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FIX: Ensure shape matches template during resampling #3296

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FIX: Ensure shape matches template during resampling #3296

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553d7e0
FIX: Ensure shape matches template
mgxd Jun 3, 2024
44bf370
Update fmriprep/utils/transforms.py
mgxd Jun 4, 2024
a28212d
STY: ruff, use trailing comma to force reshape to expand
effigies Jun 4, 2024
bcc7d3e
FIX: Catch cases of unexpected resampling
mgxd Jun 5, 2024
c9619a8
Apply suggestions from code review
mgxd Jun 5, 2024
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37 changes: 17 additions & 20 deletions fmriprep/utils/transforms.py
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Original file line number Diff line number Diff line change
@@ -1,6 +1,5 @@
"""Utilities for loading transforms for resampling"""

import warnings
from pathlib import Path

import h5py
Expand Down Expand Up @@ -38,16 +37,6 @@ def load_transforms(xfm_paths: list[Path], inverse: list[bool]) -> nt.base.Trans
return chain


FIXED_PARAMS = np.array([
193.0, 229.0, 193.0, # Size
96.0, 132.0, -78.0, # Origin
1.0, 1.0, 1.0, # Spacing
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-1.0, 0.0, 0.0, # Directions
0.0, -1.0, 0.0,
0.0, 0.0, 1.0,
]) # fmt:skip


def load_ants_h5(filename: Path) -> nt.base.TransformBase:
"""Load ANTs H5 files as a nitransforms TransformChain"""
# Borrowed from https://github.com/feilong/process
Expand Down Expand Up @@ -81,17 +70,25 @@ def load_ants_h5(filename: Path) -> nt.base.TransformBase:
raise ValueError(msg)

fixed_params = transform2['TransformFixedParameters'][:]
if not np.array_equal(fixed_params, FIXED_PARAMS):
msg = 'Unexpected fixed parameters\n'
msg += f'Expected: {FIXED_PARAMS}\n'
msg += f'Found: {fixed_params}'
if not np.array_equal(fixed_params[6:], FIXED_PARAMS[6:]):
raise ValueError(msg)
warnings.warn(msg, stacklevel=1)

spacing = fixed_params[6:9]
direction = fixed_params[9:]
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# Supported spacing
if not np.array_equal(spacing, np.array([1.0, 1.0, 1.0])):
raise ValueError(f'Unexpected spacing: {spacing}')

if not np.array_equal(direction, np.diag([-1, -1, -1])):
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raise ValueError(f'Asymmetric direction matrix: {direction}')

shape = tuple(fixed_params[:3].astype(int))
warp = h['TransformGroup']['2']['TransformParameters'][:]
warp = warp.reshape((*shape, 3)).transpose(2, 1, 0, 3)
# ITK stores warps in Fortran-order, where the vector components change fastest
# Nitransforms expects 3 volumes, not a volume of three-vectors, so transpose
warp = np.reshape(
transform2['TransformParameters'],
(3, *shape),
order='F',
).transpose(1, 2, 3, 0)
warp *= np.array([-1, -1, 1])

warp_affine = np.eye(4)
Expand Down
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