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Use neuroreg in cc / fornix evaluation - #103
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Pull request overview
This pull request updates fsqc’s image transformation path used in corpus callosum / fornix evaluation by refactoring applyTransform() to rely on neuroreg for transform parsing and reslicing, addressing failures with FastSurfer-produced cc_up.lta files (issue #101).
Changes:
- Added
neuroreg>=0.10.1as a dependency. - Replaced the previous
nibabel/scipy.ndimage-basedapplyTransform()implementation (and removed the customreadLTA()parser) with aneuroreg-based implementation that loads, reslices, and saves vianeuroreg.
Reviewed changes
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| File | Description |
|---|---|
| requirements.txt | Adds the neuroreg dependency required by the new transform/reslice implementation. |
| fsqc/fsqcUtils.py | Refactors applyTransform() to use neuroreg for LTA/XFM reading and reslicing; removes the custom LTA parsing code. |
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This pull request refactors the
applyTransformfunction infsqcUtils.pyto use theneuroreglibrary for image loading, transformation, and saving, replacing the previous custom andnibabel/scipy-based implementation.This addresses and closes issue #101.