bundle_stats
Compile statistics on bundle profiles. Uses the data after segmenting the tractogram into different bundles, which in turn are segmented into different sections. This module allows you to perform statistical analysis on bundles using metrics maps. You can choose from several types of statistics. ----------- Available statistics ----------- volume:
- volume_info: volume, volume_endpoints
- streamlines_info: streamlines_count, avg_length (in mm or in number of point), average step size, min_length, max_length.
- shape_info: span, curl, diameter, elongation, surface area, irregularity, end surface area, radius, end surface irregularity, mean_curvature, fractal dimension. ** The diameter, here, is a simple estimation using volume / length. length: number of streamlines, and mean / min / max / std of :
- length in number of points
- length in mm
- step size. endpoints: Computes the endpoint map of a bundle. The endpoint map is simply a count of the number of streamlines that start or end in each voxel. Then, Compute the statistics (mean, std) of scalar maps, which can represent diffusion metrics, in endpoint map. mean std:
- mean and std for each metric. streamline count:
- number of streamlines in a tractogram. (as this information is given by the volume stat you can choose to want only the streamlines count by deactivating volume and activating streamlines count.) volume per labels:
- bundle volume per label in mm3. This script supports anisotropic voxels resolution. Volume is estimated by counting the number of voxel occupied by each label and multiplying it by the volume of a single voxel. mean std per labels:
- mean and std for each metric along the bundle for each point(labels). **To create label_map and distance_map, see scil_bundle_label_map.py
Keywords : Bundle, Labels, Statistic, Volume, Length, Endpoint, Mean std, Streamlines count, json
Inputs
Section titled “Inputs”Input 1
Section titled “Input 1”Format : tuple val(meta), path(bundles), path(labels_map), path(metrics), path(lesions)
| Type | Description | Mandatory | Pattern | |
|---|---|---|---|---|
| meta | map | Groovy Map containing sample information e.g. [ id:'sample1', single_end:false ] | True | |
| bundles | file | Fiber bundle file to compute statistics on. | True | *.trk |
| labels_map | file | label map of the corresponding fiber bundle. this file must have the same dimension than bundle file and have datatype in int. If you have multiple bundles, it must have the same numbers of sections. | True | *.nii.gz |
| metrics | file | Nifti file to compute statistics on. Probably some tractometry measure(s) such as FA, MD, RD, … The metrics has to follow a specific naming convention. | True | *_{bundle_name}_{metric_name}.nii.gz |
| lesions | file | Nifti lesion volume to compute statistics on. The lesion mask must be a binary mask. | False | *.nii.gz |
Outputs
Section titled “Outputs”length
Section titled “length”Format : tuple val(meta), path(*__length_stats.json)
| Type | Description | Mandatory | Pattern | |
|---|---|---|---|---|
| meta | map | Groovy Map containing sample information e.g. [ id:'sample1', single_end:false ] | True | |
| *__length_stats.json | file | Information on a bundle(s) : number of streamlines, mean / min / max / std of length in number of points, length in mm and step size. | True | *__length_stats.json |
endpoints_raw
Section titled “endpoints_raw”Format : tuple val(meta), path(*__endpoints_map_raw.json)
| Type | Description | Mandatory | Pattern | |
|---|---|---|---|---|
| meta | map | Groovy Map containing sample information e.g. [ id:'sample1', single_end:false ] | True | |
| *__endpoints_map_raw.json | file | Estimation of the cortical area affected by the bundle(s) (assuming streamlines start/end in the cortex). | True | *__endpoints_map_raw.json |
endpoints_metric_stats
Section titled “endpoints_metric_stats”Format : tuple val(meta), path(*__endpoints_metric_stats.json)
| Type | Description | Mandatory | Pattern | |
|---|---|---|---|---|
| meta | map | Groovy Map containing sample information e.g. [ id:'sample1', single_end:false ] | True | |
| *__endpoints_metric_stats.json | file | Statistics of metrics at the bundle(s) endpoints. | True | *__endpoints_metric_stats.json |
mean_std
Section titled “mean_std”Format : tuple val(meta), path(*__mean_std.json)
| Type | Description | Mandatory | Pattern | |
|---|---|---|---|---|
| meta | map | Groovy Map containing sample information e.g. [ id:'sample1', single_end:false ] | True | |
| *__mean_std.json | file | Average the metric values of all voxels occupied by the bundle(s). | True | *__mean_std.json |
volume
Section titled “volume”Format : tuple val(meta), path(*__volume.json)
| Type | Description | Mandatory | Pattern | |
|---|---|---|---|---|
| meta | map | Groovy Map containing sample information e.g. [ id:'sample1', single_end:false ] | True | |
| *__volume.json | file | Volume occupied by the bundle(s). | True | *__volume.json |
volume_lesions
Section titled “volume_lesions”Format : tuple val(meta), path(*__volume_lesions.json)
| Type | Description | Mandatory | Pattern | |
|---|---|---|---|---|
| meta | map | Groovy Map containing sample information e.g. [ id:'sample1', single_end:false ] | True | |
| *__volume_lesions.json | file | Bundle(s) volume in each lesions in mm3. | True | *__volume_lesion.json |
streamline_count
Section titled “streamline_count”Format : tuple val(meta), path(*__streamline_count.json)
| Type | Description | Mandatory | Pattern | |
|---|---|---|---|---|
| meta | map | Groovy Map containing sample information e.g. [ id:'sample1', single_end:false ] | True | |
| *__streamline_count.json | file | Number of streamlines in the bundle(s). | True | *__streamline_count.json |
streamline_count_lesions
Section titled “streamline_count_lesions”Format : tuple val(meta), path(*__streamline_count_lesions.json)
| Type | Description | Mandatory | Pattern | |
|---|---|---|---|---|
| meta | map | Groovy Map containing sample information e.g. [ id:'sample1', single_end:false ] | True | |
| *__streamline_count_lesions.json | file | Number of streamlines in each lesions. | True | *__streamline_count_lesions.json |
volume_per_labels
Section titled “volume_per_labels”Format : tuple val(meta), path(*__volume_per_label.json)
| Type | Description | Mandatory | Pattern | |
|---|---|---|---|---|
| meta | map | Groovy Map containing sample information e.g. [ id:'sample1', single_end:false ] | True | |
| *__volume_per_label.json | file | Bundle volume per label in mm3. Volume is estimated by counting the number of voxel occupied by each label and multiplying it by the volume of a single voxel. | True | *__volume_per_label.json |
volume_per_labels_lesions
Section titled “volume_per_labels_lesions”Format : tuple val(meta), path(*__volume_per_label_lesions.json)
| Type | Description | Mandatory | Pattern | |
|---|---|---|---|---|
| meta | map | Groovy Map containing sample information e.g. [ id:'sample1', single_end:false ] | True | |
| *__volume_per_label_lesions.json | file | Bundle(s) volume per label in each lesions in mm3. | True | *__volume_per_label_lesions.json |
mean_std_per_point
Section titled “mean_std_per_point”Format : tuple val(meta), path(*__mean_std_per_point.json)
| Type | Description | Mandatory | Pattern | |
|---|---|---|---|---|
| meta | map | Groovy Map containing sample information e.g. [ id:'sample1', single_end:false ] | True | |
| *__mean_std_per_point.json | file | Average metric values of all voxels occupied by the bundle per label. | True | *__mean_std_per_point.json |
lesion_stats
Section titled “lesion_stats”Format : tuple val(meta), path(*__lesion_stats.json)
| Type | Description | Mandatory | Pattern | |
|---|---|---|---|---|
| meta | map | Groovy Map containing sample information e.g. [ id:'sample1', single_end:false ] | True | |
| *__lesion_stats.json | file | Lesion-wise volume measure. | True | *__lesion_stats.json |
endpoints_head
Section titled “endpoints_head”Format : tuple val(meta), path(*_endpoints_map_head.nii.gz)
| Type | Description | Mandatory | Pattern | |
|---|---|---|---|---|
| meta | map | Groovy Map containing sample information e.g. [ id:'sample1', single_end:false ] | True | |
| *_endpoints_map_head.nii.gz | file | Endpoint head map of bundle. The endpoint head map is simply a count of the number of streamlines that start in each voxel. | True | *__endpoints_map_head.nii.gz |
endpoints_tail
Section titled “endpoints_tail”Format : tuple val(meta), path(*_endpoints_map_tail.nii.gz)
| Type | Description | Mandatory | Pattern | |
|---|---|---|---|---|
| meta | map | Groovy Map containing sample information e.g. [ id:'sample1', single_end:false ] | True | |
| *_endpoints_map_tail.nii.gz | file | Endpoint tail map of bundle. The endpoint tail map is simply a count of the number of streamlines that end in each voxel. | True | *__endpoints_map_tail.nii.gz |
lesion_map
Section titled “lesion_map”Format : tuple val(meta), path(*_lesion_map.nii.gz)
| Type | Description | Mandatory | Pattern | |
|---|---|---|---|---|
| meta | map | Groovy Map containing sample information e.g. [ id:'sample1', single_end:false ] | True | |
| *_lesion_map.nii.gz | file | Nifti files of labeled lesion(s) map for each bundles. | True | *__lesion_map.nii.gz |
versions
Section titled “versions”Format : path(versions.yml)
| Type | Description | Mandatory | Pattern | |
|---|---|---|---|---|
| versions.yml | file | File containing software versions | True | versions.yml |
Arguments (see process.ext)
Section titled “Arguments (see process.ext)”| Type | Description | Default | Choices | |
|---|---|---|---|---|
| density_weighting | boolean | If set, weights statistics by the number of fibers passing through each voxel. | False | |
| normalize_weights | boolean | If set, the weights will be normalized to the [0,1] range. | False | |
| length_stats | boolean | If set, compute the length stats of the streamlines. | True | |
| endpoints | boolean | If set, compute the endpoint map of the bundle. | False | |
| mean_std | boolean | If set, compute the mean and std of the metrics along the bundle. | False | |
| volume | boolean | If set, compute the volume of the bundle(s). | False | |
| lesions_stats | boolean | If set, compute the statistics of the lesion volume. | False | |
| min_lesion_vol | int | Minimum volume of a lesion to be considered (mm). | 7 | |
| streamline_count | boolean | If set, compute the number of streamlines in a bundle. | False | |
| volume_per_labels | boolean | If set, compute bundle volume per label in mm3. | False | |
| mean_std_per_point | boolean | If set, compute the mean and std of the metrics along the bundle for each point(labels). | False |
| Description | DOI | |
|---|---|---|
| scilpy | The Sherbrooke Connectivity Imaging Lab (SCIL) Python dMRI processing toolbox. |
Authors
Section titled “Authors”Last updated : 2025-10-30