Module: bundle/labelmap

Perform SCILPY scil_bundle_label_map.py. Compute the label image (Nifti) from a centroid and tractograms (all representing the same bundle). The label image represents the coverage of the bundle, segmented into regions labelled from 0 to —nb_pts, starting from the head, ending in the tail. Each voxel will have the label of its nearest centroid point. The number of labels will be the same as the centroid’s number of points.

Inputs

	Type	Description	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]
bundles	file	List of trk files of the bundles	*.{trk}
centroids	file	List of trk files of the centroids	*.{trk}

Outputs

	Type	Description	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]
versions	file	File containing software versions	versions.yml
labels	file	Labels map, each pixel intensity corresponds to the label of the nearest centroid.	*_labels.nii.gz
distances	file	Distance map. The pixel intensity corresponds to the distance to the nearest centroid.	*_distances.nii.gz
labels_trk	file	Colored by labels bundle file. The streamline color corresponds to the label of the nearest centroid.	*_labels.trk
distances_trk	file	Colored by distance bundle file. The streamline color corresponds to the distance to the nearest centroid.	*_distances.trk

Tools

	Description	Homepage	DOI
scilpy	The Sherbrooke Connectivity Imaging Lab (SCIL) Python dMRI processing toolbox.	https://github.com/scilus/scilpy.git

Keywords

bundle
distance
label
centroid

Authors

@gagnonanthony