Module: bundle/recognize
Extract bundles from one (or more) tractograms
Keywords : Diffusion MRI, Tractogram, Segmentation, Bundles
| Type | Description | Mandatory | Pattern |
|---|
| meta | map | Groovy Map containing sample information e.g. [ id:'test', single_end:false ] | true | |
| tractograms | file | Tractogram file(s) for bundle extraction | true | *.trk |
| transform | file | Transform matrix bringing the atlas to native space | true | *.mat |
| config | file | Bundle atlas configuration file | true | *.json |
| directory | directory | Directory containing the reference atlas | true | |
Outputs
| Type | Description | Pattern |
|---|
| meta | map | Groovy Map containing sample information e.g. [ id:'test', single_end:false ] | |
| bundles | file | Segmented and cleaned bundles | *.trk |
| versions | file | File containing software versions | versions.yml |
| Type | Description | Default | Choices |
|---|
| minimal_vote_ratio | float | The ratio is a value between 0 and 1. Ex: If you have 5 input model directories and a minimal_vote_ratio of 0.5, you will need at least 3 votes. | 0.5 | |
| seed | int | Seed for random number generator | 0 | |
| processes | int | Number of sub-processes to start. | 1 | |
| outlier_alpha | float | Percent of the length of the tree that clusters of individual streamlines will be pruned. | 0.6 | |
| Description | DOI |
|---|
| Scilpy | The Sherbrooke Connectivity Imaging Lab (SCIL) Python dMRI processing toolbox. | |
Authors
CHrlS98
Last updated : 2025-07-15
