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denoising_nlmeans

Denoise a dataset with the Non Local Means algorithm.

In order to denoise, we have three methods to estimate the noise available with their requirements:

  • Sigma (needs: sigma)
  • Basic sigma (needs: ncoils, optional: mask_sigma or sigma_from_all_voxels)
  • Piesno (needs: ncoils)

Keywords : nifti, denoising, nlmeans, scilpy


Format : tuple val(meta), path(image), path(mask), path(mask_sigma)

TypeDescriptionMandatoryPattern
metamapGroovy Map containing sample information e.g. [ id:'test', single_end:false ]True
imagefileNifti image file to denoiseTrue*.{nii,nii.gz}
maskfileNifti image file used to mask the input imageFalse*.{nii,nii.gz}
mask_sigmafileNifti binary image file used to mask the input image for —basic_sigma estimation. Only the data inside the mask will be used to estimate sigmaFalse*.{nii,nii.gz}

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

TypeDescriptionMandatoryPattern
metamapGroovy Map containing sample information e.g. [ id:'test', single_end:false ]True
*__denoised.nii.gzfileDenoised Nifti image fileTrue*_denoised.{nii,nii.gz}

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

TypeDescriptionMandatoryPattern
metamapGroovy Map containing sample information e.g. [ id:'test', single_end:false ]True
*__piesno_mask.nii.gzfilePiesno mask Nifti image fileTrue*__piesno_mask.{nii,nii.gz}

Format : path(versions.yml)

TypeDescriptionMandatoryPattern
versions.ymlfileFile containing software versionsTrueversions.yml

TypeDescriptionDefaultChoices
sigmafloatProvide your own standard deviation of the noise.
basic_sigmaboolEstimate sigma using Use dipy’s basic estimation of sigma.
piesnoboolEstimate sigma using Piesno’s method. If data is 4D, the noise is estimated for each slice (3rd dimension).
gaussianboolIf your data contains gaussian noise, set this option. Otherwise, Rician is assumed.
sigma_from_all_voxelsboolIf set, all voxels are used for the —basic_sigma estimation, even zeros.
save_piesno_maskboolIf set with piesno option, it will save the piesno mask.
ncoilsintNumber of coils used for the acquisition1

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


Last updated : 2025-10-30