RecoBundlesFlow

Recognize bundles

Parameters

streamline_files : string
The path of streamline files where you want to recognize bundles
model_bundle_files : string
The path of model bundle files
greater_than : int, optional
Keep streamlines that have length greater than this value (default 50) in mm.
less_than : int, optional
Keep streamlines have length less than this value (default 1000000) in mm.
no_slr : bool, optional
Don’t enable local Streamline-based Linear Registration (default False).
clust_thr : float, optional
MDF distance threshold for all streamlines (default 15)
reduction_thr : float, optional
Reduce search space by (mm) (default 15)
reduction_distance : string, optional
Reduction distance type can be mdf or mam (default mdf)
model_clust_thr : float, optional
MDF distance threshold for the model bundles (default 2.5)
pruning_thr : float, optional
Pruning after matching (default 8).
pruning_distance : string, optional
Pruning distance type can be mdf or mam (default mdf)
slr_metric : string, optional
Options are None, symmetric, asymmetric or diagonal (default symmetric).
slr_transform : string, optional
Transformation allowed. translation, rigid, similarity or scaling (Default ‘similarity’).
slr_matrix : string, optional
Options are ‘nano’, ‘tiny’, ‘small’, ‘medium’, ‘large’, ‘huge’ (default ‘small’)
refine : bool, optional
Enable refine recognized bunle (default False)
r_reduction_thr : float, optional
Refine reduce search space by (mm) (default 12)
r_pruning_thr : float, optional
Refine pruning after matching (default 6).
no_r_slr : bool, optional
Don’t enable Refine local Streamline-based Linear Registration (default False).
out_dir : string, optional
Output directory (default input file directory)
out_recognized_transf : string, optional
Recognized bundle in the space of the model bundle (default ‘recognized.trk’)
out_recognized_labels : string, optional
Indices of recognized bundle in the original tractogram (default ‘labels.npy’)

References

[Garyfallidis17]Garyfallidis et al. Recognition of white matter bundles using local and global streamline-based registration and clustering, Neuroimage, 2017.