tracking_pfttracking

Compute include and exclude maps, and the seeding mask from partial volume estimation (PVE) maps. Generates a tractogram using anatomically-constrained particle filter tracking, Particle Filtering Tractography (PFT).

Keywords : Diffusion MRI, Tractography, Particle Filtering Tractography

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Inputs

Input 1

Format : tuple val(meta), path(wm), path(gm), path(csf), path(fodf), path(fa)

	Type	Description	Mandatory	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]	True
wm	file	Nifti white matter probability map.	True	*.{nii,nii.gz}
gm	file	Nifti grey matter probability map.	True	*.{nii,nii.gz}
csf	file	Nifti cerebrospinal fuild probability map.	True	*.{nii,nii.gz}
fodf	file	Nifti image of Spherical harmonic file (fodf).	True	*.{nii,nii.gz}
fa	file	Nifti image of FA.	True	*.{nii,nii.gz}

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Outputs

trk

Format : tuple val(meta), path(*__pft_tracking.trk)

	Type	Description	Mandatory	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]	True
*__pft_tracking.trk	file	Tractogram output file.	True	*__pft_tracking.{trk,tck}

config

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

	Type	Description	Mandatory	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]	True
*__pft_tracking_config.json	file	Json file containing tracking parameters.	True	*__pft_tracking_config.{json}

includes

Format : tuple val(meta), path(*__map_include.nii.gz)

	Type	Description	Mandatory	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]	True
*__map_include.nii.gz	file	Nifti probability map for tracking of ending the streamline and including it in the output.	True	*__map_include.{nii,nii.gz}

excludes

Format : tuple val(meta), path(*__map_exclude.nii.gz)

	Type	Description	Mandatory	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]	True
*__map_exclude.nii.gz	file	Nifti probability map for tracking of ending the streamline and excluding it in the output.	True	*__map_exclude.{nii,nii.gz}

seeding

Format : tuple val(meta), path(*__pft_seeding_mask.nii.gz)

	Type	Description	Mandatory	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]	True
*__pft_seeding_mask.nii.gz	file	Nifti seeding mask for tracking.	True	*__pft_seeding_mask.{nii,nii.gz}

mqc

Format : tuple val(meta), path(*__pft_tracking_mqc.png)

	Type	Description	Mandatory	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]	True
*__pft_tracking_mqc.png	file	PNG file containing quality control image for tracking. Made for use in MultiQC report.	True	*__pft_tracking_mqc.png

global_mqc

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

	Type	Description	Mandatory	Pattern
meta	map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]	True
*__pft_tracking_stats.json	file	JSON file containing basic measurements of whole tractogram. Made for use in MultiQC report.	True	*__pft_tracking_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
pft_fa_seeding_mask_threshold	float	FA threshold for the seeding mask.	0.1
pft_wm_seeding_mask_threshold	float	WM threshold for the seeding mask.	0.5
pft_seeding_mask_type	string	Strategy to use to compute the seeding mask.	wm	- wm - fa
pft_step	float	Tracking Step size.	0.2
pft_random_seed	int	Seed for random number generators.	0
pft_seeding	string	Seeding strategy, either Number Per Voxel (npv) or Number Total (nt).	npv	- npv - nt
pft_nbr_seeds	int	Number of seeds per voxel (if npv) or total number of seeds (if nt).	5
pft_min_len	float	Minimum length of streamlines to keep.	10.0
pft_max_len	float	Maximum length of streamlines to keep.	300.0
pft_theta	float	Maximum angular difference between tracking steps, in degrees.	40.0
pft_sfthres	float	Spherical function threshold for tracking.	0.1
pft_sfthres_init	float	Initial spherical function threshold for tracking.	0.5
pft_algo	string	Algorithm to use for tracking.	prob	- det - prob
pft_compress_value	float	Compression value for the streamlines, in mm. If 0, no compression is applied.	0.0
basis	string	Spherical basis used for FODF reconstruction.	descoteaux07_legacy	- descoteaux07_legacy - descoteaux07 - tournier07 - tournier07_legacy
pft_particles	int	Number of particles to use in the particle filter tracking.	15
pft_back	float	Backtracking distance in mm.	2.0
pft_front	float	Front tracking distance in mm.	1.0
run_qc	boolean	Whether to run quality control (QC) on the tracking results.	True

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Tools

	Description	DOI
DIPY	DIPY is the paragon 3D/4D+ imaging library in Python.	10.1016/j.neuroimage.2014.04.074
scilpy	The Sherbrooke Connectivity Imaging Lab (SCIL) Python dMRI processing toolbox.

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Authors

• @Manonedde

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Last updated : 2025-10-30