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labelmap

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

TypeDescriptionMandatoryPattern
metamapGroovy Map containing sample information e.g. [ id:'test', single_end:false ]true
bundlesfileList of trk files of the bundlestrue*.{trk}
centroidsfileList of trk files of the centroidstrue*.{trk}

Arguments

TypeDescriptionChoicesDefault
nb_pointsintNumber of divisions for the bundles.Number of points of the centroid
colormapstringSelect the colormap for colored trk (data_per_point).jet
new_labellingbooleanUse the new labelling method (multi-centroids).False

Outputs

TypeDescriptionPattern
metamapGroovy Map containing sample information e.g. [ id:'test', single_end:false ]
versionsfileFile containing software versionsversions.yml
labelsfileLabels map, each pixel intensity corresponds to the label of the nearest centroid.*_labels.nii.gz
distancesfileDistance map. The pixel intensity corresponds to the distance to the nearest centroid.*_distances.nii.gz
labels_trkfileColored by labels bundle file. The streamline color corresponds to the label of the nearest centroid.*_labels.trk
distances_trkfileColored by distance bundle file. The streamline color corresponds to the distance to the nearest centroid.*_distances.trk

Tools

DescriptionHomepageDOI
scilpyThe Sherbrooke Connectivity Imaging Lab (SCIL) Python dMRI processing toolbox.https://github.com/scilus/scilpy.git

Authors

@gagnonanthony