reconst_diffusivitypriors

Compute the axial (para_diff), mean (iso_diff) and radial (perp_diff) diffusivity priors per subject. It is common to use this module followed by the ‘reconst_meandiffusivityprior’ module to compute the mean diffusivity prior across subjects.

Keywords : diffusivity, axial, isotropic, radial

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Inputs

Input 1

Format : tuple val(meta), path(fa), path(ad), path(rd), path(md)

	Type	Description	Mandatory	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]	True
fa	file	Nifti DTI FA volume.	True	*.{nii,nii.gz}
ad	file	Nifti DTI AD volume.	True	*.{nii,nii.gz}
rd	file	Nifti DTI RD volume.	True	*.{nii,nii.gz}
md	file	Nifti DTI MD volume.	True	*.{nii,nii.gz}

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Outputs

para_diff_file

Format : tuple val(meta), path(*_para_diff.txt)

	Type	Description	Mandatory	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]	True
*_para_diff.txt	file	Text file for parallel diffusivity value.	True	*_para_diff.txt

iso_diff_file

Format : tuple val(meta), path(*_iso_diff.txt)

	Type	Description	Mandatory	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]	True
*_iso_diff.txt	file	Text file for isotropic diffusivity value.	True	*_iso_diff.txt

perp_diff_file

Format : tuple val(meta), path(*_perp_diff.txt)

	Type	Description	Mandatory	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]	True
*_perp_diff.txt	file	Text file for perpendicular diffusivity value.	True	*_perp_diff.txt

mean_para_diff

Format : tuple val(meta), val(mean_para_diff)

	Type	Description	Mandatory	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]	True
mean_para_diff	string	String containing the average parallel diffusivity value.	True

std_para_diff

Format : tuple val(meta), val(std_para_diff)

	Type	Description	Mandatory	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]	True
std_para_diff	string	String containing the standard deviation of the parallel diffusivity value.	True

min_para_diff

Format : tuple val(meta), val(min_para_diff)

	Type	Description	Mandatory	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]	True
min_para_diff	string	String containing the minimum parallel diffusivity value.	True

max_para_diff

Format : tuple val(meta), val(max_para_diff)

	Type	Description	Mandatory	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]	True
max_para_diff	string	String containing the maximum parallel diffusivity value.	True

mean_iso_diff

Format : tuple val(meta), val(mean_iso_diff)

	Type	Description	Mandatory	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]	True
mean_iso_diff	string	String containing the average isotropic diffusivity value.	True

std_iso_diff

Format : tuple val(meta), val(std_iso_diff)

	Type	Description	Mandatory	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]	True
std_iso_diff	string	String containing the standard deviation of the isotropic diffusivity value.	True

min_iso_diff

Format : tuple val(meta), val(min_iso_diff)

	Type	Description	Mandatory	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]	True
min_iso_diff	string	String containing the minimum isotropic diffusivity value.	True

max_iso_diff

Format : tuple val(meta), val(max_iso_diff)

	Type	Description	Mandatory	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]	True
max_iso_diff	string	String containing the maximum isotropic diffusivity value.	True

mean_perp_diff

Format : tuple val(meta), val(mean_perp_diff)

	Type	Description	Mandatory	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]	True
mean_perp_diff	string	String containing the average perpendicular diffusivity value.	True

std_perp_diff

Format : tuple val(meta), val(std_perp_diff)

	Type	Description	Mandatory	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]	True
std_perp_diff	string	String containing the standard deviation of the perpendicular diffusivity value.	True

min_perp_diff

Format : tuple val(meta), val(min_perp_diff)

	Type	Description	Mandatory	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]	True
min_perp_diff	string	String containing the minimum perpendicular diffusivity value.	True

max_perp_diff

Format : tuple val(meta), val(max_perp_diff)

	Type	Description	Mandatory	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]	True
max_perp_diff	string	String containing the maximum perpendicular diffusivity value.	True

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
fa_min_single_fiber	float	Minimal threshold of FA (voxels under that threshold are considered in the ventricles).	None
fa_max_ventricles	float	Maximal threshold of FA (voxels under that threshold are considered in the ventricles).	None
md_min_ventricles	float	Minimal threshold of MD in mm2/s (voxels above that threshold are considered for the ventricles).	None
roi_radius	integer	Radius of the region used to estimate the priors. The roi will be a cube spanning from ROI_CENTER in each direction.	None

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Tools

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

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Authors

• @Manonedde

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Last updated : 2025-12-22