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bundle_bundleparc

bundleparc

process bundleparc

Keywords : Tractography, Bundleparc, Diffusion MRI


Format : tuple val(meta), path(fodf), path(checkpoint)

TypeDescriptionMandatoryPattern
metamapGroovy Map containing sample information e.g. [ id:'test', single_end:false ]
True
fodffileNifti image of spherical harmonic file (fodf) - Stride -1234, with sh basis Descoteaux07True*.{nii,nii.gz}
checkpointfileCheckpoint file for bundleparcTrue*.{ckpt}

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

TypeDescriptionMandatoryPattern
metamapGroovy Map containing sample information e.g. [ id:'test', single_end:false ]
True
__.nii.gzfileLabel mapsTrue*.nii.gz

Format : path(versions.yml)

TypeDescriptionMandatoryPattern
versions.ymlfileFile containing software versionsTrueversions.yml

TypeDescriptionDefaultChoices
nb_ptsintNumber of divisions per bundle.10
mmintIf set, bundles will be split in sections roughly X mm wide.0
continuousboolIf set, the output label maps will be continuous ∈ [0, 1].False
keep_biggestboolOnly keep the biggest blob predicted.False
min_blob_sizeintMinimum blob size (in voxels) to keep. Smaller blobs will be removed.50
bundlesstring”Bundles to predict, space separated. Default is every bundle (71 bundles). Check the scilpy API.” “https://scilpy.readthedocs.io/en/latest/scripts/scil_fodf_bundleparc.html
halfboolUse half precision (float16) for inference. This reduces memory usage but may lead to reduced accuracy.False
sh_basisstring”Spherical harmonics basis used in the input fodf. This is required to determine the number of coefficients per voxel.” “Only ‘descoteaux07’ is currently supported. but needs to be specified for the module to run.” ” You need to link this parameter with params.fodf_sh_basis from tractoflow subworkflow and/or params.sh_basis from fodf module”

DescriptionDOI
scilpyThe Sherbrooke Connectivity Imaging Lab (SCIL) Python dMRI processing toolbox.


Last updated : 2026-05-12