stats_metricsinroi

Module to compute statistics (mean, std) of scalar maps (metrics), which can represent diffusion metrics, in ROIs or labels.

Keywords : nifti, volume, scilpy, stats, rois

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Inputs

Input 1

Format : tuple val(meta), path(metrics), path(rois), path(rois_lut)

	Type	Description	Mandatory	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]	True
metrics	file	Metrics volume(s) in Nifti	True	*.{nii,nii.gz}
rois	file	ROI or Label volume(s) in Nifti	True	*.{nii,nii.gz}
rois_lut	file	LUT file corresponding to labels, used to name the regions of interest	True	*.{nii,nii.gz}

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Outputs

mqc

Format : tuple val(meta), path(*_stats.json)

	Type	Description	Mandatory	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]	True
*_stats.json	file	JSON file containing mean/std per pair of roi/metrics or label/metrics	True	*_stats.json

versions

Format : path(versions.yml)

	Type	Description	Mandatory	Pattern
versions.yml	file	File containing software versions	True	versions.yml

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Arguments (see process.ext)

	Type	Description	Default	Choices
suffix	string	It will add an extra string before “_stats.json”
bin	boolean	If set, will consider every value of the mask higherthan 0 to be part of the mask (equivalent weighting for every voxel). It will be used if use_label is false.	False
normalize_weights	boolean	If set, the weights will be normalized to the [0,1] range. It will be used if use_label is false.	False
use_label	boolean	If set, rois image will be considered as a label image with multiple indices.	False

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Tools

	Description	DOI
scilpy	The Sherbrooke Connectivity Imaging Lab (SCIL) Python dMRI processing toolbox.

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Authors

• @arnaudbore

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Last updated : 2025-10-20