sct_denoising_onlm

Utility function to denoise images. Return the denoised image and also the difference between the input and the output. The denoising algorithm is based on the Non-local means methods (Pierrick Coupe, Jose Manjon, Montserrat Robles, Louis Collins. “Adaptive Multiresolution Non-Local Means Filter for 3D MR Image Denoising” IET Image Processing, Institution of Engineering and Technology, 2011). The implementation is based on Dipy (https://dipy.org/).

usage: sct_denoising_onlm -i <file> [-p {Rician,Gaussian}] [-d <int>]
                          [-std <float>] [-o <str>] [-h] [-v <int>] [-r {0,1}]

MANDATORY ARGUMENTS

-i

Input NIFTI image to be denoised. Example: image_input.nii.gz

OPTIONAL ARGUMENTS

-p

Possible choices: Rician, Gaussian

Type of assumed noise distribution.

Default: 'Rician'

-d

Threshold value for what to be considered as noise. The standard deviation of the noise is calculated for values below this limit. Not relevant if -std value is precised.

Default: 80

-std

Standard deviation of the noise. If not specified, it is calculated using a background of point of values below the threshold value (parameter -d).

-o

Name of the output NIFTI image.

MISC ARGUMENTS

-v

Possible choices: 0, 1, 2

Verbosity. 0: Display only errors/warnings, 1: Errors/warnings + info messages, 2: Debug mode.

Default: 1

-r

Possible choices: 0, 1

Remove temporary files.

Default: 1