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

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* 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 [http://www.na-mic.org/ NA-MIC website].
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* Contact: Jim Miller, <email>miller@ge.com</email>
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Revision as of 11:07, 20 October 2011

Home < Documentation < 4.0 < Modules < GradientAnisotropicDiffusion

Rons experiment

  • 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: Jim Miller, <email>miller@ge.com</email>
caption=NA-MIC‎ caption=GE caption=ITK


Begin template

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.
  • Contact: Jim Miller, <email>miller@ge.com</email>
Template:Documentation/4.0/module-introduction-logoTemplate:Documentation/4.0/module-introduction-logoTemplate:Documentation/4.0/module-introduction-logo

Module Description

Template:Documentation/4.0/module-cli-description

Use Cases

Most frequently used for these scenarios:

  • Use Case 1: Noise reduction as a preprocessing step for segmentation
    • when dealing with single voxel classification schemes running noise reduction as a preprocessing scheme will reduce the number of single misclassified voxels.
  • Use Case 2: Preprocessing to volume rendering
    • Noise reduction will result in nicer looking volume renderings

Tutorials

Links to tutorials that use this module

Panels

Template:Documentation/4.0/module-cli-parametersdescription

Panels

  • 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

Information for Developers