Code and pretrained model for BundleParc: automatic tract labeling without tractography
BundleParc so far has not been tested on data other than healthy young adults. If you're using BundleParc on pathological/young/old patients, let me know how it went and what can be improved ! Send me an email at "antoine (dot) theberge (at) usherbrooke (dot) ca".
Only Python3.10 is currently supported. It is recommended to install the software in a virtualenv.
To install, in the cloned project's folder:
pip install -e .Docker containers are coming soon-ish.
The method takes as input a fODF map of order 6 (descoteaux07 basis) and a WM mask:
Example command:
bundleparc_predict fodf.nii.gz --out_folder bundleparc --out_prefix sub-001__ --nb_pts 25
See --help for more arguments.
Example output:
bundleparc/sub-001__AF_left.nii.gz, bundleparc/sub-001__AF_right.nii.gz, ..., bundleparc/sub-001__UF_right.nii.gz
The software will output 71 files, each corresponding to a bundle's label map. The bundle definitions follow TractSeg's, minus the whole CC.
BundleParc may move to scilpy soon ! Stay updated by starring the repo.
Ran into a problem during installation or prediction ? Have a question ? Please open an issue !
Antoine Théberge, Zineb El Yamani, François Rheault, Maxime Descoteaux, Pierre-Marc Jodoin (2025). LabelSeg. ISMRM Workshop on 40 Years of Diffusion: Past, Present & Future Perspectives, Kyoto, Japan.
Full paper in the works.