Difference between revisions of "Documentation/Nightly/Extensions/BrainTissuesExtension"

From Slicer Wiki
Jump to: navigation, search
m
m
Line 50: Line 50:
 
Image:WM_3DReconstruction.png|A white matter mask 3D reconstruction  
 
Image:WM_3DReconstruction.png|A white matter mask 3D reconstruction  
 
Image:GM_3DReconstruction.png|A gray matter mask 3D reconstruction
 
Image:GM_3DReconstruction.png|A gray matter mask 3D reconstruction
 +
Image:WM_GM_3DReconstruction.png|A merge white and gray matter masks 3D reconstruction
 
</gallery>
 
</gallery>
  

Revision as of 16:55, 26 November 2016

Home < Documentation < Nightly < Extensions < BrainTissuesExtension


For the latest Slicer documentation, visit the read-the-docs.


Introduction and Acknowledgements

This work was partially funded by CAPES and CNPq, a Brazillian Agencies. Information on CAPES can be obtained on the CAPES website and CNPq website.
Author: Antonio Carlos da S. Senra Filho, CSIM Laboratory (University of Sao Paulo, Department of Computing and Mathematics)
Contact: Antonio Carlos da S. Senra Filho <email>acsenrafilho@usp.br</email>

CSIM Laboratory  
University of Sao Paulo  
CNPq Brazil  
CAPES Brazil  


Extension Description

BrainTissuesExtension-logo.png

Brain tissue segmentation plays an important role in many different image processing steps, which offers a possibility to study different neurodegenerative diseases or also in more specific tasks such as in brain structural quantitative parameters (brain atrophy, for instance). For this reason, brain tissue segmentation procedures have been intensively studied in recent years. This extension aims to offer a fast, robust and simple solutions for brain tissue segmentation, in which specific segmentation tasks are separated in different modules. See the modules list below to find the most appropriate tool for your study.


Modules

NOTE: The Brain Structures Segmenter is the main module for a general brain segmentation approach, which uses a predefined image processing pipeline in order to result in a smoothed tissue mask. See the module's documentation for more details.

Use Cases

Most frequently used for these scenarios:

  • Use Case 1: Tissue classification
    • There are several image quantitative approaches that are applied only in a certain tissue type (for instance, cortical thickness) in which a previous brain segmentation could be needed.
  • Use Case 2: Restrict brain regions for image quantitative analysis
    • A white matter mask could be used for specific measurements in some brain diseases, for example, in Multiple Sclerosis it could be useful to help lesion detection algorithms.

Similar Extensions

EM Segmenter

References

N/A

Information for Developers


Repositories: