Wraps command ** UnbiasedNonLocalMeans **
title: Unbiased NLM for MRI
category: Filtering.Denoising
version: 0.0.1.$Revision: 1 $(beta)
documentation-url: http://www.slicer.org/slicerWiki/index.php/Modules:UnbiasedNonLocalMeans-Documentation-3.6
contributor: Antonio Tristan Vega, Veronica Garcia-Perez, Santiago Aja-Fernandez, Carl-Fredrik Westin
acknowledgements: Supported by grant number FMECD-2010/71131616E from the Spanish Ministry of Education/Fulbright Committee
Inputs:
[Mandatory]
[Optional]
args: (a string)
Additional parameters to the command
flag: %s
environ: (a dictionary with keys which are a value of type 'str' and
with values which are a value of type 'str', nipype default value:
{})
Environment variables
hp: (a float)
This parameter is related to noise; the larger the parameter, the
more aggressive the filtering. Should be near 1, and only values
between 0.8 and 1.2 are allowed
flag: --hp %f
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
inputVolume: (an existing file name)
Input MRI volume.
flag: %s, position: -2
outputVolume: (a boolean or a file name)
Output (filtered) MRI volume.
flag: %s, position: -1
ps: (a float)
To accelerate computations, preselection is used: if the normalized
difference is above this threshold, the voxel will be discarded (non
used for average)
flag: --ps %f
rc: (a list of items which are an integer)
Similarity between blocks is computed as the difference between mean
values and gradients. These parameters are computed fitting a
hyperplane with LS inside a neighborhood of this size
flag: --rc %s
rs: (a list of items which are an integer)
The algorithm search for similar voxels in a neighborhood of this
radius (radii larger than 5,5,5 are very slow, and the results can
be only marginally better. Small radii may fail to effectively
remove the noise).
flag: --rs %s
sigma: (a float)
The root power of noise (sigma) in the complex Gaussian process the
Rician comes from. If it is underestimated, the algorithm fails to
remove the noise. If it is overestimated, over-blurring is likely to
occur.
flag: --sigma %f
terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
Control terminal output: `stream` - displays to terminal immediately
(default), `allatonce` - waits till command is finished to display
output, `file` - writes output to file, `none` - output is ignored
Outputs:
outputVolume: (an existing file name)
Output (filtered) MRI volume.