Add DTI measures#41
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2026-04-21 DCM norm meeting:
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…used for final database)
…ile before concatenation
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Right now T2w -> template reg uses all discs for PAM50-normalized-metrics/processing_scripts/process_data_spine-generic_dwi.sh Lines 225 to 228 in 973fbec TODO: try only 2 labels to be consistent with SCT course |
… SCT course. Context: #41
Tests whether warping commutes with DTI computation: compute(warp(E1,E2,E3)) should match warp(compute(E1,E2,E3)) = warp(FA/MD/RD/AD) - sct_dmri_compute_dti now runs with -evecs 1 to also output eigenvalues E1, E2, E3 (and eigenvectors V1, V2, V3). - New section code warps E1, E2, E3 to PAM50, recomputes FA/MD/RD/AD via the new compute_dti_from_evals.py helper script, and extracts per-slice metrics
Reverts the SCT-course-style 2-label setup (commit 0d0b607) for consistency with previous runs. The 2-label code is kept commented out for reference.
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Sanity check for the "warping" method suggested by @gdavidmr: warp eigenvalues from native space to template and compute DTI metrics in the template. Then compare them to the warped DTI metrics. They should be the same. Implemented in 33b99bb. Running it rn. UPDATE: both warped FA and FA computed from warped eigenvalues are the same:
Code cleaned up in 8ca5aff |
…ce for a single subject
- generate_figures_dti.py -> generate_figures_dti_PAM50_all_subjects.py - compare_FA_PAM50_single_subject.py -> generate_figure_FA_PAM50_single_subject.py
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Verified in #41 (comment)
…prove code readability
(sct_deepseg_sc fallback wasn't issue as I reused spine-generic derivatives; but it's a good idea to use the CAv3 model for future new T2w images)
as we decided on preprocessing steps: sct_get_centerline to create a 35mm mask for sct_dmri_moco (--metric CC) and sct_deepseg spinalcord for cord DWI seg. No denoising
for now, it was okay as I was reusing spine-generic derivatives, but for future images, let's use TTS instead of sct_label_vertebrae
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TODO Sanity check on spine-generic: compare normative curves between labels under derivatives vs automatically obtained ones. |
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This PR adds a processing script to get DTI metrics in the PAM50 space.
Dataset: spine-generic multi-subject (C2-C5 DWI; n=201 healthy subjects)
Approach:
Method: Warping DTI metrics to PAM50
sct_register_to_template(T2w to PAM50)sct_register_multimodal(PAM50 to DWI; using T2w-PAM50 as init warp)sct_apply_transfo(Warp DTI maps to PAM50)Method: Interpolating DTI metrics to PAM50
More details and first results: G Slides presentation
Resolves #17