Difference between revisions of "Modules:RicianLMMSEImageFilter-Documentation-3.6"
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===Source code & documentation=== | ===Source code & documentation=== | ||
| + | Source Code: Follow this [http://www.na-mic.org/ViewVC/index.cgi/trunk/Applications/CLI/DiffusionApplications/dwiNoiseFilter link] | ||
| + | |||
| + | Doxygen documentation: | ||
| + | *[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classitk_1_1ComputeRestrictedHistogram.html itkComputeRestrictedHistogram.h] | ||
| + | *[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classitk_1_1ComputeStatisticsWherePositiveFilter.html itkComputeStatisticsWherePositiveFilter.h] | ||
| + | *[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classitk_1_1ExtractVolumeFilter.html itkExtractVolumeFilter.h] | ||
| + | *[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classitk_1_1LMMSEVectorImageFilter.html itkLMMSEVectorImageFilter.h] | ||
| + | *[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classitk_1_1LMMSEVectorImageFilterStep.html itkLMMSEVectorImageFilterStep.h] | ||
| + | *[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classitk_1_1MaskedMeanImageFilter.html itkMaskedMeanImageFilter.h] | ||
| + | *[http://www.na-mic.org/Slicer/Documentation/Slicer3-doc/html/classitk_1_1VectorImageCastFilter.html itkVectorImageCastFilter.h] | ||
== More Information == | == More Information == | ||
Revision as of 15:44, 8 May 2010
Home < Modules:RicianLMMSEImageFilter-Documentation-3.6Return to Slicer 3.6 Documentation
Module Name
jointLMMSE
General Information
Module Type & Category
Type: Interactive
Category: CLI/DiffusionApplications
Authors, Collaborators & Contact
- Author: Antonio Tristán Vega and Santiago Aja Fernández
- Contact: atriveg@bwh.harvard.edu
Module Description
This module reduces 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. Images correspondinge to each gradient direction and baseline image are processed individually. The noise parameter is automatically estimated (noise estimation improved but slower). A complete description of the algorithm may be found in "DWI filtering using joint information for DTI and HARDI", Antonio Tristan Vega and Santiago Aja-Fernandez, Medical Image Analysis, Volume 14, Issue 2, Pages 205-218.
Usage
Examples, Use Cases & Tutorials
Quick Tour of Features and Use
It is very easy to use it. Just select a DWI, set the parameters (if you really need it), and you're ready to go.
- Input DWI Volume: set the DWI volume
- Output DWI Volume: the filtered DWI volume
- Estimation radius: This is the 3D radius of the neighborhood used for noise estimation. Noise power is estimated as the mode of the histogram of local variances
- Filtering radius: This is the 3D radius of the neighborhood used for filtering: local means and covariance matrices are estimated within this neighborhood
Development
Dependencies
Volumes. Needed to load DWI volumes
Known bugs
Usability issues
Source code & documentation
Source Code: Follow this link
Doxygen documentation:
- itkComputeRestrictedHistogram.h
- itkComputeStatisticsWherePositiveFilter.h
- itkExtractVolumeFilter.h
- itkLMMSEVectorImageFilter.h
- itkLMMSEVectorImageFilterStep.h
- itkMaskedMeanImageFilter.h
- itkVectorImageCastFilter.h
More Information
Acknowledgment
Antonio Tristan Vega, Santiago Aja Fernandez. University of Valladolid (SPAIN). Partially founded by grant number TEC2007-67073/TCM from the Comision Interministerial de Ciencia y Tecnologia (Spain).
