Modules:UnbiasedNonLocalMeans-Documentation-3.4
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Module Name
UnbiasedNonLocalMeans
General Information
Module Type & Category
Type: Interactive
Category: CLI/DiffusionApplications
Authors, Collaborators & Contact
- Author: Antonio Tristán Vega , Santiago Aja Fernández
- Contact: atriveg@bwh.harvard.edu
Module Description
Filters a set of diffusion weighted images using Unbiased Non Local Means for Rician noise. It exploits not only the spatial redundancy, but the redundancy in similar gradient directions as well; it takes into account the N closest gradient directions to the direction being processed (a maximum of 5 gradient directions is allowed to keep a reasonable computational load, since we do not use neither similarity maps nor block-wise implementation). The noise parameter is automatically estimated. A complete description of the algorithm may be found in "DWI filtering using joint information for DTI and HARDI", by Antonio Tristan Vega and Santiago Aja-Fernandez (under review).
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
Development
Dependencies
Volumes. Needed to load DWI volumes
Known bugs
Usability issues
This filter is painfully slow. May take hours.
Source code & documentation
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).
