Difference between revisions of "Documentation/4.0/Modules/GradientAnisotropicDiffusion"

From Slicer Wiki
Jump to: navigation, search
Line 14: Line 14:
  
 
=Module Description=
 
=Module Description=
−
Runs the ITK gradient anisotropic diffusion filter on a volume.
+
{{module:cli:generaldescription|xmlurl={{module:cli:xmlurl|GradientAnisotropicDiffusion|17347}} }}
−
 
 
−
Anisotropic diffusion methods reduce noise (or unwanted detail) in images while preserving specific image features, like edges.  For many applications, there is an assumption that light-dark transitions (edges) are interesting. Standard isotropic diffusion methods move and blur light-dark boundaries. Anisotropic diffusion methods are formulated to specifically preserve edges. The conductance term for this implementation is a function of the gradient magnitude of the image at each point, reducing the strength of diffusion at edges.
 
−
 
 
−
The numerical implementation of this equation is similar to that described in the Perona-Malik paper, but uses a more robust technique for gradient magnitude estimation and has been generalized to N-dimensions.
 
  
 
[[Module:EndUserDocumentationTemplate-4.0#References|See references]] for more details on the algorithm.
 
[[Module:EndUserDocumentationTemplate-4.0#References|See references]] for more details on the algorithm.

Revision as of 18:35, 24 August 2011

Home < Documentation < 4.0 < Modules < GradientAnisotropicDiffusion

Template:Module:documentationheader

Introduction and Acknowledgements

GradientAnisotropicFilter
  • 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.
  • Contact: millerjv at ge.crd
NA-MIC
ITK

Module Description

Template:Module:cli:generaldescription

See references for more details on the algorithm.

Use Cases

Most frequently used for these scenarios:

  • Use Case 1: Noise reduction as a preprocessing step for segmentation
  • Use Case 2: Preprocessing to volume rendering

Tutorials

Links to tutorials that use this module

Panels

Template:Module:cli:parametersdescription

Similar Modules

  • Point to other modules that have similar functionality

References

Publications related to this module go here. Links to pdfs would be useful. For extensions: link to the source code repository and additional documentation

Template:Module:developerinfo