Documentation/Nightly/Extensions/DiffusionComplexityMap

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Introduction and Acknowledgements

This work was funded by University of Campinas, Brazil. More information on the website Unicamp website. Author: Antonio Carlos da S. Senra Filho, LOAMRI Laboratory (University of Campinas, Department of Cosmic Rays and Chronology ) Author: Andre Monteiro Paschoal, LOAMRI Laboratory (University of Campinas, Department of Cosmic Rays and Chronology ) Author: Luiz Otávio Murta Junior, CSIM Laboratory (University of Sao Paulo, Department of Computing and Mathematics ) Contact: Antonio Carlos da S. Senra Filho <email>acsenrafilho@alumni.usp.br</email>

CSIM Laboratory   LOAMRI Laboratory   University of Campinas   University of Sao Paulo

Extension Description

XXX .

Modules

• Diffusion Complexity Map (DC): DC Mapping

Use Cases

• Use Case 1: Noise reduction as a preprocessing step for tissue 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
• Use Case 3: Noise reduction as part of image processing pipeline
  • Could offer a better segmentation and classification on specific brain image analysis such as in Multiple Sclerosis lesion segmentation

• 

  Raw T1 weighted MRI Image

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  T1 weighted MRI Image with AAD filter (q=1.2)

Similar Modules

• IAD Image Filter TODO Colocar outros links

References

• Manuscript in review process

Information for Developers

Repositories:

• Source code: GitHub repository
• Issue tracker: open issues and enhancement requests