Docker to segment white matter bundles with Classifyber.
You can run Classifyber through the docker container in the following way:
sudo docker run -v /absolute/path/to/my/data/directory:/data \
-t giuliaberto/classifyber:1.1 ./Classifyber-seg \
-tractogram /data/track.tck \
-t1 /data/t1.nii.gz \
-config /data/config.json
provided that track.tck is the whole brain tractogram from which you want to segment the bundles, that t1.nii.gz is the T1 structral image (in the same anatomical space of the tractogram), and that config.json contains the IDs of the bundles to be segmented (for a template refer to the config_template.json file and for the ID mapping refer to this repo https://github.com/FBK-NILab/app-classifyber-segmentation).
"Classifyber, a robust streamline-based linear classifier for white matter bundle segmentation", Bertò, G., Bullock, D., Astolfi, P., Hayashi, S., Zigiotto, L., Annicchiarico, L., Corsini, F., De Benedictis, A., Sarubbo, S., Pestilli, F., Avesani, P., Olivetti, E.