From SlicerWiki

Introduction and Acknowledgements

This work is part of the National Alliance for Medical Image Computing (NA-MIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149. Information on NA-MIC can be obtained from the NA-MIC website. Author: FIRSTNAME LASTNAME, AFFILIATION Contributor1: FIRSTNAME LASTNAME, AFFILIATION Contributor2: FIRSTNAME LASTNAME, AFFILIATION Contact: FIRSTNAME LASTNAME,

Isomics, Inc. <- Replace this logo with yours   Surgical Planning Laboratory (SPL) <-Replace this logo with yours

Module Description

This module reduces Rician noise (or unwanted detail) on a set of diffusion weighted images. For this, it filters the image in the mean squared error sense using a Rician noise model. The N closest gradient directions to the direction being processed are filtered together to improve the results: the noise-free signal is seen as an n-diemensional vector which has to be estimated with the LMMSE method from a set of corrupted measurements. To that end, the covariance matrix of the noise-free vector and the cross covariance between this signal and the noise have to be estimated, which is done taking into account the image formation process. The noise parameter is automatically estimated from a rough segmentation of the background of the image. In this area the signal is simply 0, so that Rician statistics reduce to Rayleigh and the noise power can be easily estimated from the mode of the histogram. A complete description of the algorithm may be found in: Antonio Tristan-Vega and Santiago Aja-Fernandez, DWI filtering using joint information for DTI and HARDI, Medical Image Analysis, Volume 14, Issue 2, Pages 205-218. 2010.

Use Cases

N/A

Tutorials

N/A

Panels and their use

Parameters:

• DWI Noise Removal Parameters
  • Estimation Radius: Estimation radius.
  • Filtering Radius: Filtering radius.
  • Number of neighboring gradients: The number of the closest gradients that are used to jointly filter a given gradient direction (0 to use all).
• IO
  • Input Volume: Input DWI volume.
  • Output Volume: Output DWI volume.

Similar Modules

N/A

References

N/A

Information for Developers

Section under construction.