usage: __main__.py [-h]
[--tractogram_clustering_thr TRACTOGRAM_CLUSTERING_THR]
[--model_clustering_thr MODEL_CLUSTERING_THR]
[--pruning_thr PRUNING_THR] [--slr_threads SLR_THREADS]
[--seed SEED] [--inverse] [--no_empty]
[--in_pickle IN_PICKLE | --out_pickle OUT_PICKLE]
[--reference REFERENCE] [-v [{DEBUG,INFO,WARNING}]] [-f]
in_tractogram in_model in_transfo out_tractogram
Compute a simple Recobundles (single-atlas & single-parameters).
The model need to be cleaned and lightweight.
Transform should come from ANTs: (using the --inverse flag)
AntsRegistrationSyNQuick.sh -d 3 -m MODEL_REF -f SUBJ_REF
If you are unsure about the transformation 'direction' use the verbose
option (-v) and try with and without the --inverse flag. If you are not using
the right transformation 'direction' a warning will popup. If there is no
warning in both case it means the transformation is very close to identity and
both 'direction' will work.
Formerly: scil_recognize_single_bundles.py
positional arguments:
in_tractogram Input tractogram filename.
in_model Model to use for recognition.
in_transfo Path for the transformation to model space (.txt, .npy or .mat).
out_tractogram Output tractogram filename.
options:
-h, --help show this help message and exit
--tractogram_clustering_thr TRACTOGRAM_CLUSTERING_THR
Clustering threshold used for the whole brain [8mm].
--model_clustering_thr MODEL_CLUSTERING_THR
Clustering threshold used for the model [4mm].
--pruning_thr PRUNING_THR
MDF threshold used for final streamlines selection [6mm].
--slr_threads SLR_THREADS
Number of threads for SLR [1].
--seed SEED Random number generator seed [None].
--inverse Use the inverse transformation.
--no_empty Do not write file if there is no streamline.
--in_pickle IN_PICKLE
Input pickle clusters map file.
Will override the tractogram_clustering_thr parameter.
--out_pickle OUT_PICKLE
Output pickle clusters map file.
--reference REFERENCE
Reference anatomy for tck/vtk/fib/dpy file
support (.nii or .nii.gz).
-v [{DEBUG,INFO,WARNING}]
Produces verbose output depending on the provided level.
Default level is warning, default when using -v is info.
-f Force overwriting of the output files.
Garyfallidis, E., Cote, M. A., Rheault, F., ... &
Descoteaux, M. (2018). Recognition of white matter
bundles using local and global streamline-based registration and
clustering. NeuroImage, 170, 283-295.