqi/master/doc/schemas/sr-tid1500-schema.json#\"\n",
    "\t# inputMetadata[\"SeriesDescription\"] = \"Measurements\"\n",
    "\tinputMetadata[\"SeriesDescription\"] = SeriesDescriptionPrefix + '_' + \"Measurements\"\n",
    "\tinputMetadata[\"SeriesNumber\"] = \"1001\"\n",
    "\tinputMetadata[\"InstanceNumber\"] = \"1\"\n",
    "\n",
    "\tinputMetadata[\"compositeContext\"] = [abspath(seg_file)] # not full path\n",
    "\n",
    "\tinputMetadata[\"imageLibrary\"] = files_sorted # not full path\n",
    "\n",
    "\t# inputMetadata[\"observerContext\"] = {\n",
    "\t#                                     \"ObserverType\": \"PERSON\",\n",
    "\t#                                     \"PersonObserverName\": \"Reader1\"\n",
    "\t#                                   }\n",
    "\t# inputMetadata[\"observerContext\"] = {\n",
    "\t#                     \"ObserverType\": \"DEVICE\",\n",
    "\t#                     \"DeviceObserverName\": \"pyradiomics\",\n",
    "\t#                     \"DeviceObserverModelName\": \"v3.0.1\"\n",
    "\t#                   }\n",
    "\tinputMetadata[\"observerContext\"] = {\n",
    "\t\t\t\t\t\t\t\t\t\t\t\"ObserverType\": \"DEVICE\",\n",
    "\t\t\t\t\t\t\t\t\t\t\t\"DeviceObserverName\": \"pyradiomics\",\n",
    "\t\t\t\t\t\t\t\t\t\t\t\"DeviceObserverModelName\": pyradiomics_version_number\n",
    "\t\t\t\t\t\t\t\t\t\t}\n",
    "\n",
    "\tinputMetadata[\"VerificationFlag\"]  = \"UNVERIFIED\"\n",
    "\tinputMetadata[\"CompletionFlag\"] =  \"COMPLETE\"\n",
    "\tinputMetadata[\"activitySession\"] = \"1\"\n",
    "\tinputMetadata[\"timePoint\"] = \"1\"\n",
    "\n",
    "\t# ------------------------------------------------------------------------- #\n",
    "\t# --- Create the measurement_dict for each segment - holds all features --- #\n",
    "\n",
    "\tmeasurement = []\n",
    "\n",
    "\t# --- Now create the dict for all features and all segments --- #\n",
    "\n",
    "\t# --- Loop over the number of segments --- #\n",
    "\n",
    "\t# number of rows in the df_features\n",
    "\tnum_segments = df_features.shape[0]\n",
    "\n",
    "\t# Array of dictionaries - one dictionary for each segment\n",
    "\tmeasurement_across_segments_combined = []\n",
    "\n",
    "\tfor segment_id in range(0,num_segments):\n",
    "\n",
    "\t\tReferencedSegment = int(df_features['ReferencedSegment'].values[segment_id])\n",
    "\t\tFindingSite = df_features['label_name'].values[segment_id]\n",
    "\n",
    "\t\tprint('segment_id: ' + str(segment_id))\n",
    "\t\tprint('ReferencedSegment: ' + str(ReferencedSegment))\n",
    "\t\tprint('FindingSite: ' + str(FindingSite))\n",
    "\n",
    "\t\t# --- Create the dict for the Measurements group --- #\n",
    "\t\tTrackingIdentifier = \"Measurements group \" + str(ReferencedSegment)\n",
    "\n",
    "\t\tsegment_row = segments_code_mapping_df[segments_code_mapping_df[\"segment\"] == FindingSite]\n",
    "\t\t# print(segment_row)\n",
    "\n",
    "\t\tmy_dict = {\n",
    "\t\t\t\"TrackingIdentifier\": str(TrackingIdentifier),\n",
    "\t\t\t\"ReferencedSegment\": int(ReferencedSegment),\n",
    "\t\t\t\"SourceSeriesForImageSegmentation\": str(SeriesInstanceUID),\n",
    "\t\t\t\"segmentationSOPInstanceUID\": str(SOPInstanceUID_seg),\n",
    "\t\t\t\"measurementAlgorithmIdentification\": {\n",
    "\t\t\t\t\t\t\t\t\"AlgorithmName\": \"pyradiomics\",\n",
    "\t\t\t\t\t\t\t\t\"AlgorithmVersion\": str(pyradiomics_version_number)\n",
    "\t\t\t\t\t\t},\n",
    "\t\t\t\"Finding\": {\n",
    "\t\t\t\t\"CodeValue\": \"113343008\",\n",
    "\t\t\t\t\"CodingSchemeDesignator\": \"SCT\",\n",
    "\t\t\t\t\"CodeMeaning\": \"Organ\"\n",
    "\t\t\t},\n",
    "\t\t\t\"FindingSite\": {\n",
    "\t\t\t\t\"CodeValue\": str(segment_row[\"FindingSite_CodeValue\"].values[0]),\n",
    "\t\t\t\t\"CodingSchemeDesignator\": str(segment_row[\"FindingSite_CodingSchemeDesignator\"].values[0]),\n",
    "\t\t\t\t\"CodeMeaning\": str(segment_row[\"FindingSite_CodeMeaning\"].values[0])\n",
    "\t\t\t}\n",
    "\t\t}\n",
    "\n",
    "\t\tmeasurement = []\n",
    "\t\t# number of features - number of columns in df_features - 2 (label_name and ReferencedSegment)\n",
    "\t\tnum_values = len(df_features.columns)-2\n",
    "\n",
    "\t\tfeature_list = df_features.columns[2:] # remove first two\n",
    "\n",
    "\n",
    "\t\t# For each measurement per region segment\n",
    "\t\tfor n in range(0,num_values):\n",
    "\t\t\tmeasurement_dict = {}\n",
    "\t\t\trow = df_features.loc[df_features['label_name'] == FindingSite]\n",
    "\t\t\tfeature_row = shape_features_code_mapping_df.loc[shape_features_code_mapping_df[\"shape_feature\"] == feature_list[n]]\n",
    "\t\t\tvalue = str(np.round(row[feature_list[n]].values[0],3))\n",
    "\t\t\tmeasurement_dict[\"value\"] = value\n",
    "\t\t\tmeasurement_dict[\"quantity\"] = {}\n",
    "\t\t\tmeasurement_dict[\"quantity\"][\"CodeValue\"] = str(feature_row[\"quantity_CodeValue\"].values[0])\n",
    "\t\t\tmeasurement_dict[\"quantity\"][\"CodingSchemeDesignator\"] = str(feature_row[\"quantity_CodingSchemeDesignator\"].values[0])\n",
    "\t\t\tmeasurement_dict[\"quantity\"][\"CodeMeaning\"] = str(feature_row[\"quantity_CodeMeaning\"].values[0])\n",
    "\t\t\tmeasurement_dict[\"units\"] = {}\n",
    "\t\t\tmeasurement_dict[\"units\"][\"CodeValue\"] = str(feature_row[\"units_CodeValue\"].values[0])\n",
    "\t\t\tmeasurement_dict[\"units\"][\"CodingSchemeDesignator\"] = str(feature_row[\"units_CodingSchemeDesignator\"].values[0])\n",
    "\t\t\tmeasurement_dict[\"units\"][\"CodeMeaning\"] = str(feature_row[\"units_CodeMeaning\"].values[0])\n",
    "\t\t\t# measurement_dict[\"measurementAlgorithmIdentification\"] = {}\n",
    "\t\t\t# measurement_dict[\"measurementAlgorithmIdentification\"][\"AlgorithmName\"] = \"pyradiomics\"\n",
    "\t\t\t# measurement_dict[\"measurementAlgorithmIdentification\"][\"AlgorithmVersion\"] = str(pyradiomics_version_number)\n",
    "\t\t\tmeasurement.append(measurement_dict)\n",
    "\n",
    "\t\tmeasurement_combined_dict = {}\n",
    "\t\tmeasurement_combined_dict['measurementItems'] = measurement # measurement is an array of dictionaries\n",
    "\n",
    "\t\toutput_dict_one_segment = {**my_dict, **measurement_combined_dict}\n",
    "\n",
    "\t\t# append to array for all segments\n",
    "\n",
    "\t\tmeasurement_across_segments_combined.append(output_dict_one_segment)\n",
    "\n",
    "\t# --- Add the measurement data --- #\n",
    "\n",
    "\tinputMetadata[\"Measurements\"] = {}\n",
    "\tinputMetadata[\"Measurements\"] = measurement_across_segments_combined\n",
    "\n",
    "\treturn inputMetadata"
   ]
  },
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     "start_time": "2024-09-10T04:38:25.629379",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def save_structured_report_for_shape_features_idc_seg(SeriesInstanceUID,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tlabel_values,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tlabel_names,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tSOPInstanceUID_seg,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tpred_dicomseg_path,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tdicomseg_json_path,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tdcm_directory,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsplit_pred_nii_path,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tct_nifti_path,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsegments_code_mapping_df,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tshape_features_code_mapping_df,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsr_json_path,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsr_path,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tSegmentAlgorithmName,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tSeriesDescriptionPrefix\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t):\n",
    "\n",
    "\t\"\"\" This function creates the SR necessary for the nnUNet shape features\n",
    "\n",
    "\tInputs:\n",
    "\tSeriesInstanceUID               : SeriesInstanceUID of the corresponding CT\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfile\n",
    "\tSOPInstanceUID_seg              : SOPInstanceUID of the corresponding SEG file\n",
    "\tpred_dicomseg_path              : filename of DICOM SEG file\n",
    "\tdicomseg_json_path              : json file for DICOM SEG file\n",
    "\tdcm_directory                   : list of ct files that will be sorted in\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tterms of axial ordering according to the\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tImagePositionPatient and ImageOrientation\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfields\n",
    "\tnnunet_base_path                : path to hold the split nifti files\n",
    "\tct_nifti_path                   : filename for CT nifti file\n",
    "\tsegments_code_mapping_df        : dataframe that holds the names of the\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsegments and the associated code values etc.\n",
    "\tshape_features_code_mapping_df  : dataframe that holds the names of the\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfeatures and the associated code values etc.\n",
    "\tsr_json_path                    : the path that the metajson for the SR for\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tthe 3D shape features will be saved\n",
    "\tsr_path                         : the path that the SR for the 3D shape\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfeatures will be saved\n",
    "\tSegmentAlgorithmName            : the name of the algorithm used to create the\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsegmentations - e.g. '3d_fullres_tta_nnUnet'\n",
    "\n",
    "\tOutputs:\n",
    "\t\tReturns the metajson for the structured report that will then be used by\n",
    "\t\tdcmqi tid1500writer to create a structured report\n",
    "\n",
    "\t\"\"\"\n",
    "\n",
    "\t# --- get label values and names from metajson file --- #\n",
    "\tlabel_values, label_names = label_values, label_names#get_label_and_names_from_metadata_json(dicomseg_json_path)\n",
    "\n",
    "\tdf_features = compute_pyradiomics_3D_features(ct_nifti_path,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tlabel_values,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tlabel_names,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsplit_pred_nii_path,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tnnunet_shape_features_code_mapping_df)\n",
    "\tprint ('created df_features')\n",
    "\n",
    "\t# --- upload csv file to bucket --- #\n",
    "\t# !$s5cmd_path --endpoint-url https://storage.googleapis.com cp $pred_features_csv_path $gs_uri_features_csv_file\n",
    "\n",
    "\t# remove nii files after saving out pyradiomics results\n",
    "\t!rm $split_pred_nii_path/*\n",
    "\t# remove csv\n",
    "\t# !rm $pred_features_csv_path\n",
    "\n",
    "\t# --- Create the final metadata for the SR --- #\n",
    "\tinputMetadata = create_structured_report_metajson_for_shape_features(SeriesInstanceUID,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t SOPInstanceUID_seg,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t pred_dicomseg_path,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t dcm_directory,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t segments_code_mapping_df,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t nnunet_shape_features_code_mapping_df,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t df_features,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t SegmentAlgorithmName,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t SeriesDescriptionPrefix)\n",
    "\n",
    "\tprint ('created SR json for shape features')\n",
    "\n",
    "\t# --- Write out json --- #\n",
    "\n",
    "\twith open(sr_json_path, 'w') as f:\n",
    "\t\tjson.dump(inputMetadata, f, indent=2)\n",
    "\tprint ('wrote out json for shape features')\n",
    "\n",
    "\t# --- Save the SR for nnUNet shape features --- #\n",
    "\tinputImageLibraryDirectory = dcm_directory\n",
    "\toutputDICOM = sr_path\n",
    "\t# the name of the folder where the seg files are located\n",
    "\tinputCompositeContextDirectory = os.path.basename(pred_dicomseg_path) # might need to check this\n",
    "\tinputMetadata_json = sr_json_path\n",
    "\n",
    "\tprint ('inputImageLibraryDirectory: ' + str(inputImageLibraryDirectory))\n",
    "\tprint ('outputDICOM: ' + str(outputDICOM))\n",
    "\tprint ('inputCompositeContextDirectory: ' + str(inputCompositeContextDirectory))\n",
    "\tprint ('inputMetadata_json: ' + str(inputMetadata_json))\n",
    "\t!tid1500writer --inputImageLibraryDirectory $inputImageLibraryDirectory \\\n",
    "\t\t\t\t\t\t\t\t--outputDICOM $outputDICOM  \\\n",
    "\t\t\t\t\t\t\t\t--inputCompositeContextDirectory $inputCompositeContextDirectory \\\n",
    "\t\t\t\t\t\t\t\t--inputMetadata $inputMetadata_json\n",
    "\tprint ('wrote out SR for shape features')\n",
    "\n",
    "\treturn"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9a2b21cb",
   "metadata": {
    "id": "9a2b21cb",
    "papermill": {
     "duration": 0.007977,
     "end_time": "2024-09-10T04:38:25.671861",
     "exception": false,
     "start_time": "2024-09-10T04:38:25.663884",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "5e7bfbf8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-10T04:38:25.723542Z",
     "iopub.status.busy": "2024-09-10T04:38:25.723167Z",
     "iopub.status.idle": "2024-09-10T04:38:26.030753Z",
     "shell.execute_reply": "2024-09-10T04:38:26.029235Z"
    },
    "id": "5e7bfbf8",
    "papermill": {
     "duration": 0.32011,
     "end_time": "2024-09-10T04:38:26.033113",
     "exception": false,
     "start_time": "2024-09-10T04:38:25.713003",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Packages for the structured report\n",
    "import radiomics\n",
    "from radiomics import featureextractor\n",
    "\n",
    "import highdicom\n",
    "\n",
    "from pathlib import Path\n",
    "\n",
    "import highdicom as hd\n",
    "\n",
    "from pydicom.uid import generate_uid\n",
    "from pydicom.filereader import dcmread\n",
    "from pydicom.sr.codedict import codes\n",
    "\n",
    "from highdicom.sr.content import (\n",
    "\tFindingSite,\n",
    "\tImageRegion,\n",
    "\tImageRegion3D,\n",
    "\tSourceImageForRegion,\n",
    "\tSourceImageForMeasurement,\n",
    "\tSourceImageForMeasurementGroup\n",
    ")\n",
    "from highdicom.sr.enum import GraphicTypeValues3D\n",
    "from highdicom.sr.enum import GraphicTypeValues\n",
    "from highdicom.sr.sop import Comprehensive3DSR, ComprehensiveSR\n",
    "from highdicom.sr.templates import (\n",
    "\tDeviceObserverIdentifyingAttributes,\n",
    "\tMeasurement,\n",
    "\tMeasurementProperties,\n",
    "\tMeasurementReport,\n",
    "\tMeasurementsAndQualitativeEvaluations,\n",
    "\tObservationContext,\n",
    "\tObserverContext,\n",
    "\tPersonObserverIdentifyingAttributes,\n",
    "\tPlanarROIMeasurementsAndQualitativeEvaluations,\n",
    "\tRelationshipTypeValues,\n",
    "\tTrackingIdentifier,\n",
    "\tQualitativeEvaluation,\n",
    "\tImageLibrary,\n",
    "\tImageLibraryEntryDescriptors\n",
    ")\n",
    "from highdicom.sr.value_types import (\n",
    "\tCodedConcept,\n",
    "\tCodeContentItem,\n",
    ")\n",
    "\n",
    "import logging\n",
    "logger = logging.getLogger(\"highdicom.sr.sop\")\n",
    "logger.setLevel(logging.INFO)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "257aa7d2",
   "metadata": {
    "id": "257aa7d2",
    "papermill": {
     "duration": 0.008944,
     "end_time": "2024-09-10T04:38:26.052990",
     "exception": false,
     "start_time": "2024-09-10T04:38:26.044046",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Input setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "e811f1b6",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "execution": {
     "iopub.execute_input": "2024-09-10T04:38:26.072611Z",
     "iopub.status.busy": "2024-09-10T04:38:26.071481Z",
     "iopub.status.idle": "2024-09-10T04:38:26.263047Z",
     "shell.execute_reply": "2024-09-10T04:38:26.261689Z"
    },
    "id": "e811f1b6",
    "outputId": "1f52ecc9-6e55-4648-a8d8-cc9b53215676",
    "papermill": {
     "duration": 0.203891,
     "end_time": "2024-09-10T04:38:26.265421",
     "exception": false,
     "start_time": "2024-09-10T04:38:26.061530",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "combination_archive/\n",
      "combination_archive/seg_prostate_gen/\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088/\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088/meta.json\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088/3.nii.gz\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088/2.nii.gz\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088/1.nii.gz\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936/\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936/meta.json\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936/3.nii.gz\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936/2.nii.gz\n",
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      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.165941479363091869002475812419/\n",
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      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223/\n",
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      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.621341845114918594203879249474/\n",
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      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.621341845114918594203879249474/1.nii.gz\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017/\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017/meta.json\n",
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      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017/2.nii.gz\n",
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      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480/\n",
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      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480/3.nii.gz\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480/2.nii.gz\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480/1.nii.gz\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127/\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127/meta.json\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127/3.nii.gz\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127/2.nii.gz\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127/1.nii.gz\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931/\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931/meta.json\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931/4.nii.gz\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931/3.nii.gz\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931/2.nii.gz\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931/1.nii.gz\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147/\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147/meta.json\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147/4.nii.gz\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147/3.nii.gz\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147/2.nii.gz\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147/1.nii.gz\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857/\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857/meta.json\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857/4.nii.gz\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857/3.nii.gz\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857/2.nii.gz\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857/1.nii.gz\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172/\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172/meta.json\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172/3.nii.gz\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172/2.nii.gz\n",
      "combination_archive/seg_prostate_gen/output_nii_combined/1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172/1.nii.gz\n",
      "combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/\n",
      "combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088/\n",
      "combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088/2de72a55-26d8-4d08-9bcc-38f4ebbde413.dcm\n",
      "combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936/\n",
      "combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936/d148919e-2c32-4501-9315-3f55c2ba31a5.dcm\n",
      "combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.165941479363091869002475812419/\n",
      "combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.165941479363091869002475812419/5f5f0840-3dee-4fb4-bab7-419cb2ecb8ad.dcm\n",
      "combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223/\n",
      "combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223/bf1e495e-5b73-4efa-8a63-d80b8426034a.dcm\n",
      "combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.621341845114918594203879249474/\n",
      "combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.621341845114918594203879249474/32a4c94b-1057-4535-be91-4f4e54f4b6ad.dcm\n",
      "combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017/\n",
      "combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017/38636f83-f883-40be-8036-19b9bdb94911.dcm\n",
      "combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480/\n",
      "combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480/6689344c-8b81-4282-aa49-af3a29cc9527.dcm\n",
      "combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127/\n",
      "combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127/6d3d17e8-e0cc-40d5-8c9d-6fd4357599dc.dcm\n",
      "combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931/\n",
      "combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931/e36e0862-575e-48f8-8fc1-104fbbf44d01.dcm\n",
      "combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147/\n",
      "combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147/56866f5f-1d17-48ed-8ed3-5218adc662b5.dcm\n",
      "combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857/\n",
      "combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857/8ae1177f-8173-47d8-a25f-0a182cdd4162.dcm\n",
      "combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172/\n",
      "combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172/7540b951-70e5-449b-8747-79397bfede9a.dcm\n",
      "combination_archive/idc_seg_dicom_combination-output.ipynb\n"
     ]
    }
   ],
   "source": [
    "!lz4 -dc < $SEG_OUTPUT | tar xvf - -C $SEG_OUTPUT_UNZIP"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "147b399e",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "execution": {
     "iopub.execute_input": "2024-09-10T04:38:26.352517Z",
     "iopub.status.busy": "2024-09-10T04:38:26.352147Z",
     "iopub.status.idle": "2024-09-10T04:38:26.671425Z",
     "shell.execute_reply": "2024-09-10T04:38:26.670382Z"
    },
    "id": "147b399e",
    "outputId": "12e5de09-db49-4c64-9946-4f3cde254240",
    "papermill": {
     "duration": 0.331665,
     "end_time": "2024-09-10T04:38:26.673746",
     "exception": false,
     "start_time": "2024-09-10T04:38:26.342081",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--2024-10-10 20:12:35--  https://raw.githubusercontent.com/ImagingDataCommons/ai_medima_misc/main/nnunet/data/nnunet_shape_features_code_mapping.csv\n",
      "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.109.133, 185.199.111.133, 185.199.108.133, ...\n",
      "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.109.133|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 1053 (1.0K) [text/plain]\n",
      "Saving to: ‘nnunet_shape_features_code_mapping.csv’\n",
      "\n",
      "nnunet_shape_featur 100%[===================>]   1.03K  --.-KB/s    in 0s      \n",
      "\n",
      "Last-modified header missing -- time-stamps turned off.\n",
      "2024-10-10 20:12:35 (57.7 MB/s) - ‘nnunet_shape_features_code_mapping.csv’ saved [1053/1053]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#nnunet code mapping\n",
    "import pandas as pd\n",
    "#radiomics df\n",
    "!wget -N https://raw.githubusercontent.com/ImagingDataCommons/ai_medima_misc/main/nnunet/data/nnunet_shape_features_code_mapping.csv\n",
    "nnunet_shape_features_code_mapping_df = pd.read_csv(\"nnunet_shape_features_code_mapping.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8462b617",
   "metadata": {
    "id": "8462b617",
    "papermill": {
     "duration": 0.009138,
     "end_time": "2024-09-10T04:38:26.691938",
     "exception": false,
     "start_time": "2024-09-10T04:38:26.682800",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Radiomics computation\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "3bd31df1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-10T04:38:26.711750Z",
     "iopub.status.busy": "2024-09-10T04:38:26.711334Z",
     "iopub.status.idle": "2024-09-10T04:38:26.719695Z",
     "shell.execute_reply": "2024-09-10T04:38:26.718671Z"
    },
    "id": "3bd31df1",
    "papermill": {
     "duration": 0.021092,
     "end_time": "2024-09-10T04:38:26.721863",
     "exception": false,
     "start_time": "2024-09-10T04:38:26.700771",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "seg_dicom_objects = glob.glob(os.path.join(SEG_OUTPUT_UNZIP, \"**\",\n",
    "\t\t\t\t\t\t\t\t\t\t \"*.dcm\"), recursive=True)\n",
    "assert os.path.exists(seg_dicom_objects[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5312978e",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "execution": {
     "iopub.execute_input": "2024-09-10T04:38:26.742200Z",
     "iopub.status.busy": "2024-09-10T04:38:26.741840Z",
     "iopub.status.idle": "2024-09-10T04:39:35.855435Z",
     "shell.execute_reply": "2024-09-10T04:39:35.854387Z"
    },
    "id": "5312978e",
    "outputId": "65c48364-1dde-4a8e-a47d-581869660ad4",
    "papermill": {
     "duration": 69.126673,
     "end_time": "2024-09-10T04:39:35.857506",
     "exception": false,
     "start_time": "2024-09-10T04:38:26.730833",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "serieUID image referenced : 1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088\n",
      "dcmqi repository URL: https://github.com/QIICR/dcmqi revision: d88b025 tag: v1.3.4\n",
      "Loading DICOM SEG file TEST/seg_unzip/combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088/2de72a55-26d8-4d08-9bcc-38f4ebbde413.dcm\n",
      "Row direction: 0.999908 0.0135279 -0.000333927\n",
      "Col direction: 0.0133358 -0.989293 -0.14533\n",
      "Z direction: -0.00229637 0.145313 -0.989383\n",
      "Total frames: 32\n",
      "Total frames with unique IPP: 15\n",
      "Total overlapping frames: 13\n",
      "Origin: [-47.2438, 90.5125, 62.0734]\n",
      "Slice extent: 49\n",
      "Slice spacing: 3.5\n",
      "Will not merge segments: Splitting segments into 3 groups\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088/1.nii.gz ... done\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088/2.nii.gz ... done\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088/3.nii.gz ... done\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Downloading data: 100%|█████████▉| 13.7M/13.7M [00:01<00:00, 13.6MB/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Chris Rorden's dcm2niiX version v1.0.20220505  GCC11.4.0 x86-64 (64-bit Linux)\n",
      "Found 26 DICOM file(s)\n",
      "Convert 26 DICOM as TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088/PCAMPMRI-00008_1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088 (512x512x26x1)\n",
      "Conversion required 0.852539 seconds (0.852327 for core code).\n",
      "\n",
      "Running 'plastimatch convert' with the specified arguments:\n",
      "  --input TEST/idc_image_data/dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088/qin_prostate_repeatability/PCAMPMRI-00008/1.3.6.1.4.1.14519.5.2.1.3671.4754.266963586071007736606548226859/MR_1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088\n",
      "  --output-img TEST/idc_image_data/nrrd/1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088/1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088.nrrd\n",
      "... Done.\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088/2.nii.gz\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088/1.nii.gz\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088/3.nii.gz\n",
      "SegmentAlgorithmName : MANUAL\n",
      "label_values: [3, 1]\n",
      "label_names: ['Prostate', 'Peripheral zone of the prostate']\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:No valid config parameter, using defaults: {'minimumROIDimensions': 2, 'minimumROISize': None, 'normalize': False, 'normalizeScale': 1, 'removeOutliers': None, 'resampledPixelSpacing': None, 'interpolator': 'sitkBSpline', 'preCrop': False, 'padDistance': 5, 'distances': [1], 'force2D': False, 'force2Ddimension': 0, 'resegmentRange': None, 'label': 1, 'additionalInfo': True}\n",
      "INFO:radiomics.featureextractor:Enabled image types: {'Original': {}}\n",
      "INFO:radiomics.featureextractor:Enabled features: {'firstorder': [], 'glcm': [], 'gldm': [], 'glrlm': [], 'glszm': [], 'ngtdm': [], 'shape': []}\n",
      "INFO:radiomics.featureextractor:Applying custom setting overrides: {'correctMask': True, 'geometryTolerance': 0.0001, 'label': 3}\n",
      "INFO:radiomics.featureextractor:Calculating features with label: 3\n",
      "INFO:radiomics.featureextractor:Loading image and mask\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ct nifti path : /content/TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088/PCAMPMRI-00008_1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088.nii.gz\n",
      " mask path : /content/TEST/seg_objects/nii_resampled_renamed/1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088/Prostate.nii.gz\n",
      "labelValue : 3\n",
      "label_name : Prostate\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:Computing shape\n",
      "Feature Compactness1 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness1 is deprecated, use with caution!\n",
      "Feature Compactness2 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness2 is deprecated, use with caution!\n",
      "Feature SphericalDisproportion is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature SphericalDisproportion is deprecated, use with caution!\n",
      "INFO:radiomics.featureextractor:Adding image type \"Original\" with custom settings: {}\n",
      "INFO:radiomics.featureextractor:Calculating features for original image\n",
      "INFO:radiomics.featureextractor:No valid config parameter, using defaults: {'minimumROIDimensions': 2, 'minimumROISize': None, 'normalize': False, 'normalizeScale': 1, 'removeOutliers': None, 'resampledPixelSpacing': None, 'interpolator': 'sitkBSpline', 'preCrop': False, 'padDistance': 5, 'distances': [1], 'force2D': False, 'force2Ddimension': 0, 'resegmentRange': None, 'label': 1, 'additionalInfo': True}\n",
      "INFO:radiomics.featureextractor:Enabled image types: {'Original': {}}\n",
      "INFO:radiomics.featureextractor:Enabled features: {'firstorder': [], 'glcm': [], 'gldm': [], 'glrlm': [], 'glszm': [], 'ngtdm': [], 'shape': []}\n",
      "INFO:radiomics.featureextractor:Applying custom setting overrides: {'correctMask': True, 'geometryTolerance': 0.0001, 'label': 1}\n",
      "INFO:radiomics.featureextractor:Calculating features with label: 1\n",
      "INFO:radiomics.featureextractor:Loading image and mask\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ct nifti path : /content/TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088/PCAMPMRI-00008_1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088.nii.gz\n",
      " mask path : /content/TEST/seg_objects/nii_resampled_renamed/1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088/Peripheral zone of the prostate.nii.gz\n",
      "labelValue : 1\n",
      "label_name : Peripheral zone of the prostate\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:Computing shape\n",
      "Feature Compactness1 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness1 is deprecated, use with caution!\n",
      "Feature Compactness2 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness2 is deprecated, use with caution!\n",
      "Feature SphericalDisproportion is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature SphericalDisproportion is deprecated, use with caution!\n",
      "INFO:radiomics.featureextractor:Adding image type \"Original\" with custom settings: {}\n",
      "INFO:radiomics.featureextractor:Calculating features for original image\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "created df_features\n",
      "segment_id: 0\n",
      "ReferencedSegment: 3\n",
      "FindingSite: Prostate\n",
      "segment_id: 1\n",
      "ReferencedSegment: 1\n",
      "FindingSite: Peripheral zone of the prostate\n",
      "created SR json for shape features\n",
      "wrote out json for shape features\n",
      "inputImageLibraryDirectory: /content/TEST/idc_image_data/dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088/qin_prostate_repeatability/PCAMPMRI-00008/1.3.6.1.4.1.14519.5.2.1.3671.4754.266963586071007736606548226859/MR_1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088\n",
      "outputDICOM: /content/TEST/seg_objects/dicom_sr/1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088/1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088_SR.dcm\n",
      "inputCompositeContextDirectory: 2de72a55-26d8-4d08-9bcc-38f4ebbde413.dcm\n",
      "inputMetadata_json: /content/TEST/seg_objects/dicom_sr_json/1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088/1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088_SR.json\n",
      "dcmqi repository URL: https://github.com/QIICR/dcmqi revision: d88b025 tag: v1.3.4\n",
      "Total measurement groups: 2\n",
      "Adding to compositeContext: /content/TEST/seg_unzip/combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.331664318047739623745747449088/2de72a55-26d8-4d08-9bcc-38f4ebbde413.dcm\n",
      "Composite Context has been initialized\n",
      "SR saved!\n",
      "wrote out SR for shape features\n",
      "\n",
      "\n",
      "serieUID image referenced : 1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931\n",
      "dcmqi repository URL: https://github.com/QIICR/dcmqi revision: d88b025 tag: v1.3.4\n",
      "Loading DICOM SEG file TEST/seg_unzip/combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931/e36e0862-575e-48f8-8fc1-104fbbf44d01.dcm\n",
      "Row direction: 0.999997 0.00153529 -0.00195045\n",
      "Col direction: 0.00130966 -0.993838 -0.110837\n",
      "Z direction: -0.0021086 0.110834 -0.993837\n",
      "Total frames: 29\n",
      "Total frames with unique IPP: 15\n",
      "Total overlapping frames: 11\n",
      "Origin: [-44.6381, 81.4048, -27.4447]\n",
      "Slice extent: 49\n",
      "Slice spacing: 3.5\n",
      "Will not merge segments: Splitting segments into 4 groups\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931/1.nii.gz ... done\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931/2.nii.gz ... done\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931/3.nii.gz ... done\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931/4.nii.gz ... done\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Downloading data: 100%|██████████| 14.8M/14.8M [00:01<00:00, 14.7MB/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Chris Rorden's dcm2niiX version v1.0.20220505  GCC11.4.0 x86-64 (64-bit Linux)\n",
      "Found 28 DICOM file(s)\n",
      "Convert 28 DICOM as TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931/PCAMPMRI-00009_1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931 (512x512x28x1)\n",
      "Conversion required 0.907367 seconds (0.906991 for core code).\n",
      "\n",
      "Running 'plastimatch convert' with the specified arguments:\n",
      "  --input TEST/idc_image_data/dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931/qin_prostate_repeatability/PCAMPMRI-00009/1.3.6.1.4.1.14519.5.2.1.3671.4754.864607788085827202303582199118/MR_1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931\n",
      "  --output-img TEST/idc_image_data/nrrd/1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931/1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931.nrrd\n",
      "... Done.\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931/2.nii.gz\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931/1.nii.gz\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931/4.nii.gz\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931/3.nii.gz\n",
      "SegmentAlgorithmName : MANUAL\n",
      "label_values: [4, 2]\n",
      "label_names: ['Prostate', 'Peripheral zone of the prostate']\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:No valid config parameter, using defaults: {'minimumROIDimensions': 2, 'minimumROISize': None, 'normalize': False, 'normalizeScale': 1, 'removeOutliers': None, 'resampledPixelSpacing': None, 'interpolator': 'sitkBSpline', 'preCrop': False, 'padDistance': 5, 'distances': [1], 'force2D': False, 'force2Ddimension': 0, 'resegmentRange': None, 'label': 1, 'additionalInfo': True}\n",
      "INFO:radiomics.featureextractor:Enabled image types: {'Original': {}}\n",
      "INFO:radiomics.featureextractor:Enabled features: {'firstorder': [], 'glcm': [], 'gldm': [], 'glrlm': [], 'glszm': [], 'ngtdm': [], 'shape': []}\n",
      "INFO:radiomics.featureextractor:Applying custom setting overrides: {'correctMask': True, 'geometryTolerance': 0.0001, 'label': 4}\n",
      "INFO:radiomics.featureextractor:Calculating features with label: 4\n",
      "INFO:radiomics.featureextractor:Loading image and mask\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ct nifti path : /content/TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931/PCAMPMRI-00009_1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931.nii.gz\n",
      " mask path : /content/TEST/seg_objects/nii_resampled_renamed/1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931/Prostate.nii.gz\n",
      "labelValue : 4\n",
      "label_name : Prostate\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:Computing shape\n",
      "Feature Compactness1 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness1 is deprecated, use with caution!\n",
      "Feature Compactness2 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness2 is deprecated, use with caution!\n",
      "Feature SphericalDisproportion is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature SphericalDisproportion is deprecated, use with caution!\n",
      "INFO:radiomics.featureextractor:Adding image type \"Original\" with custom settings: {}\n",
      "INFO:radiomics.featureextractor:Calculating features for original image\n",
      "INFO:radiomics.featureextractor:No valid config parameter, using defaults: {'minimumROIDimensions': 2, 'minimumROISize': None, 'normalize': False, 'normalizeScale': 1, 'removeOutliers': None, 'resampledPixelSpacing': None, 'interpolator': 'sitkBSpline', 'preCrop': False, 'padDistance': 5, 'distances': [1], 'force2D': False, 'force2Ddimension': 0, 'resegmentRange': None, 'label': 1, 'additionalInfo': True}\n",
      "INFO:radiomics.featureextractor:Enabled image types: {'Original': {}}\n",
      "INFO:radiomics.featureextractor:Enabled features: {'firstorder': [], 'glcm': [], 'gldm': [], 'glrlm': [], 'glszm': [], 'ngtdm': [], 'shape': []}\n",
      "INFO:radiomics.featureextractor:Applying custom setting overrides: {'correctMask': True, 'geometryTolerance': 0.0001, 'label': 2}\n",
      "INFO:radiomics.featureextractor:Calculating features with label: 2\n",
      "INFO:radiomics.featureextractor:Loading image and mask\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ct nifti path : /content/TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931/PCAMPMRI-00009_1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931.nii.gz\n",
      " mask path : /content/TEST/seg_objects/nii_resampled_renamed/1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931/Peripheral zone of the prostate.nii.gz\n",
      "labelValue : 2\n",
      "label_name : Peripheral zone of the prostate\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:Computing shape\n",
      "Feature Compactness1 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness1 is deprecated, use with caution!\n",
      "Feature Compactness2 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness2 is deprecated, use with caution!\n",
      "Feature SphericalDisproportion is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature SphericalDisproportion is deprecated, use with caution!\n",
      "INFO:radiomics.featureextractor:Adding image type \"Original\" with custom settings: {}\n",
      "INFO:radiomics.featureextractor:Calculating features for original image\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "created df_features\n",
      "segment_id: 0\n",
      "ReferencedSegment: 4\n",
      "FindingSite: Prostate\n",
      "segment_id: 1\n",
      "ReferencedSegment: 2\n",
      "FindingSite: Peripheral zone of the prostate\n",
      "created SR json for shape features\n",
      "wrote out json for shape features\n",
      "inputImageLibraryDirectory: /content/TEST/idc_image_data/dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931/qin_prostate_repeatability/PCAMPMRI-00009/1.3.6.1.4.1.14519.5.2.1.3671.4754.864607788085827202303582199118/MR_1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931\n",
      "outputDICOM: /content/TEST/seg_objects/dicom_sr/1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931/1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931_SR.dcm\n",
      "inputCompositeContextDirectory: e36e0862-575e-48f8-8fc1-104fbbf44d01.dcm\n",
      "inputMetadata_json: /content/TEST/seg_objects/dicom_sr_json/1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931/1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931_SR.json\n",
      "dcmqi repository URL: https://github.com/QIICR/dcmqi revision: d88b025 tag: v1.3.4\n",
      "Total measurement groups: 2\n",
      "Adding to compositeContext: /content/TEST/seg_unzip/combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.117459950571016749056636056931/e36e0862-575e-48f8-8fc1-104fbbf44d01.dcm\n",
      "Composite Context has been initialized\n",
      "SR saved!\n",
      "wrote out SR for shape features\n",
      "\n",
      "\n",
      "serieUID image referenced : 1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480\n",
      "dcmqi repository URL: https://github.com/QIICR/dcmqi revision: d88b025 tag: v1.3.4\n",
      "Loading DICOM SEG file TEST/seg_unzip/combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480/6689344c-8b81-4282-aa49-af3a29cc9527.dcm\n",
      "Row direction: 0.99824 0.0592954 -2.73264e-06\n",
      "Col direction: 0.0567975 -0.956201 -0.287147\n",
      "Z direction: -0.0170291 0.286642 -0.957886\n",
      "Total frames: 32\n",
      "Total frames with unique IPP: 17\n",
      "Total overlapping frames: 13\n",
      "Origin: [-89.0328, 31.195, 23.5008]\n",
      "Slice extent: 48\n",
      "Slice spacing: 3\n",
      "Will not merge segments: Splitting segments into 3 groups\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480/1.nii.gz ... done\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480/2.nii.gz ... done\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480/3.nii.gz ... done\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Downloading data: 100%|██████████| 17.9M/17.9M [00:01<00:00, 17.8MB/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Chris Rorden's dcm2niiX version v1.0.20220505  GCC11.4.0 x86-64 (64-bit Linux)\n",
      "Found 34 DICOM file(s)\n",
      "Convert 34 DICOM as TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480/PCAMPMRI-00006_1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480 (512x512x34x1)\n",
      "Conversion required 1.048482 seconds (1.047158 for core code).\n",
      "\n",
      "Running 'plastimatch convert' with the specified arguments:\n",
      "  --input TEST/idc_image_data/dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480/qin_prostate_repeatability/PCAMPMRI-00006/1.3.6.1.4.1.14519.5.2.1.3671.4754.287814201869490350714498330797/MR_1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480\n",
      "  --output-img TEST/idc_image_data/nrrd/1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480/1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480.nrrd\n",
      "... Done.\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480/2.nii.gz\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480/1.nii.gz\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480/3.nii.gz\n",
      "SegmentAlgorithmName : MANUAL\n",
      "label_values: [3, 2]\n",
      "label_names: ['Prostate', 'Peripheral zone of the prostate']\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:No valid config parameter, using defaults: {'minimumROIDimensions': 2, 'minimumROISize': None, 'normalize': False, 'normalizeScale': 1, 'removeOutliers': None, 'resampledPixelSpacing': None, 'interpolator': 'sitkBSpline', 'preCrop': False, 'padDistance': 5, 'distances': [1], 'force2D': False, 'force2Ddimension': 0, 'resegmentRange': None, 'label': 1, 'additionalInfo': True}\n",
      "INFO:radiomics.featureextractor:Enabled image types: {'Original': {}}\n",
      "INFO:radiomics.featureextractor:Enabled features: {'firstorder': [], 'glcm': [], 'gldm': [], 'glrlm': [], 'glszm': [], 'ngtdm': [], 'shape': []}\n",
      "INFO:radiomics.featureextractor:Applying custom setting overrides: {'correctMask': True, 'geometryTolerance': 0.0001, 'label': 3}\n",
      "INFO:radiomics.featureextractor:Calculating features with label: 3\n",
      "INFO:radiomics.featureextractor:Loading image and mask\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ct nifti path : /content/TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480/PCAMPMRI-00006_1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480.nii.gz\n",
      " mask path : /content/TEST/seg_objects/nii_resampled_renamed/1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480/Prostate.nii.gz\n",
      "labelValue : 3\n",
      "label_name : Prostate\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:Computing shape\n",
      "Feature Compactness1 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness1 is deprecated, use with caution!\n",
      "Feature Compactness2 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness2 is deprecated, use with caution!\n",
      "Feature SphericalDisproportion is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature SphericalDisproportion is deprecated, use with caution!\n",
      "INFO:radiomics.featureextractor:Adding image type \"Original\" with custom settings: {}\n",
      "INFO:radiomics.featureextractor:Calculating features for original image\n",
      "INFO:radiomics.featureextractor:No valid config parameter, using defaults: {'minimumROIDimensions': 2, 'minimumROISize': None, 'normalize': False, 'normalizeScale': 1, 'removeOutliers': None, 'resampledPixelSpacing': None, 'interpolator': 'sitkBSpline', 'preCrop': False, 'padDistance': 5, 'distances': [1], 'force2D': False, 'force2Ddimension': 0, 'resegmentRange': None, 'label': 1, 'additionalInfo': True}\n",
      "INFO:radiomics.featureextractor:Enabled image types: {'Original': {}}\n",
      "INFO:radiomics.featureextractor:Enabled features: {'firstorder': [], 'glcm': [], 'gldm': [], 'glrlm': [], 'glszm': [], 'ngtdm': [], 'shape': []}\n",
      "INFO:radiomics.featureextractor:Applying custom setting overrides: {'correctMask': True, 'geometryTolerance': 0.0001, 'label': 2}\n",
      "INFO:radiomics.featureextractor:Calculating features with label: 2\n",
      "INFO:radiomics.featureextractor:Loading image and mask\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ct nifti path : /content/TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480/PCAMPMRI-00006_1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480.nii.gz\n",
      " mask path : /content/TEST/seg_objects/nii_resampled_renamed/1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480/Peripheral zone of the prostate.nii.gz\n",
      "labelValue : 2\n",
      "label_name : Peripheral zone of the prostate\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:Computing shape\n",
      "Feature Compactness1 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness1 is deprecated, use with caution!\n",
      "Feature Compactness2 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness2 is deprecated, use with caution!\n",
      "Feature SphericalDisproportion is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature SphericalDisproportion is deprecated, use with caution!\n",
      "INFO:radiomics.featureextractor:Adding image type \"Original\" with custom settings: {}\n",
      "INFO:radiomics.featureextractor:Calculating features for original image\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "created df_features\n",
      "segment_id: 0\n",
      "ReferencedSegment: 3\n",
      "FindingSite: Prostate\n",
      "segment_id: 1\n",
      "ReferencedSegment: 2\n",
      "FindingSite: Peripheral zone of the prostate\n",
      "created SR json for shape features\n",
      "wrote out json for shape features\n",
      "inputImageLibraryDirectory: /content/TEST/idc_image_data/dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480/qin_prostate_repeatability/PCAMPMRI-00006/1.3.6.1.4.1.14519.5.2.1.3671.4754.287814201869490350714498330797/MR_1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480\n",
      "outputDICOM: /content/TEST/seg_objects/dicom_sr/1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480/1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480_SR.dcm\n",
      "inputCompositeContextDirectory: 6689344c-8b81-4282-aa49-af3a29cc9527.dcm\n",
      "inputMetadata_json: /content/TEST/seg_objects/dicom_sr_json/1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480/1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480_SR.json\n",
      "dcmqi repository URL: https://github.com/QIICR/dcmqi revision: d88b025 tag: v1.3.4\n",
      "Total measurement groups: 2\n",
      "Adding to compositeContext: /content/TEST/seg_unzip/combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.124813816937601110554342446480/6689344c-8b81-4282-aa49-af3a29cc9527.dcm\n",
      "Composite Context has been initialized\n",
      "SR saved!\n",
      "wrote out SR for shape features\n",
      "\n",
      "\n",
      "serieUID image referenced : 1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172\n",
      "dcmqi repository URL: https://github.com/QIICR/dcmqi revision: d88b025 tag: v1.3.4\n",
      "Loading DICOM SEG file TEST/seg_unzip/combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172/7540b951-70e5-449b-8747-79397bfede9a.dcm\n",
      "Row direction: 0.999976 -0.00674503 -0.00183578\n",
      "Col direction: -0.00691257 -0.993212 -0.116116\n",
      "Z direction: -0.00104012 0.116126 -0.993234\n",
      "Total frames: 16\n",
      "Total frames with unique IPP: 8\n",
      "Total overlapping frames: 7\n",
      "Origin: [-54.0669, 92.9251, 7.07746]\n",
      "Slice extent: 24.5\n",
      "Slice spacing: 3.5\n",
      "Will not merge segments: Splitting segments into 3 groups\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172/1.nii.gz ... done\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172/2.nii.gz ... done\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172/3.nii.gz ... done\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Downloading data: 100%|██████████| 14.8M/14.8M [00:01<00:00, 14.7MB/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Chris Rorden's dcm2niiX version v1.0.20220505  GCC11.4.0 x86-64 (64-bit Linux)\n",
      "Found 28 DICOM file(s)\n",
      "Convert 28 DICOM as TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172/PCAMPMRI-00014_1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172 (512x512x28x1)\n",
      "Conversion required 0.932408 seconds (0.932210 for core code).\n",
      "\n",
      "Running 'plastimatch convert' with the specified arguments:\n",
      "  --input TEST/idc_image_data/dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172/qin_prostate_repeatability/PCAMPMRI-00014/1.3.6.1.4.1.14519.5.2.1.3671.4754.194890890650697728529329442454/MR_1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172\n",
      "  --output-img TEST/idc_image_data/nrrd/1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172/1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172.nrrd\n",
      "... Done.\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172/2.nii.gz\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172/1.nii.gz\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172/3.nii.gz\n",
      "SegmentAlgorithmName : MANUAL\n",
      "label_values: [3, 2]\n",
      "label_names: ['Prostate', 'Peripheral zone of the prostate']\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:No valid config parameter, using defaults: {'minimumROIDimensions': 2, 'minimumROISize': None, 'normalize': False, 'normalizeScale': 1, 'removeOutliers': None, 'resampledPixelSpacing': None, 'interpolator': 'sitkBSpline', 'preCrop': False, 'padDistance': 5, 'distances': [1], 'force2D': False, 'force2Ddimension': 0, 'resegmentRange': None, 'label': 1, 'additionalInfo': True}\n",
      "INFO:radiomics.featureextractor:Enabled image types: {'Original': {}}\n",
      "INFO:radiomics.featureextractor:Enabled features: {'firstorder': [], 'glcm': [], 'gldm': [], 'glrlm': [], 'glszm': [], 'ngtdm': [], 'shape': []}\n",
      "INFO:radiomics.featureextractor:Applying custom setting overrides: {'correctMask': True, 'geometryTolerance': 0.0001, 'label': 3}\n",
      "INFO:radiomics.featureextractor:Calculating features with label: 3\n",
      "INFO:radiomics.featureextractor:Loading image and mask\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ct nifti path : /content/TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172/PCAMPMRI-00014_1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172.nii.gz\n",
      " mask path : /content/TEST/seg_objects/nii_resampled_renamed/1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172/Prostate.nii.gz\n",
      "labelValue : 3\n",
      "label_name : Prostate\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:Computing shape\n",
      "Feature Compactness1 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness1 is deprecated, use with caution!\n",
      "Feature Compactness2 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness2 is deprecated, use with caution!\n",
      "Feature SphericalDisproportion is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature SphericalDisproportion is deprecated, use with caution!\n",
      "INFO:radiomics.featureextractor:Adding image type \"Original\" with custom settings: {}\n",
      "INFO:radiomics.featureextractor:Calculating features for original image\n",
      "INFO:radiomics.featureextractor:No valid config parameter, using defaults: {'minimumROIDimensions': 2, 'minimumROISize': None, 'normalize': False, 'normalizeScale': 1, 'removeOutliers': None, 'resampledPixelSpacing': None, 'interpolator': 'sitkBSpline', 'preCrop': False, 'padDistance': 5, 'distances': [1], 'force2D': False, 'force2Ddimension': 0, 'resegmentRange': None, 'label': 1, 'additionalInfo': True}\n",
      "INFO:radiomics.featureextractor:Enabled image types: {'Original': {}}\n",
      "INFO:radiomics.featureextractor:Enabled features: {'firstorder': [], 'glcm': [], 'gldm': [], 'glrlm': [], 'glszm': [], 'ngtdm': [], 'shape': []}\n",
      "INFO:radiomics.featureextractor:Applying custom setting overrides: {'correctMask': True, 'geometryTolerance': 0.0001, 'label': 2}\n",
      "INFO:radiomics.featureextractor:Calculating features with label: 2\n",
      "INFO:radiomics.featureextractor:Loading image and mask\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ct nifti path : /content/TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172/PCAMPMRI-00014_1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172.nii.gz\n",
      " mask path : /content/TEST/seg_objects/nii_resampled_renamed/1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172/Peripheral zone of the prostate.nii.gz\n",
      "labelValue : 2\n",
      "label_name : Peripheral zone of the prostate\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:Computing shape\n",
      "Feature Compactness1 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness1 is deprecated, use with caution!\n",
      "Feature Compactness2 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness2 is deprecated, use with caution!\n",
      "Feature SphericalDisproportion is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature SphericalDisproportion is deprecated, use with caution!\n",
      "INFO:radiomics.featureextractor:Adding image type \"Original\" with custom settings: {}\n",
      "INFO:radiomics.featureextractor:Calculating features for original image\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "created df_features\n",
      "segment_id: 0\n",
      "ReferencedSegment: 3\n",
      "FindingSite: Prostate\n",
      "segment_id: 1\n",
      "ReferencedSegment: 2\n",
      "FindingSite: Peripheral zone of the prostate\n",
      "created SR json for shape features\n",
      "wrote out json for shape features\n",
      "inputImageLibraryDirectory: /content/TEST/idc_image_data/dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172/qin_prostate_repeatability/PCAMPMRI-00014/1.3.6.1.4.1.14519.5.2.1.3671.4754.194890890650697728529329442454/MR_1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172\n",
      "outputDICOM: /content/TEST/seg_objects/dicom_sr/1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172/1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172_SR.dcm\n",
      "inputCompositeContextDirectory: 7540b951-70e5-449b-8747-79397bfede9a.dcm\n",
      "inputMetadata_json: /content/TEST/seg_objects/dicom_sr_json/1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172/1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172_SR.json\n",
      "dcmqi repository URL: https://github.com/QIICR/dcmqi revision: d88b025 tag: v1.3.4\n",
      "Total measurement groups: 2\n",
      "Adding to compositeContext: /content/TEST/seg_unzip/combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.155463265953508142920250222172/7540b951-70e5-449b-8747-79397bfede9a.dcm\n",
      "Composite Context has been initialized\n",
      "SR saved!\n",
      "wrote out SR for shape features\n",
      "\n",
      "\n",
      "serieUID image referenced : 1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147\n",
      "dcmqi repository URL: https://github.com/QIICR/dcmqi revision: d88b025 tag: v1.3.4\n",
      "Loading DICOM SEG file TEST/seg_unzip/combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147/56866f5f-1d17-48ed-8ed3-5218adc662b5.dcm\n",
      "Row direction: 0.999066 0.0430733 -0.00342618\n",
      "Col direction: 0.0427847 -0.997222 -0.0609658\n",
      "Z direction: -0.00604266 0.0607623 -0.998134\n",
      "Total frames: 19\n",
      "Total frames with unique IPP: 9\n",
      "Total overlapping frames: 7\n",
      "Origin: [-92.0149, 95.2166, -70.0256]\n",
      "Slice extent: 28\n",
      "Slice spacing: 3.5\n",
      "Will not merge segments: Splitting segments into 4 groups\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147/1.nii.gz ... done\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147/2.nii.gz ... done\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147/3.nii.gz ... done\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147/4.nii.gz ... done\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Downloading data: 100%|█████████▉| 15.8M/15.8M [00:01<00:00, 15.7MB/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Chris Rorden's dcm2niiX version v1.0.20220505  GCC11.4.0 x86-64 (64-bit Linux)\n",
      "Found 30 DICOM file(s)\n",
      "Convert 30 DICOM as TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147/PCAMPMRI-00010_1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147 (512x512x30x1)\n",
      "Conversion required 1.022540 seconds (1.021063 for core code).\n",
      "\n",
      "Running 'plastimatch convert' with the specified arguments:\n",
      "  --input TEST/idc_image_data/dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147/qin_prostate_repeatability/PCAMPMRI-00010/1.3.6.1.4.1.14519.5.2.1.3671.4754.318227959935022390930294557376/MR_1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147\n",
      "  --output-img TEST/idc_image_data/nrrd/1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147/1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147.nrrd\n",
      "... Done.\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147/2.nii.gz\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147/1.nii.gz\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147/4.nii.gz\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147/3.nii.gz\n",
      "SegmentAlgorithmName : MANUAL\n",
      "label_values: [4, 2]\n",
      "label_names: ['Prostate', 'Peripheral zone of the prostate']\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:No valid config parameter, using defaults: {'minimumROIDimensions': 2, 'minimumROISize': None, 'normalize': False, 'normalizeScale': 1, 'removeOutliers': None, 'resampledPixelSpacing': None, 'interpolator': 'sitkBSpline', 'preCrop': False, 'padDistance': 5, 'distances': [1], 'force2D': False, 'force2Ddimension': 0, 'resegmentRange': None, 'label': 1, 'additionalInfo': True}\n",
      "INFO:radiomics.featureextractor:Enabled image types: {'Original': {}}\n",
      "INFO:radiomics.featureextractor:Enabled features: {'firstorder': [], 'glcm': [], 'gldm': [], 'glrlm': [], 'glszm': [], 'ngtdm': [], 'shape': []}\n",
      "INFO:radiomics.featureextractor:Applying custom setting overrides: {'correctMask': True, 'geometryTolerance': 0.0001, 'label': 4}\n",
      "INFO:radiomics.featureextractor:Calculating features with label: 4\n",
      "INFO:radiomics.featureextractor:Loading image and mask\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ct nifti path : /content/TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147/PCAMPMRI-00010_1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147.nii.gz\n",
      " mask path : /content/TEST/seg_objects/nii_resampled_renamed/1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147/Prostate.nii.gz\n",
      "labelValue : 4\n",
      "label_name : Prostate\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:Computing shape\n",
      "Feature Compactness1 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness1 is deprecated, use with caution!\n",
      "Feature Compactness2 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness2 is deprecated, use with caution!\n",
      "Feature SphericalDisproportion is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature SphericalDisproportion is deprecated, use with caution!\n",
      "INFO:radiomics.featureextractor:Adding image type \"Original\" with custom settings: {}\n",
      "INFO:radiomics.featureextractor:Calculating features for original image\n",
      "INFO:radiomics.featureextractor:No valid config parameter, using defaults: {'minimumROIDimensions': 2, 'minimumROISize': None, 'normalize': False, 'normalizeScale': 1, 'removeOutliers': None, 'resampledPixelSpacing': None, 'interpolator': 'sitkBSpline', 'preCrop': False, 'padDistance': 5, 'distances': [1], 'force2D': False, 'force2Ddimension': 0, 'resegmentRange': None, 'label': 1, 'additionalInfo': True}\n",
      "INFO:radiomics.featureextractor:Enabled image types: {'Original': {}}\n",
      "INFO:radiomics.featureextractor:Enabled features: {'firstorder': [], 'glcm': [], 'gldm': [], 'glrlm': [], 'glszm': [], 'ngtdm': [], 'shape': []}\n",
      "INFO:radiomics.featureextractor:Applying custom setting overrides: {'correctMask': True, 'geometryTolerance': 0.0001, 'label': 2}\n",
      "INFO:radiomics.featureextractor:Calculating features with label: 2\n",
      "INFO:radiomics.featureextractor:Loading image and mask\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ct nifti path : /content/TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147/PCAMPMRI-00010_1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147.nii.gz\n",
      " mask path : /content/TEST/seg_objects/nii_resampled_renamed/1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147/Peripheral zone of the prostate.nii.gz\n",
      "labelValue : 2\n",
      "label_name : Peripheral zone of the prostate\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:Computing shape\n",
      "Feature Compactness1 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness1 is deprecated, use with caution!\n",
      "Feature Compactness2 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness2 is deprecated, use with caution!\n",
      "Feature SphericalDisproportion is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature SphericalDisproportion is deprecated, use with caution!\n",
      "INFO:radiomics.featureextractor:Adding image type \"Original\" with custom settings: {}\n",
      "INFO:radiomics.featureextractor:Calculating features for original image\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "created df_features\n",
      "segment_id: 0\n",
      "ReferencedSegment: 4\n",
      "FindingSite: Prostate\n",
      "segment_id: 1\n",
      "ReferencedSegment: 2\n",
      "FindingSite: Peripheral zone of the prostate\n",
      "created SR json for shape features\n",
      "wrote out json for shape features\n",
      "inputImageLibraryDirectory: /content/TEST/idc_image_data/dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147/qin_prostate_repeatability/PCAMPMRI-00010/1.3.6.1.4.1.14519.5.2.1.3671.4754.318227959935022390930294557376/MR_1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147\n",
      "outputDICOM: /content/TEST/seg_objects/dicom_sr/1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147/1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147_SR.dcm\n",
      "inputCompositeContextDirectory: 56866f5f-1d17-48ed-8ed3-5218adc662b5.dcm\n",
      "inputMetadata_json: /content/TEST/seg_objects/dicom_sr_json/1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147/1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147_SR.json\n",
      "dcmqi repository URL: https://github.com/QIICR/dcmqi revision: d88b025 tag: v1.3.4\n",
      "Total measurement groups: 2\n",
      "Adding to compositeContext: /content/TEST/seg_unzip/combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.105976129314091491952445656147/56866f5f-1d17-48ed-8ed3-5218adc662b5.dcm\n",
      "Composite Context has been initialized\n",
      "SR saved!\n",
      "wrote out SR for shape features\n",
      "\n",
      "\n",
      "serieUID image referenced : 1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223\n",
      "dcmqi repository URL: https://github.com/QIICR/dcmqi revision: d88b025 tag: v1.3.4\n",
      "Loading DICOM SEG file TEST/seg_unzip/combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223/bf1e495e-5b73-4efa-8a63-d80b8426034a.dcm\n",
      "Row direction: 0.999988 0.00336207 0.00344383\n",
      "Col direction: 0.0040773 -0.971981 -0.235024\n",
      "Z direction: 0.00255717 0.235035 -0.971983\n",
      "Total frames: 22\n",
      "Total frames with unique IPP: 9\n",
      "Total overlapping frames: 8\n",
      "Origin: [-83.8114, 88.4381, 116.113]\n",
      "Slice extent: 28\n",
      "Slice spacing: 3.5\n",
      "Will not merge segments: Splitting segments into 4 groups\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223/1.nii.gz ... done\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223/2.nii.gz ... done\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223/3.nii.gz ... done\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223/4.nii.gz ... done\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Downloading data: 100%|██████████| 14.8M/14.8M [00:01<00:00, 14.7MB/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Chris Rorden's dcm2niiX version v1.0.20220505  GCC11.4.0 x86-64 (64-bit Linux)\n",
      "Found 28 DICOM file(s)\n",
      "Convert 28 DICOM as TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223/PCAMPMRI-00011_1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223 (512x512x28x1)\n",
      "Conversion required 0.981619 seconds (0.981355 for core code).\n",
      "\n",
      "Running 'plastimatch convert' with the specified arguments:\n",
      "  --input TEST/idc_image_data/dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223/qin_prostate_repeatability/PCAMPMRI-00011/1.3.6.1.4.1.14519.5.2.1.3671.4754.131608903441424620949571415524/MR_1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223\n",
      "  --output-img TEST/idc_image_data/nrrd/1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223/1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223.nrrd\n",
      "... Done.\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223/2.nii.gz\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223/1.nii.gz\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223/4.nii.gz\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223/3.nii.gz\n",
      "SegmentAlgorithmName : MANUAL\n",
      "label_values: [4, 2]\n",
      "label_names: ['Prostate', 'Peripheral zone of the prostate']\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:No valid config parameter, using defaults: {'minimumROIDimensions': 2, 'minimumROISize': None, 'normalize': False, 'normalizeScale': 1, 'removeOutliers': None, 'resampledPixelSpacing': None, 'interpolator': 'sitkBSpline', 'preCrop': False, 'padDistance': 5, 'distances': [1], 'force2D': False, 'force2Ddimension': 0, 'resegmentRange': None, 'label': 1, 'additionalInfo': True}\n",
      "INFO:radiomics.featureextractor:Enabled image types: {'Original': {}}\n",
      "INFO:radiomics.featureextractor:Enabled features: {'firstorder': [], 'glcm': [], 'gldm': [], 'glrlm': [], 'glszm': [], 'ngtdm': [], 'shape': []}\n",
      "INFO:radiomics.featureextractor:Applying custom setting overrides: {'correctMask': True, 'geometryTolerance': 0.0001, 'label': 4}\n",
      "INFO:radiomics.featureextractor:Calculating features with label: 4\n",
      "INFO:radiomics.featureextractor:Loading image and mask\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ct nifti path : /content/TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223/PCAMPMRI-00011_1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223.nii.gz\n",
      " mask path : /content/TEST/seg_objects/nii_resampled_renamed/1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223/Prostate.nii.gz\n",
      "labelValue : 4\n",
      "label_name : Prostate\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:Computing shape\n",
      "Feature Compactness1 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness1 is deprecated, use with caution!\n",
      "Feature Compactness2 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness2 is deprecated, use with caution!\n",
      "Feature SphericalDisproportion is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature SphericalDisproportion is deprecated, use with caution!\n",
      "INFO:radiomics.featureextractor:Adding image type \"Original\" with custom settings: {}\n",
      "INFO:radiomics.featureextractor:Calculating features for original image\n",
      "INFO:radiomics.featureextractor:No valid config parameter, using defaults: {'minimumROIDimensions': 2, 'minimumROISize': None, 'normalize': False, 'normalizeScale': 1, 'removeOutliers': None, 'resampledPixelSpacing': None, 'interpolator': 'sitkBSpline', 'preCrop': False, 'padDistance': 5, 'distances': [1], 'force2D': False, 'force2Ddimension': 0, 'resegmentRange': None, 'label': 1, 'additionalInfo': True}\n",
      "INFO:radiomics.featureextractor:Enabled image types: {'Original': {}}\n",
      "INFO:radiomics.featureextractor:Enabled features: {'firstorder': [], 'glcm': [], 'gldm': [], 'glrlm': [], 'glszm': [], 'ngtdm': [], 'shape': []}\n",
      "INFO:radiomics.featureextractor:Applying custom setting overrides: {'correctMask': True, 'geometryTolerance': 0.0001, 'label': 2}\n",
      "INFO:radiomics.featureextractor:Calculating features with label: 2\n",
      "INFO:radiomics.featureextractor:Loading image and mask\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ct nifti path : /content/TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223/PCAMPMRI-00011_1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223.nii.gz\n",
      " mask path : /content/TEST/seg_objects/nii_resampled_renamed/1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223/Peripheral zone of the prostate.nii.gz\n",
      "labelValue : 2\n",
      "label_name : Peripheral zone of the prostate\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:Computing shape\n",
      "Feature Compactness1 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness1 is deprecated, use with caution!\n",
      "Feature Compactness2 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness2 is deprecated, use with caution!\n",
      "Feature SphericalDisproportion is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature SphericalDisproportion is deprecated, use with caution!\n",
      "INFO:radiomics.featureextractor:Adding image type \"Original\" with custom settings: {}\n",
      "INFO:radiomics.featureextractor:Calculating features for original image\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "created df_features\n",
      "segment_id: 0\n",
      "ReferencedSegment: 4\n",
      "FindingSite: Prostate\n",
      "segment_id: 1\n",
      "ReferencedSegment: 2\n",
      "FindingSite: Peripheral zone of the prostate\n",
      "created SR json for shape features\n",
      "wrote out json for shape features\n",
      "inputImageLibraryDirectory: /content/TEST/idc_image_data/dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223/qin_prostate_repeatability/PCAMPMRI-00011/1.3.6.1.4.1.14519.5.2.1.3671.4754.131608903441424620949571415524/MR_1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223\n",
      "outputDICOM: /content/TEST/seg_objects/dicom_sr/1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223/1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223_SR.dcm\n",
      "inputCompositeContextDirectory: bf1e495e-5b73-4efa-8a63-d80b8426034a.dcm\n",
      "inputMetadata_json: /content/TEST/seg_objects/dicom_sr_json/1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223/1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223_SR.json\n",
      "dcmqi repository URL: https://github.com/QIICR/dcmqi revision: d88b025 tag: v1.3.4\n",
      "Total measurement groups: 2\n",
      "Adding to compositeContext: /content/TEST/seg_unzip/combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.212083125906384321957172108223/bf1e495e-5b73-4efa-8a63-d80b8426034a.dcm\n",
      "Composite Context has been initialized\n",
      "SR saved!\n",
      "wrote out SR for shape features\n",
      "\n",
      "\n",
      "serieUID image referenced : 1.3.6.1.4.1.14519.5.2.1.3671.4754.621341845114918594203879249474\n",
      "dcmqi repository URL: https://github.com/QIICR/dcmqi revision: d88b025 tag: v1.3.4\n",
      "Loading DICOM SEG file TEST/seg_unzip/combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.621341845114918594203879249474/32a4c94b-1057-4535-be91-4f4e54f4b6ad.dcm\n",
      "Row direction: 0.99998 0.00195692 0.0060752\n",
      "Col direction: 0.0021987 -0.999195 -0.0400496\n",
      "Z direction: 0.00599194 0.0400622 -0.999179\n",
      "Total frames: 22\n",
      "Total frames with unique IPP: 14\n",
      "Total overlapping frames: 8\n",
      "Origin: [-84.8898, 103.272, 200.896]\n",
      "Slice extent: 45.5114\n",
      "Slice spacing: 3.50087\n",
      "Will not merge segments: Splitting segments into 2 groups\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.621341845114918594203879249474/1.nii.gz ... done\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.621341845114918594203879249474/2.nii.gz ... done\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Downloading data: 100%|██████████| 14.8M/14.8M [00:01<00:00, 14.7MB/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Chris Rorden's dcm2niiX version v1.0.20220505  GCC11.4.0 x86-64 (64-bit Linux)\n",
      "Found 28 DICOM file(s)\n",
      "Convert 28 DICOM as TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.621341845114918594203879249474/PCAMPMRI-00015_1.3.6.1.4.1.14519.5.2.1.3671.4754.621341845114918594203879249474 (512x512x28x1)\n",
      "Conversion required 0.869408 seconds (0.869231 for core code).\n",
      "\n",
      "Running 'plastimatch convert' with the specified arguments:\n",
      "  --input TEST/idc_image_data/dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.621341845114918594203879249474/qin_prostate_repeatability/PCAMPMRI-00015/1.3.6.1.4.1.14519.5.2.1.3671.4754.431678793261759442965045820561/MR_1.3.6.1.4.1.14519.5.2.1.3671.4754.621341845114918594203879249474\n",
      "  --output-img TEST/idc_image_data/nrrd/1.3.6.1.4.1.14519.5.2.1.3671.4754.621341845114918594203879249474/1.3.6.1.4.1.14519.5.2.1.3671.4754.621341845114918594203879249474.nrrd\n",
      "... Done.\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.621341845114918594203879249474/2.nii.gz\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.621341845114918594203879249474/1.nii.gz\n",
      "SegmentAlgorithmName : MANUAL\n",
      "label_values: [2, 1]\n",
      "label_names: ['Prostate', 'Peripheral zone of the prostate']\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:No valid config parameter, using defaults: {'minimumROIDimensions': 2, 'minimumROISize': None, 'normalize': False, 'normalizeScale': 1, 'removeOutliers': None, 'resampledPixelSpacing': None, 'interpolator': 'sitkBSpline', 'preCrop': False, 'padDistance': 5, 'distances': [1], 'force2D': False, 'force2Ddimension': 0, 'resegmentRange': None, 'label': 1, 'additionalInfo': True}\n",
      "INFO:radiomics.featureextractor:Enabled image types: {'Original': {}}\n",
      "INFO:radiomics.featureextractor:Enabled features: {'firstorder': [], 'glcm': [], 'gldm': [], 'glrlm': [], 'glszm': [], 'ngtdm': [], 'shape': []}\n",
      "INFO:radiomics.featureextractor:Applying custom setting overrides: {'correctMask': True, 'geometryTolerance': 0.0001, 'label': 2}\n",
      "INFO:radiomics.featureextractor:Calculating features with label: 2\n",
      "INFO:radiomics.featureextractor:Loading image and mask\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ct nifti path : /content/TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.621341845114918594203879249474/PCAMPMRI-00015_1.3.6.1.4.1.14519.5.2.1.3671.4754.621341845114918594203879249474.nii.gz\n",
      " mask path : /content/TEST/seg_objects/nii_resampled_renamed/1.3.6.1.4.1.14519.5.2.1.3671.4754.621341845114918594203879249474/Prostate.nii.gz\n",
      "labelValue : 2\n",
      "label_name : Prostate\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:Computing shape\n",
      "Feature Compactness1 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness1 is deprecated, use with caution!\n",
      "Feature Compactness2 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness2 is deprecated, use with caution!\n",
      "Feature SphericalDisproportion is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature SphericalDisproportion is deprecated, use with caution!\n",
      "INFO:radiomics.featureextractor:Adding image type \"Original\" with custom settings: {}\n",
      "INFO:radiomics.featureextractor:Calculating features for original image\n",
      "INFO:radiomics.featureextractor:No valid config parameter, using defaults: {'minimumROIDimensions': 2, 'minimumROISize': None, 'normalize': False, 'normalizeScale': 1, 'removeOutliers': None, 'resampledPixelSpacing': None, 'interpolator': 'sitkBSpline', 'preCrop': False, 'padDistance': 5, 'distances': [1], 'force2D': False, 'force2Ddimension': 0, 'resegmentRange': None, 'label': 1, 'additionalInfo': True}\n",
      "INFO:radiomics.featureextractor:Enabled image types: {'Original': {}}\n",
      "INFO:radiomics.featureextractor:Enabled features: {'firstorder': [], 'glcm': [], 'gldm': [], 'glrlm': [], 'glszm': [], 'ngtdm': [], 'shape': []}\n",
      "INFO:radiomics.featureextractor:Applying custom setting overrides: {'correctMask': True, 'geometryTolerance': 0.0001, 'label': 1}\n",
      "INFO:radiomics.featureextractor:Calculating features with label: 1\n",
      "INFO:radiomics.featureextractor:Loading image and mask\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ct nifti path : /content/TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.621341845114918594203879249474/PCAMPMRI-00015_1.3.6.1.4.1.14519.5.2.1.3671.4754.621341845114918594203879249474.nii.gz\n",
      " mask path : /content/TEST/seg_objects/nii_resampled_renamed/1.3.6.1.4.1.14519.5.2.1.3671.4754.621341845114918594203879249474/Peripheral zone of the prostate.nii.gz\n",
      "labelValue : 1\n",
      "label_name : Peripheral zone of the prostate\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:Computing shape\n",
      "Feature Compactness1 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness1 is deprecated, use with caution!\n",
      "Feature Compactness2 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness2 is deprecated, use with caution!\n",
      "Feature SphericalDisproportion is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature SphericalDisproportion is deprecated, use with caution!\n",
      "INFO:radiomics.featureextractor:Adding image type \"Original\" with custom settings: {}\n",
      "INFO:radiomics.featureextractor:Calculating features for original image\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "created df_features\n",
      "segment_id: 0\n",
      "ReferencedSegment: 2\n",
      "FindingSite: Prostate\n",
      "segment_id: 1\n",
      "ReferencedSegment: 1\n",
      "FindingSite: Peripheral zone of the prostate\n",
      "created SR json for shape features\n",
      "wrote out json for shape features\n",
      "inputImageLibraryDirectory: /content/TEST/idc_image_data/dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.621341845114918594203879249474/qin_prostate_repeatability/PCAMPMRI-00015/1.3.6.1.4.1.14519.5.2.1.3671.4754.431678793261759442965045820561/MR_1.3.6.1.4.1.14519.5.2.1.3671.4754.621341845114918594203879249474\n",
      "outputDICOM: /content/TEST/seg_objects/dicom_sr/1.3.6.1.4.1.14519.5.2.1.3671.4754.621341845114918594203879249474/1.3.6.1.4.1.14519.5.2.1.3671.4754.621341845114918594203879249474_SR.dcm\n",
      "inputCompositeContextDirectory: 32a4c94b-1057-4535-be91-4f4e54f4b6ad.dcm\n",
      "inputMetadata_json: /content/TEST/seg_objects/dicom_sr_json/1.3.6.1.4.1.14519.5.2.1.3671.4754.621341845114918594203879249474/1.3.6.1.4.1.14519.5.2.1.3671.4754.621341845114918594203879249474_SR.json\n",
      "dcmqi repository URL: https://github.com/QIICR/dcmqi revision: d88b025 tag: v1.3.4\n",
      "Total measurement groups: 2\n",
      "Adding to compositeContext: /content/TEST/seg_unzip/combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.621341845114918594203879249474/32a4c94b-1057-4535-be91-4f4e54f4b6ad.dcm\n",
      "Composite Context has been initialized\n",
      "SR saved!\n",
      "wrote out SR for shape features\n",
      "\n",
      "\n",
      "serieUID image referenced : 1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936\n",
      "dcmqi repository URL: https://github.com/QIICR/dcmqi revision: d88b025 tag: v1.3.4\n",
      "Loading DICOM SEG file TEST/seg_unzip/combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936/d148919e-2c32-4501-9315-3f55c2ba31a5.dcm\n",
      "Row direction: 0.994439 0.0988235 -0.0364065\n",
      "Col direction: 0.087248 -0.966655 -0.240763\n",
      "Z direction: -0.0589855 0.236247 -0.969901\n",
      "Total frames: 27\n",
      "Total frames with unique IPP: 13\n",
      "Total overlapping frames: 10\n",
      "Origin: [-95.0362, 33.0869, 47.1416]\n",
      "Slice extent: 35.9978\n",
      "Slice spacing: 2.99982\n",
      "Will not merge segments: Splitting segments into 3 groups\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936/1.nii.gz ... done\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936/2.nii.gz ... done\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936/3.nii.gz ... done\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Downloading data: 100%|██████████| 15.8M/15.8M [00:01<00:00, 15.7MB/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Chris Rorden's dcm2niiX version v1.0.20220505  GCC11.4.0 x86-64 (64-bit Linux)\n",
      "Found 30 DICOM file(s)\n",
      "Convert 30 DICOM as TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936/PCAMPMRI-00007_1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936 (512x512x30x1)\n",
      "Conversion required 0.809656 seconds (0.809476 for core code).\n",
      "\n",
      "Running 'plastimatch convert' with the specified arguments:\n",
      "  --input TEST/idc_image_data/dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936/qin_prostate_repeatability/PCAMPMRI-00007/1.3.6.1.4.1.14519.5.2.1.3671.4754.962865348146140991373362412648/MR_1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936\n",
      "  --output-img TEST/idc_image_data/nrrd/1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936/1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936.nrrd\n",
      "... Done.\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936/2.nii.gz\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936/1.nii.gz\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936/3.nii.gz\n",
      "SegmentAlgorithmName : MANUAL\n",
      "label_values: [3, 1]\n",
      "label_names: ['Prostate', 'Peripheral zone of the prostate']\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:No valid config parameter, using defaults: {'minimumROIDimensions': 2, 'minimumROISize': None, 'normalize': False, 'normalizeScale': 1, 'removeOutliers': None, 'resampledPixelSpacing': None, 'interpolator': 'sitkBSpline', 'preCrop': False, 'padDistance': 5, 'distances': [1], 'force2D': False, 'force2Ddimension': 0, 'resegmentRange': None, 'label': 1, 'additionalInfo': True}\n",
      "INFO:radiomics.featureextractor:Enabled image types: {'Original': {}}\n",
      "INFO:radiomics.featureextractor:Enabled features: {'firstorder': [], 'glcm': [], 'gldm': [], 'glrlm': [], 'glszm': [], 'ngtdm': [], 'shape': []}\n",
      "INFO:radiomics.featureextractor:Applying custom setting overrides: {'correctMask': True, 'geometryTolerance': 0.0001, 'label': 3}\n",
      "INFO:radiomics.featureextractor:Calculating features with label: 3\n",
      "INFO:radiomics.featureextractor:Loading image and mask\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ct nifti path : /content/TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936/PCAMPMRI-00007_1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936.nii.gz\n",
      " mask path : /content/TEST/seg_objects/nii_resampled_renamed/1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936/Prostate.nii.gz\n",
      "labelValue : 3\n",
      "label_name : Prostate\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:Computing shape\n",
      "Feature Compactness1 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness1 is deprecated, use with caution!\n",
      "Feature Compactness2 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness2 is deprecated, use with caution!\n",
      "Feature SphericalDisproportion is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature SphericalDisproportion is deprecated, use with caution!\n",
      "INFO:radiomics.featureextractor:Adding image type \"Original\" with custom settings: {}\n",
      "INFO:radiomics.featureextractor:Calculating features for original image\n",
      "INFO:radiomics.featureextractor:No valid config parameter, using defaults: {'minimumROIDimensions': 2, 'minimumROISize': None, 'normalize': False, 'normalizeScale': 1, 'removeOutliers': None, 'resampledPixelSpacing': None, 'interpolator': 'sitkBSpline', 'preCrop': False, 'padDistance': 5, 'distances': [1], 'force2D': False, 'force2Ddimension': 0, 'resegmentRange': None, 'label': 1, 'additionalInfo': True}\n",
      "INFO:radiomics.featureextractor:Enabled image types: {'Original': {}}\n",
      "INFO:radiomics.featureextractor:Enabled features: {'firstorder': [], 'glcm': [], 'gldm': [], 'glrlm': [], 'glszm': [], 'ngtdm': [], 'shape': []}\n",
      "INFO:radiomics.featureextractor:Applying custom setting overrides: {'correctMask': True, 'geometryTolerance': 0.0001, 'label': 1}\n",
      "INFO:radiomics.featureextractor:Calculating features with label: 1\n",
      "INFO:radiomics.featureextractor:Loading image and mask\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ct nifti path : /content/TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936/PCAMPMRI-00007_1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936.nii.gz\n",
      " mask path : /content/TEST/seg_objects/nii_resampled_renamed/1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936/Peripheral zone of the prostate.nii.gz\n",
      "labelValue : 1\n",
      "label_name : Peripheral zone of the prostate\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:Computing shape\n",
      "Feature Compactness1 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness1 is deprecated, use with caution!\n",
      "Feature Compactness2 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness2 is deprecated, use with caution!\n",
      "Feature SphericalDisproportion is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature SphericalDisproportion is deprecated, use with caution!\n",
      "INFO:radiomics.featureextractor:Adding image type \"Original\" with custom settings: {}\n",
      "INFO:radiomics.featureextractor:Calculating features for original image\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "created df_features\n",
      "segment_id: 0\n",
      "ReferencedSegment: 3\n",
      "FindingSite: Prostate\n",
      "segment_id: 1\n",
      "ReferencedSegment: 1\n",
      "FindingSite: Peripheral zone of the prostate\n",
      "created SR json for shape features\n",
      "wrote out json for shape features\n",
      "inputImageLibraryDirectory: /content/TEST/idc_image_data/dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936/qin_prostate_repeatability/PCAMPMRI-00007/1.3.6.1.4.1.14519.5.2.1.3671.4754.962865348146140991373362412648/MR_1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936\n",
      "outputDICOM: /content/TEST/seg_objects/dicom_sr/1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936/1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936_SR.dcm\n",
      "inputCompositeContextDirectory: d148919e-2c32-4501-9315-3f55c2ba31a5.dcm\n",
      "inputMetadata_json: /content/TEST/seg_objects/dicom_sr_json/1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936/1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936_SR.json\n",
      "dcmqi repository URL: https://github.com/QIICR/dcmqi revision: d88b025 tag: v1.3.4\n",
      "Total measurement groups: 2\n",
      "Adding to compositeContext: /content/TEST/seg_unzip/combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.330807155674174304012309699936/d148919e-2c32-4501-9315-3f55c2ba31a5.dcm\n",
      "Composite Context has been initialized\n",
      "SR saved!\n",
      "wrote out SR for shape features\n",
      "\n",
      "\n",
      "serieUID image referenced : 1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857\n",
      "dcmqi repository URL: https://github.com/QIICR/dcmqi revision: d88b025 tag: v1.3.4\n",
      "Loading DICOM SEG file TEST/seg_unzip/combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857/8ae1177f-8173-47d8-a25f-0a182cdd4162.dcm\n",
      "Row direction: 0.998814 0.0486132 -0.0027702\n",
      "Col direction: 0.0469094 -0.975942 -0.212926\n",
      "Z direction: -0.0130546 0.212543 -0.977064\n",
      "Total frames: 25\n",
      "Total frames with unique IPP: 11\n",
      "Total overlapping frames: 10\n",
      "Origin: [-96.4709, 50.9827, 1.85367]\n",
      "Slice extent: 30\n",
      "Slice spacing: 3\n",
      "Will not merge segments: Splitting segments into 4 groups\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857/1.nii.gz ... done\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857/2.nii.gz ... done\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857/3.nii.gz ... done\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857/4.nii.gz ... done\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Downloading data: 100%|██████████| 15.8M/15.8M [00:01<00:00, 15.7MB/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Chris Rorden's dcm2niiX version v1.0.20220505  GCC11.4.0 x86-64 (64-bit Linux)\n",
      "Found 30 DICOM file(s)\n",
      "Convert 30 DICOM as TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857/PCAMPMRI-00002_1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857 (512x512x30x1)\n",
      "Conversion required 1.007435 seconds (1.007296 for core code).\n",
      "\n",
      "Running 'plastimatch convert' with the specified arguments:\n",
      "  --input TEST/idc_image_data/dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857/qin_prostate_repeatability/PCAMPMRI-00002/1.3.6.1.4.1.14519.5.2.1.3671.4754.568383070573576760578239627478/MR_1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857\n",
      "  --output-img TEST/idc_image_data/nrrd/1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857/1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857.nrrd\n",
      "... Done.\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857/2.nii.gz\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857/1.nii.gz\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857/4.nii.gz\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857/3.nii.gz\n",
      "SegmentAlgorithmName : MANUAL\n",
      "label_values: [4, 2]\n",
      "label_names: ['Prostate', 'Peripheral zone of the prostate']\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:No valid config parameter, using defaults: {'minimumROIDimensions': 2, 'minimumROISize': None, 'normalize': False, 'normalizeScale': 1, 'removeOutliers': None, 'resampledPixelSpacing': None, 'interpolator': 'sitkBSpline', 'preCrop': False, 'padDistance': 5, 'distances': [1], 'force2D': False, 'force2Ddimension': 0, 'resegmentRange': None, 'label': 1, 'additionalInfo': True}\n",
      "INFO:radiomics.featureextractor:Enabled image types: {'Original': {}}\n",
      "INFO:radiomics.featureextractor:Enabled features: {'firstorder': [], 'glcm': [], 'gldm': [], 'glrlm': [], 'glszm': [], 'ngtdm': [], 'shape': []}\n",
      "INFO:radiomics.featureextractor:Applying custom setting overrides: {'correctMask': True, 'geometryTolerance': 0.0001, 'label': 4}\n",
      "INFO:radiomics.featureextractor:Calculating features with label: 4\n",
      "INFO:radiomics.featureextractor:Loading image and mask\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ct nifti path : /content/TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857/PCAMPMRI-00002_1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857.nii.gz\n",
      " mask path : /content/TEST/seg_objects/nii_resampled_renamed/1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857/Prostate.nii.gz\n",
      "labelValue : 4\n",
      "label_name : Prostate\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:Computing shape\n",
      "Feature Compactness1 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness1 is deprecated, use with caution!\n",
      "Feature Compactness2 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness2 is deprecated, use with caution!\n",
      "Feature SphericalDisproportion is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature SphericalDisproportion is deprecated, use with caution!\n",
      "INFO:radiomics.featureextractor:Adding image type \"Original\" with custom settings: {}\n",
      "INFO:radiomics.featureextractor:Calculating features for original image\n",
      "INFO:radiomics.featureextractor:No valid config parameter, using defaults: {'minimumROIDimensions': 2, 'minimumROISize': None, 'normalize': False, 'normalizeScale': 1, 'removeOutliers': None, 'resampledPixelSpacing': None, 'interpolator': 'sitkBSpline', 'preCrop': False, 'padDistance': 5, 'distances': [1], 'force2D': False, 'force2Ddimension': 0, 'resegmentRange': None, 'label': 1, 'additionalInfo': True}\n",
      "INFO:radiomics.featureextractor:Enabled image types: {'Original': {}}\n",
      "INFO:radiomics.featureextractor:Enabled features: {'firstorder': [], 'glcm': [], 'gldm': [], 'glrlm': [], 'glszm': [], 'ngtdm': [], 'shape': []}\n",
      "INFO:radiomics.featureextractor:Applying custom setting overrides: {'correctMask': True, 'geometryTolerance': 0.0001, 'label': 2}\n",
      "INFO:radiomics.featureextractor:Calculating features with label: 2\n",
      "INFO:radiomics.featureextractor:Loading image and mask\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ct nifti path : /content/TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857/PCAMPMRI-00002_1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857.nii.gz\n",
      " mask path : /content/TEST/seg_objects/nii_resampled_renamed/1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857/Peripheral zone of the prostate.nii.gz\n",
      "labelValue : 2\n",
      "label_name : Peripheral zone of the prostate\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:Computing shape\n",
      "Feature Compactness1 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness1 is deprecated, use with caution!\n",
      "Feature Compactness2 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness2 is deprecated, use with caution!\n",
      "Feature SphericalDisproportion is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature SphericalDisproportion is deprecated, use with caution!\n",
      "INFO:radiomics.featureextractor:Adding image type \"Original\" with custom settings: {}\n",
      "INFO:radiomics.featureextractor:Calculating features for original image\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "created df_features\n",
      "segment_id: 0\n",
      "ReferencedSegment: 4\n",
      "FindingSite: Prostate\n",
      "segment_id: 1\n",
      "ReferencedSegment: 2\n",
      "FindingSite: Peripheral zone of the prostate\n",
      "created SR json for shape features\n",
      "wrote out json for shape features\n",
      "inputImageLibraryDirectory: /content/TEST/idc_image_data/dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857/qin_prostate_repeatability/PCAMPMRI-00002/1.3.6.1.4.1.14519.5.2.1.3671.4754.568383070573576760578239627478/MR_1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857\n",
      "outputDICOM: /content/TEST/seg_objects/dicom_sr/1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857/1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857_SR.dcm\n",
      "inputCompositeContextDirectory: 8ae1177f-8173-47d8-a25f-0a182cdd4162.dcm\n",
      "inputMetadata_json: /content/TEST/seg_objects/dicom_sr_json/1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857/1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857_SR.json\n",
      "dcmqi repository URL: https://github.com/QIICR/dcmqi revision: d88b025 tag: v1.3.4\n",
      "Total measurement groups: 2\n",
      "Adding to compositeContext: /content/TEST/seg_unzip/combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.322350301601580056579486694857/8ae1177f-8173-47d8-a25f-0a182cdd4162.dcm\n",
      "Composite Context has been initialized\n",
      "SR saved!\n",
      "wrote out SR for shape features\n",
      "\n",
      "\n",
      "serieUID image referenced : 1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017\n",
      "dcmqi repository URL: https://github.com/QIICR/dcmqi revision: d88b025 tag: v1.3.4\n",
      "Loading DICOM SEG file TEST/seg_unzip/combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017/38636f83-f883-40be-8036-19b9bdb94911.dcm\n",
      "Row direction: 0.998914 0.00555077 -0.0462661\n",
      "Col direction: -0.00313966 -0.982606 -0.185675\n",
      "Z direction: -0.046492 0.185619 -0.981521\n",
      "Total frames: 23\n",
      "Total frames with unique IPP: 11\n",
      "Total overlapping frames: 11\n",
      "Origin: [-88.036, 58.4, 18.9914]\n",
      "Slice extent: 30\n",
      "Slice spacing: 3\n",
      "Will not merge segments: Splitting segments into 3 groups\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017/1.nii.gz ... done\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017/2.nii.gz ... done\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017/3.nii.gz ... done\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Downloading data: 100%|█████████▉| 16.9M/16.9M [00:01<00:00, 16.8MB/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Chris Rorden's dcm2niiX version v1.0.20220505  GCC11.4.0 x86-64 (64-bit Linux)\n",
      "Found 32 DICOM file(s)\n",
      "Convert 32 DICOM as TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017/PCAMPMRI-00004_1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017 (512x512x32x1)\n",
      "Conversion required 0.864532 seconds (0.864403 for core code).\n",
      "\n",
      "Running 'plastimatch convert' with the specified arguments:\n",
      "  --input TEST/idc_image_data/dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017/qin_prostate_repeatability/PCAMPMRI-00004/1.3.6.1.4.1.14519.5.2.1.3671.4754.204078048920967920419177848890/MR_1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017\n",
      "  --output-img TEST/idc_image_data/nrrd/1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017/1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017.nrrd\n",
      "... Done.\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017/2.nii.gz\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017/1.nii.gz\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017/3.nii.gz\n",
      "SegmentAlgorithmName : MANUAL\n",
      "label_values: [3, 1]\n",
      "label_names: ['Prostate', 'Peripheral zone of the prostate']\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:No valid config parameter, using defaults: {'minimumROIDimensions': 2, 'minimumROISize': None, 'normalize': False, 'normalizeScale': 1, 'removeOutliers': None, 'resampledPixelSpacing': None, 'interpolator': 'sitkBSpline', 'preCrop': False, 'padDistance': 5, 'distances': [1], 'force2D': False, 'force2Ddimension': 0, 'resegmentRange': None, 'label': 1, 'additionalInfo': True}\n",
      "INFO:radiomics.featureextractor:Enabled image types: {'Original': {}}\n",
      "INFO:radiomics.featureextractor:Enabled features: {'firstorder': [], 'glcm': [], 'gldm': [], 'glrlm': [], 'glszm': [], 'ngtdm': [], 'shape': []}\n",
      "INFO:radiomics.featureextractor:Applying custom setting overrides: {'correctMask': True, 'geometryTolerance': 0.0001, 'label': 3}\n",
      "INFO:radiomics.featureextractor:Calculating features with label: 3\n",
      "INFO:radiomics.featureextractor:Loading image and mask\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ct nifti path : /content/TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017/PCAMPMRI-00004_1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017.nii.gz\n",
      " mask path : /content/TEST/seg_objects/nii_resampled_renamed/1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017/Prostate.nii.gz\n",
      "labelValue : 3\n",
      "label_name : Prostate\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:Computing shape\n",
      "Feature Compactness1 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness1 is deprecated, use with caution!\n",
      "Feature Compactness2 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness2 is deprecated, use with caution!\n",
      "Feature SphericalDisproportion is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature SphericalDisproportion is deprecated, use with caution!\n",
      "INFO:radiomics.featureextractor:Adding image type \"Original\" with custom settings: {}\n",
      "INFO:radiomics.featureextractor:Calculating features for original image\n",
      "INFO:radiomics.featureextractor:No valid config parameter, using defaults: {'minimumROIDimensions': 2, 'minimumROISize': None, 'normalize': False, 'normalizeScale': 1, 'removeOutliers': None, 'resampledPixelSpacing': None, 'interpolator': 'sitkBSpline', 'preCrop': False, 'padDistance': 5, 'distances': [1], 'force2D': False, 'force2Ddimension': 0, 'resegmentRange': None, 'label': 1, 'additionalInfo': True}\n",
      "INFO:radiomics.featureextractor:Enabled image types: {'Original': {}}\n",
      "INFO:radiomics.featureextractor:Enabled features: {'firstorder': [], 'glcm': [], 'gldm': [], 'glrlm': [], 'glszm': [], 'ngtdm': [], 'shape': []}\n",
      "INFO:radiomics.featureextractor:Applying custom setting overrides: {'correctMask': True, 'geometryTolerance': 0.0001, 'label': 1}\n",
      "INFO:radiomics.featureextractor:Calculating features with label: 1\n",
      "INFO:radiomics.featureextractor:Loading image and mask\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ct nifti path : /content/TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017/PCAMPMRI-00004_1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017.nii.gz\n",
      " mask path : /content/TEST/seg_objects/nii_resampled_renamed/1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017/Peripheral zone of the prostate.nii.gz\n",
      "labelValue : 1\n",
      "label_name : Peripheral zone of the prostate\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:Computing shape\n",
      "Feature Compactness1 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness1 is deprecated, use with caution!\n",
      "Feature Compactness2 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness2 is deprecated, use with caution!\n",
      "Feature SphericalDisproportion is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature SphericalDisproportion is deprecated, use with caution!\n",
      "INFO:radiomics.featureextractor:Adding image type \"Original\" with custom settings: {}\n",
      "INFO:radiomics.featureextractor:Calculating features for original image\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "created df_features\n",
      "segment_id: 0\n",
      "ReferencedSegment: 3\n",
      "FindingSite: Prostate\n",
      "segment_id: 1\n",
      "ReferencedSegment: 1\n",
      "FindingSite: Peripheral zone of the prostate\n",
      "created SR json for shape features\n",
      "wrote out json for shape features\n",
      "inputImageLibraryDirectory: /content/TEST/idc_image_data/dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017/qin_prostate_repeatability/PCAMPMRI-00004/1.3.6.1.4.1.14519.5.2.1.3671.4754.204078048920967920419177848890/MR_1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017\n",
      "outputDICOM: /content/TEST/seg_objects/dicom_sr/1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017/1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017_SR.dcm\n",
      "inputCompositeContextDirectory: 38636f83-f883-40be-8036-19b9bdb94911.dcm\n",
      "inputMetadata_json: /content/TEST/seg_objects/dicom_sr_json/1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017/1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017_SR.json\n",
      "dcmqi repository URL: https://github.com/QIICR/dcmqi revision: d88b025 tag: v1.3.4\n",
      "Total measurement groups: 2\n",
      "Adding to compositeContext: /content/TEST/seg_unzip/combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.242851658965322332393259472017/38636f83-f883-40be-8036-19b9bdb94911.dcm\n",
      "Composite Context has been initialized\n",
      "SR saved!\n",
      "wrote out SR for shape features\n",
      "\n",
      "\n",
      "serieUID image referenced : 1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127\n",
      "dcmqi repository URL: https://github.com/QIICR/dcmqi revision: d88b025 tag: v1.3.4\n",
      "Loading DICOM SEG file TEST/seg_unzip/combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127/6d3d17e8-e0cc-40d5-8c9d-6fd4357599dc.dcm\n",
      "Row direction: 0.999581 0.0271354 -0.010107\n",
      "Col direction: 0.0244944 -0.978525 -0.204668\n",
      "Z direction: -0.0154437 0.204335 -0.978779\n",
      "Total frames: 20\n",
      "Total frames with unique IPP: 10\n",
      "Total overlapping frames: 9\n",
      "Origin: [-111.731, 98.0057, -42.4853]\n",
      "Slice extent: 31.5\n",
      "Slice spacing: 3.5\n",
      "Will not merge segments: Splitting segments into 3 groups\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127/1.nii.gz ... done\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127/2.nii.gz ... done\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127/3.nii.gz ... done\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Downloading data: 100%|██████████| 14.8M/14.8M [00:01<00:00, 14.7MB/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Chris Rorden's dcm2niiX version v1.0.20220505  GCC11.4.0 x86-64 (64-bit Linux)\n",
      "Found 28 DICOM file(s)\n",
      "Convert 28 DICOM as TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127/PCAMPMRI-00014_1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127 (512x512x28x1)\n",
      "Conversion required 0.928520 seconds (0.928287 for core code).\n",
      "\n",
      "Running 'plastimatch convert' with the specified arguments:\n",
      "  --input TEST/idc_image_data/dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127/qin_prostate_repeatability/PCAMPMRI-00014/1.3.6.1.4.1.14519.5.2.1.3671.4754.288453744990673175783381845880/MR_1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127\n",
      "  --output-img TEST/idc_image_data/nrrd/1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127/1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127.nrrd\n",
      "... Done.\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127/2.nii.gz\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127/1.nii.gz\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127/3.nii.gz\n",
      "SegmentAlgorithmName : MANUAL\n",
      "label_values: [3, 2]\n",
      "label_names: ['Prostate', 'Peripheral zone of the prostate']\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:No valid config parameter, using defaults: {'minimumROIDimensions': 2, 'minimumROISize': None, 'normalize': False, 'normalizeScale': 1, 'removeOutliers': None, 'resampledPixelSpacing': None, 'interpolator': 'sitkBSpline', 'preCrop': False, 'padDistance': 5, 'distances': [1], 'force2D': False, 'force2Ddimension': 0, 'resegmentRange': None, 'label': 1, 'additionalInfo': True}\n",
      "INFO:radiomics.featureextractor:Enabled image types: {'Original': {}}\n",
      "INFO:radiomics.featureextractor:Enabled features: {'firstorder': [], 'glcm': [], 'gldm': [], 'glrlm': [], 'glszm': [], 'ngtdm': [], 'shape': []}\n",
      "INFO:radiomics.featureextractor:Applying custom setting overrides: {'correctMask': True, 'geometryTolerance': 0.0001, 'label': 3}\n",
      "INFO:radiomics.featureextractor:Calculating features with label: 3\n",
      "INFO:radiomics.featureextractor:Loading image and mask\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ct nifti path : /content/TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127/PCAMPMRI-00014_1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127.nii.gz\n",
      " mask path : /content/TEST/seg_objects/nii_resampled_renamed/1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127/Prostate.nii.gz\n",
      "labelValue : 3\n",
      "label_name : Prostate\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:Computing shape\n",
      "Feature Compactness1 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness1 is deprecated, use with caution!\n",
      "Feature Compactness2 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness2 is deprecated, use with caution!\n",
      "Feature SphericalDisproportion is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature SphericalDisproportion is deprecated, use with caution!\n",
      "INFO:radiomics.featureextractor:Adding image type \"Original\" with custom settings: {}\n",
      "INFO:radiomics.featureextractor:Calculating features for original image\n",
      "INFO:radiomics.featureextractor:No valid config parameter, using defaults: {'minimumROIDimensions': 2, 'minimumROISize': None, 'normalize': False, 'normalizeScale': 1, 'removeOutliers': None, 'resampledPixelSpacing': None, 'interpolator': 'sitkBSpline', 'preCrop': False, 'padDistance': 5, 'distances': [1], 'force2D': False, 'force2Ddimension': 0, 'resegmentRange': None, 'label': 1, 'additionalInfo': True}\n",
      "INFO:radiomics.featureextractor:Enabled image types: {'Original': {}}\n",
      "INFO:radiomics.featureextractor:Enabled features: {'firstorder': [], 'glcm': [], 'gldm': [], 'glrlm': [], 'glszm': [], 'ngtdm': [], 'shape': []}\n",
      "INFO:radiomics.featureextractor:Applying custom setting overrides: {'correctMask': True, 'geometryTolerance': 0.0001, 'label': 2}\n",
      "INFO:radiomics.featureextractor:Calculating features with label: 2\n",
      "INFO:radiomics.featureextractor:Loading image and mask\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ct nifti path : /content/TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127/PCAMPMRI-00014_1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127.nii.gz\n",
      " mask path : /content/TEST/seg_objects/nii_resampled_renamed/1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127/Peripheral zone of the prostate.nii.gz\n",
      "labelValue : 2\n",
      "label_name : Peripheral zone of the prostate\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:Computing shape\n",
      "Feature Compactness1 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness1 is deprecated, use with caution!\n",
      "Feature Compactness2 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness2 is deprecated, use with caution!\n",
      "Feature SphericalDisproportion is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature SphericalDisproportion is deprecated, use with caution!\n",
      "INFO:radiomics.featureextractor:Adding image type \"Original\" with custom settings: {}\n",
      "INFO:radiomics.featureextractor:Calculating features for original image\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "created df_features\n",
      "segment_id: 0\n",
      "ReferencedSegment: 3\n",
      "FindingSite: Prostate\n",
      "segment_id: 1\n",
      "ReferencedSegment: 2\n",
      "FindingSite: Peripheral zone of the prostate\n",
      "created SR json for shape features\n",
      "wrote out json for shape features\n",
      "inputImageLibraryDirectory: /content/TEST/idc_image_data/dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127/qin_prostate_repeatability/PCAMPMRI-00014/1.3.6.1.4.1.14519.5.2.1.3671.4754.288453744990673175783381845880/MR_1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127\n",
      "outputDICOM: /content/TEST/seg_objects/dicom_sr/1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127/1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127_SR.dcm\n",
      "inputCompositeContextDirectory: 6d3d17e8-e0cc-40d5-8c9d-6fd4357599dc.dcm\n",
      "inputMetadata_json: /content/TEST/seg_objects/dicom_sr_json/1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127/1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127_SR.json\n",
      "dcmqi repository URL: https://github.com/QIICR/dcmqi revision: d88b025 tag: v1.3.4\n",
      "Total measurement groups: 2\n",
      "Adding to compositeContext: /content/TEST/seg_unzip/combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.654327272206188613770270554127/6d3d17e8-e0cc-40d5-8c9d-6fd4357599dc.dcm\n",
      "Composite Context has been initialized\n",
      "SR saved!\n",
      "wrote out SR for shape features\n",
      "\n",
      "\n",
      "serieUID image referenced : 1.3.6.1.4.1.14519.5.2.1.3671.4754.165941479363091869002475812419\n",
      "dcmqi repository URL: https://github.com/QIICR/dcmqi revision: d88b025 tag: v1.3.4\n",
      "Loading DICOM SEG file TEST/seg_unzip/combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.165941479363091869002475812419/5f5f0840-3dee-4fb4-bab7-419cb2ecb8ad.dcm\n",
      "Row direction: 0.999896 -0.00808328 -0.0119669\n",
      "Col direction: -0.0120285 -0.924739 -0.380412\n",
      "Z direction: -0.00799125 0.380516 -0.92474\n",
      "Total frames: 30\n",
      "Total frames with unique IPP: 13\n",
      "Total overlapping frames: 13\n",
      "Origin: [-73.4399, 26.5429, 71.6239]\n",
      "Slice extent: 36.0018\n",
      "Slice spacing: 3.00015\n",
      "Will not merge segments: Splitting segments into 3 groups\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.165941479363091869002475812419/1.nii.gz ... done\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.165941479363091869002475812419/2.nii.gz ... done\n",
      "Writing itk image to TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.165941479363091869002475812419/3.nii.gz ... done\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Downloading data: 100%|██████████| 15.8M/15.8M [00:01<00:00, 15.7MB/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Chris Rorden's dcm2niiX version v1.0.20220505  GCC11.4.0 x86-64 (64-bit Linux)\n",
      "Found 30 DICOM file(s)\n",
      "Convert 30 DICOM as TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.165941479363091869002475812419/PCAMPMRI-00003_1.3.6.1.4.1.14519.5.2.1.3671.4754.165941479363091869002475812419 (512x512x30x1)\n",
      "Conversion required 0.866236 seconds (0.866008 for core code).\n",
      "\n",
      "Running 'plastimatch convert' with the specified arguments:\n",
      "  --input TEST/idc_image_data/dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.165941479363091869002475812419/qin_prostate_repeatability/PCAMPMRI-00003/1.3.6.1.4.1.14519.5.2.1.3671.4754.162322077241419864654545266845/MR_1.3.6.1.4.1.14519.5.2.1.3671.4754.165941479363091869002475812419\n",
      "  --output-img TEST/idc_image_data/nrrd/1.3.6.1.4.1.14519.5.2.1.3671.4754.165941479363091869002475812419/1.3.6.1.4.1.14519.5.2.1.3671.4754.165941479363091869002475812419.nrrd\n",
      "... Done.\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.165941479363091869002475812419/2.nii.gz\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.165941479363091869002475812419/1.nii.gz\n",
      "TEST/seg_objects/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.165941479363091869002475812419/3.nii.gz\n",
      "SegmentAlgorithmName : MANUAL\n",
      "label_values: [3, 1]\n",
      "label_names: ['Prostate', 'Peripheral zone of the prostate']\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:No valid config parameter, using defaults: {'minimumROIDimensions': 2, 'minimumROISize': None, 'normalize': False, 'normalizeScale': 1, 'removeOutliers': None, 'resampledPixelSpacing': None, 'interpolator': 'sitkBSpline', 'preCrop': False, 'padDistance': 5, 'distances': [1], 'force2D': False, 'force2Ddimension': 0, 'resegmentRange': None, 'label': 1, 'additionalInfo': True}\n",
      "INFO:radiomics.featureextractor:Enabled image types: {'Original': {}}\n",
      "INFO:radiomics.featureextractor:Enabled features: {'firstorder': [], 'glcm': [], 'gldm': [], 'glrlm': [], 'glszm': [], 'ngtdm': [], 'shape': []}\n",
      "INFO:radiomics.featureextractor:Applying custom setting overrides: {'correctMask': True, 'geometryTolerance': 0.0001, 'label': 3}\n",
      "INFO:radiomics.featureextractor:Calculating features with label: 3\n",
      "INFO:radiomics.featureextractor:Loading image and mask\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ct nifti path : /content/TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.165941479363091869002475812419/PCAMPMRI-00003_1.3.6.1.4.1.14519.5.2.1.3671.4754.165941479363091869002475812419.nii.gz\n",
      " mask path : /content/TEST/seg_objects/nii_resampled_renamed/1.3.6.1.4.1.14519.5.2.1.3671.4754.165941479363091869002475812419/Prostate.nii.gz\n",
      "labelValue : 3\n",
      "label_name : Prostate\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:Computing shape\n",
      "Feature Compactness1 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness1 is deprecated, use with caution!\n",
      "Feature Compactness2 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness2 is deprecated, use with caution!\n",
      "Feature SphericalDisproportion is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature SphericalDisproportion is deprecated, use with caution!\n",
      "INFO:radiomics.featureextractor:Adding image type \"Original\" with custom settings: {}\n",
      "INFO:radiomics.featureextractor:Calculating features for original image\n",
      "INFO:radiomics.featureextractor:No valid config parameter, using defaults: {'minimumROIDimensions': 2, 'minimumROISize': None, 'normalize': False, 'normalizeScale': 1, 'removeOutliers': None, 'resampledPixelSpacing': None, 'interpolator': 'sitkBSpline', 'preCrop': False, 'padDistance': 5, 'distances': [1], 'force2D': False, 'force2Ddimension': 0, 'resegmentRange': None, 'label': 1, 'additionalInfo': True}\n",
      "INFO:radiomics.featureextractor:Enabled image types: {'Original': {}}\n",
      "INFO:radiomics.featureextractor:Enabled features: {'firstorder': [], 'glcm': [], 'gldm': [], 'glrlm': [], 'glszm': [], 'ngtdm': [], 'shape': []}\n",
      "INFO:radiomics.featureextractor:Applying custom setting overrides: {'correctMask': True, 'geometryTolerance': 0.0001, 'label': 1}\n",
      "INFO:radiomics.featureextractor:Calculating features with label: 1\n",
      "INFO:radiomics.featureextractor:Loading image and mask\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ct nifti path : /content/TEST/idc_image_data/nii/1.3.6.1.4.1.14519.5.2.1.3671.4754.165941479363091869002475812419/PCAMPMRI-00003_1.3.6.1.4.1.14519.5.2.1.3671.4754.165941479363091869002475812419.nii.gz\n",
      " mask path : /content/TEST/seg_objects/nii_resampled_renamed/1.3.6.1.4.1.14519.5.2.1.3671.4754.165941479363091869002475812419/Peripheral zone of the prostate.nii.gz\n",
      "labelValue : 1\n",
      "label_name : Peripheral zone of the prostate\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:radiomics.featureextractor:Computing shape\n",
      "Feature Compactness1 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness1 is deprecated, use with caution!\n",
      "Feature Compactness2 is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature Compactness2 is deprecated, use with caution!\n",
      "Feature SphericalDisproportion is deprecated, use with caution!\n",
      "WARNING:radiomics.shape:Feature SphericalDisproportion is deprecated, use with caution!\n",
      "INFO:radiomics.featureextractor:Adding image type \"Original\" with custom settings: {}\n",
      "INFO:radiomics.featureextractor:Calculating features for original image\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "created df_features\n",
      "segment_id: 0\n",
      "ReferencedSegment: 3\n",
      "FindingSite: Prostate\n",
      "segment_id: 1\n",
      "ReferencedSegment: 1\n",
      "FindingSite: Peripheral zone of the prostate\n",
      "created SR json for shape features\n",
      "wrote out json for shape features\n",
      "inputImageLibraryDirectory: /content/TEST/idc_image_data/dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.165941479363091869002475812419/qin_prostate_repeatability/PCAMPMRI-00003/1.3.6.1.4.1.14519.5.2.1.3671.4754.162322077241419864654545266845/MR_1.3.6.1.4.1.14519.5.2.1.3671.4754.165941479363091869002475812419\n",
      "outputDICOM: /content/TEST/seg_objects/dicom_sr/1.3.6.1.4.1.14519.5.2.1.3671.4754.165941479363091869002475812419/1.3.6.1.4.1.14519.5.2.1.3671.4754.165941479363091869002475812419_SR.dcm\n",
      "inputCompositeContextDirectory: 5f5f0840-3dee-4fb4-bab7-419cb2ecb8ad.dcm\n",
      "inputMetadata_json: /content/TEST/seg_objects/dicom_sr_json/1.3.6.1.4.1.14519.5.2.1.3671.4754.165941479363091869002475812419/1.3.6.1.4.1.14519.5.2.1.3671.4754.165941479363091869002475812419_SR.json\n",
      "dcmqi repository URL: https://github.com/QIICR/dcmqi revision: d88b025 tag: v1.3.4\n",
      "Total measurement groups: 2\n",
      "Adding to compositeContext: /content/TEST/seg_unzip/combination_archive/seg_prostate_gen/output_nii_combined_resampled_dicom/1.3.6.1.4.1.14519.5.2.1.3671.4754.165941479363091869002475812419/5f5f0840-3dee-4fb4-bab7-419cb2ecb8ad.dcm\n",
      "Composite Context has been initialized\n",
      "SR saved!\n",
      "wrote out SR for shape features\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "for serieUID_path in seg_dicom_objects:\n",
    "\ttry:\n",
    "\t\t#convert AI SEG DICOM object to NIFTI SEG\n",
    "\t\tserieUID_image = str(pydicom.dcmread(serieUID_path).ReferencedSeriesSequence[0].SeriesInstanceUID)\n",
    "\t\tprint(f\"serieUID image referenced : {serieUID_image}\")\n",
    "\t\t!mkdir -p {os.path.join(seg_nii_folder, serieUID_image)}\n",
    "\t\tassert os.path.exists(serieUID_path)\n",
    "\t\t!segimage2itkimage --inputDICOM $serieUID_path \\\n",
    "\t\t--outputDirectory {os.path.join(seg_nii_folder, serieUID_image)} --outputType nii\n",
    "\t\t#download IDC reference image for downstream resampling\n",
    "\t\tout_image_dicom = os.path.join(IDC_IMAGE_DICOM, serieUID_image)\n",
    "\t\t!rm -rf $out_image_dicom\n",
    "\t\t!mkdir -p $out_image_dicom\n",
    "\t\tclient.download_from_selection(seriesInstanceUID=list([serieUID_image]),\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tdownloadDir=out_image_dicom,)\n",
    "\t\t#convert idc reference image to NIFTI/NRRD\n",
    "\t\tout_image_nii = os.path.join(IDC_IMAGE_NII, serieUID_image)\n",
    "\t\tout_image_nrrd = os.path.join(IDC_IMAGE_NRRD, serieUID_image)\n",
    "\t\t##nii\n",
    "\t\t!rm -rf $out_image_nii\n",
    "\t\t!mkdir -p $out_image_nii\n",
    "\t\t##nrrd\n",
    "\t\t!rm -rf $out_image_nrrd\n",
    "\t\t!mkdir -p $out_image_nrrd\n",
    "\t\t#convert image dicom to nii\n",
    "\t\t!dcm2niix -z y -m y -f %i_{serieUID_image} -o $out_image_nii $out_image_dicom\n",
    "\t\tif len(glob.glob(os.path.join(out_image_nii, \"*.nii.gz\"))) > 1:\n",
    "\t\t\t!rm -rf $out_image_nii\n",
    "\t\t\t!mkdir -p $out_image_nii\n",
    "\t\t\tconvert_nii_args = {\"input\":\"/\".join(glob.glob(os.path.join(out_image_dicom, \"**\", \"*.dcm\"), recursive=True)[0].split(\"/\")[:-1]),\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\"output-img\": os.path.join(out_image_nii, f\"{serieUID_image}.nii.gz\")}\n",
    "\t\t\tpypla.convert(verbose=True, **convert_nii_args)\n",
    "\t\t#convert image dicom to nrrd\n",
    "\t\tout_image_dicom_for_nrrd = \"/\".join(glob.glob(os.path.join(out_image_dicom, \"**\", \"*.dcm\"), recursive=True)[0].split(\"/\")[:-1])\n",
    "\t\tout_img_nrrd_file_path = os.path.join(out_image_nrrd, f\"{serieUID_image}.nrrd\")\n",
    "\t\tconvert_nrrd_args = {\"input\":out_image_dicom_for_nrrd, \"output-img\":out_img_nrrd_file_path}\n",
    "\t\tpypla.convert(verbose=True, **convert_nrrd_args)\n",
    "\t\tref_image_nii_path = glob.glob(os.path.join(out_image_nii, '*.nii.gz'))[0]\n",
    "\t\tref_image_nrrd_path = glob.glob(os.path.join(out_image_nrrd, '*.nrrd'))[0]\n",
    "\t\t#resample AI NIFTI SEG object to the reference image space\n",
    "\t\toutput_serie_resampled = os.path.join(seg_nii_resampled_folder, serieUID_image)\n",
    "\t\t!rm -rf $output_serie_resampled\n",
    "\t\t!mkdir -p $output_serie_resampled\n",
    "\t\t#define resampling scheme\n",
    "\t\tif res_scheme_format == \"nrrd\":\n",
    "\t\t\tref_image_path = ref_image_nrrd_path\n",
    "\t\t\tct_nifti_path = abspath(glob.glob(os.path.join(out_image_nrrd, \"*.nrrd\"))[0])#abspath(glob.glob(f\"{out_image_nii}/*.nii.gz\")[0])\n",
    "\t\telif res_scheme_format == \"nii\":\n",
    "\t\t\tref_image_path = ref_image_nii_path\n",
    "\t\t\tct_nifti_path = abspath(glob.glob(os.path.join(out_image_nii, \"*.nii.gz\"))[0])#abspath(glob.glob(f\"{out_image_nii}/*.nii.gz\")[0])\n",
    "\t\telse:\n",
    "\t\t\tref_image_path = ref_image_nii_path\n",
    "\t\t\tct_nifti_path = abspath(glob.glob(os.path.join(out_image_nii, \"*.nii.gz\"))[0])#abspath(glob.glob(f\"{out_image_nii}/*.nii.gz\")[0])\n",
    "\t\tfor ai_segment_path in glob.glob(os.path.join(seg_nii_folder, serieUID_image, \"*.nii.gz\")):\n",
    "\t\t\tprint(ai_segment_path)\n",
    "\t\t\tout_segment_path = os.path.join(output_serie_resampled, ai_segment_path.split('/')[-1])\n",
    "\t\t\t# # !plastimatch resample --input $ai_segment_path \\\n",
    "\t\t\t# # --fixed $ref_image_nii_path --output $out_segment_path --interpolation nn\n",
    "\t\t\t# resample_args = {\"input\" : ai_segment_path,#change to pred path if no largest_component_retrieval necessary\n",
    "\t\t\t# \t\t\t\t\t\t\t\t\t\t\t\"output\" : out_segment_path,\n",
    "\t\t\t# \t\t\t\t\t\t\t\t\t\t\t\"fixed\" : ref_image_path,#ref_image_nii_path,\n",
    "\t\t\t# \t\t\t\t\t\t\t\t\t\t\t\"interpolation\" : \"nn\"}\n",
    "\t\t\t# pypla.resample(verbose = False, **resample_args)\n",
    "\t\t\tresample_seg_with_sitk(input_seg_nifti_path=ai_segment_path,\n",
    "\t\t\t\tinput_dicom_path=out_image_dicom_for_nrrd, \n",
    "\t\t\t\toutput_seg_path=out_segment_path)\n",
    "\t\t#compute radiomics\n",
    "\t\t##get parameters for radiomics computation\n",
    "\t\tSeriesInstanceUID = serieUID_image # image reference serieUID\n",
    "\t\tSOPInstanceUID = get_tag_pydicom(serieUID_path, \"SOPInstanceUID\").value #SOPInstanceUID of AI DICOM SEG\n",
    "\t\tct_nifti_path = abspath(ct_nifti_path)\n",
    "\t\tpred_dicomseg_path = serieUID_path\n",
    "\t\tdicomseg_json_path = abspath(glob.glob(os.path.join(seg_nii_folder, serieUID_image, \"meta.json\"))[0])\n",
    "\t\tmhub_ai_meta_df = retrieve_meta_df_from_json(dicomseg_json_path)\n",
    "\t\tdcm_directory = abspath(\"/\".join(glob.glob(os.path.join(out_image_dicom, \"**/*.dcm\"), recursive=True)[0].split(\"/\")[:-1]))\n",
    "\t\tsegments_code_mapping_df = mhub_ai_meta_df#idc_seg_segments_code_mapping_df\n",
    "\t\tshape_features_code_mapping_df = nnunet_shape_features_code_mapping_df\n",
    "\t\tmhub_serieUID_sr_path = abspath(os.path.join(seg_sr_dicom_folder, serieUID_image))\n",
    "\t\tmhub_serieUID_sr_json_path = abspath(os.path.join(seg_sr_json_dicom_folder, serieUID_image))\n",
    "\t\t!mkdir -p $mhub_serieUID_sr_path\n",
    "\t\t!mkdir -p $mhub_serieUID_sr_json_path\n",
    "\t\tsr_json_path = abspath(os.path.join(mhub_serieUID_sr_json_path, serieUID_image+\"_SR.json\"))\n",
    "\t\tsr_path = abspath(os.path.join(mhub_serieUID_sr_path, serieUID_image+\"_SR.dcm\"))\n",
    "\t\tif \"SegmentAlgorithmName\" in list(mhub_ai_meta_df.columns.values):\n",
    "\t\t\tSegmentAlgorithmName = str(mhub_ai_meta_df.SegmentAlgorithmName.unique()[0])\n",
    "\t\telse:#if SegmentAlgorithmName not in dcmqi.meta.json, that means its likely that it is an expert annotation\n",
    "\t\t\tSegmentAlgorithmName = \"MANUAL\"\n",
    "\t\tprint(f\"SegmentAlgorithmName : {SegmentAlgorithmName}\")\n",
    "\t\tsegseriesDescription = \"\"\n",
    "\t\tif len(terraRadSeriesDescription) > 0:\n",
    "\t\t\tsegseriesDescription = terraRadSeriesDescription\n",
    "\t\telse:\n",
    "\t\t\tsegseriesDescription = SegmentAlgorithmName\n",
    "\t\tlabel_values_lst = []\n",
    "\t\tlabel_names_lst = []\n",
    "\t\tfor analyzed_segmentCodeValue,analyzed_segmentCodingSchemeDesignator \\\n",
    "\t\tin zip(dicom_sr_CodeValues_lst, dicom_sr_CodingSchemeDesignator_lst):\n",
    "\t\t\tif analyzed_segmentCodeValue in mhub_ai_meta_df.FindingSite_CodeValue.values \\\n",
    "\t\t\tand analyzed_segmentCodingSchemeDesignator in mhub_ai_meta_df.FindingSite_CodingSchemeDesignator.values:\n",
    "\t\t\t\tlabel_values_lst.append(int(mhub_ai_meta_df[(mhub_ai_meta_df.FindingSite_CodeValue \\\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t== str(analyzed_segmentCodeValue))\\\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t&(mhub_ai_meta_df.FindingSite_CodingSchemeDesignator\\\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t== str(analyzed_segmentCodingSchemeDesignator))].labelID.unique()[0]))\n",
    "\t\t\t\tlabel_names_lst.append(str(mhub_ai_meta_df[(mhub_ai_meta_df.FindingSite_CodeValue \\\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t== str(analyzed_segmentCodeValue))\\\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t&(mhub_ai_meta_df.FindingSite_CodingSchemeDesignator\\\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t== str(analyzed_segmentCodingSchemeDesignator))].FindingSite_CodeMeaning.unique()[0]))\n",
    "\t\t\tlabel_values = label_values_lst\n",
    "\t\t\tlabel_names = label_names_lst\n",
    "\t\tprint(f\"label_values: {label_values}\")\n",
    "\t\tprint(f\"label_names: {label_names}\")\n",
    "\t\t#rename dcmqi seg output by segmentCodeMeaning for SR computation\n",
    "\t\tout_serieUID_renamed_path = os.path.join(seg_nii_resampled_renamed_folder, serieUID_image)\n",
    "\t\t!rm -rf $out_serieUID_renamed_path && mkdir -p $out_serieUID_renamed_path\n",
    "\t\tfor segment_dcmqi_path in glob.glob(f\"{output_serie_resampled}/*nii.gz\"):\n",
    "\t\t\tsegment_name = str(mhub_ai_meta_df[mhub_ai_meta_df.labelID == \\\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tint(segment_dcmqi_path.split(\"/\")[-1][:-7])].FindingSite_CodeMeaning.unique()[0])\n",
    "\t\t\tshutil.copy(segment_dcmqi_path, os.path.join(out_serieUID_renamed_path, f\"{segment_name}.nii.gz\"))\n",
    "\t\tsplit_pred_nii_path = abspath(out_serieUID_renamed_path)\n",
    "\t\tnnunet_features_metajson = save_structured_report_for_shape_features_idc_seg(SeriesInstanceUID=SeriesInstanceUID,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tSOPInstanceUID_seg=SOPInstanceUID,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tlabel_values=label_values,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tlabel_names = label_names,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tpred_dicomseg_path=pred_dicomseg_path,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tdicomseg_json_path=dicomseg_json_path,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tdcm_directory=dcm_directory,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsplit_pred_nii_path=split_pred_nii_path,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tct_nifti_path=ct_nifti_path,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsegments_code_mapping_df=segments_code_mapping_df,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tshape_features_code_mapping_df=shape_features_code_mapping_df,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsr_json_path=sr_json_path,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsr_path=sr_path,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tSegmentAlgorithmName=SegmentAlgorithmName,\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tSeriesDescriptionPrefix=segseriesDescription)\n",
    "\t\tprint(\"\\n\")\n",
    "\texcept:\n",
    "\t\tprint(f\"DID NOT WORK FOR : {serieUID_path}\")"
   ]
  }
 ],
 "metadata": {
  "celltoolbar": "Tags",
  "colab": {
   "collapsed_sections": [
    "924ea23b",
    "869990f5",
    "9a2b21cb"
   ],
   "gpuType": "T4",
   "include_colab_link": true,
   "machine_shape": "hm",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.15"
  },
  "papermill": {
   "default_parameters": {},
   "duration": 78.931592,
   "end_time": "2024-09-10T04:39:36.772148",
   "environment_variables": {},
   "exception": null,
   "input_path": "/app/data/sr_dicom_generation.ipynb",
   "output_path": "/app/data/sr_dicom_generation-output.ipynb",
   "parameters": {
    "OUTPUT_PATH": "/app/data/output_sr",
    "SEG_OUTPUT": "/cromwell_root/fc-5af492dc-6993-4c91-bbf6-3e2747868642/submissions/1cfa9482-c6f9-4a13-9958-42542c1fd756/mhubai_workflow/04ca2438-9a92-4e60-9519-056fca645468/call-ai_combine_seg/shard-3/ai_combination_archive.tar.lz4",
    "dicom_sr_CodeValues_lst": [
     "41216001",
     "279706003",
     "399384005"
    ],
    "dicom_sr_CodingSchemeDesignator_lst": [
     "SCT",
     "SCT",
     "SCT"
    ],
    "dicom_sr_codeMeaning_lst": [
     "Prostatic_structure",
     "Structure_of_peripheral_glandular_zone_of_prostate_(body_structure)",
     "Structure_of_transition_zone_of_prostate_(body_structure)"
    ]
   },
   "start_time": "2024-09-10T04:38:17.840556",
   "version": "2.6.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}