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

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[[Image:BrainTissuesExtension-logo.png|left]]
 
[[Image:BrainTissuesExtension-logo.png|left]]
  
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Brain tissue segmentation plays an important role in many different image processing steps, which can offer a possibility to study different parts of the brain in different hypothesis, such as neurodegenerative disease progression and global brain structural quantitative parameters (brain atrophy, for instance). For this reason, tissue segmentation procedures have been intensively studied in the recent years. This extension aims to offer a fast, reliable and simple solutions for brain tissue segmentation, in which are separated in different modules. See the modules list below to find the most appropriate tool for your study.  
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Brain tissue segmentation plays an important role in many different image processing steps, which offers a possibility to study different neurodegenerative disease progression and global brain structural quantitative parameters (brain atrophy, for instance). For this reason, tissue segmentation procedures have been intensively studied in the recent years. This extension aims to offer a fast, robust and simple solutions for brain tissue segmentation, in which are separated in different modules. See the modules list below to find the most appropriate tool for your study.  
  
 
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*[[Documentation/{{documentation/version}}/Modules/BrainStructuresSegmenter|Brain Structures Segmenter]]
 
*[[Documentation/{{documentation/version}}/Modules/BrainStructuresSegmenter|Brain Structures Segmenter]]
 
*[[Documentation/{{documentation/version}}/Modules/BasicBrainTissues|Basic Brain Tissues]]
 
*[[Documentation/{{documentation/version}}/Modules/BasicBrainTissues|Basic Brain Tissues]]
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'''NOTE''': The [[Documentation/{{documentation/version}}/Modules/BrainStructuresSegmenter|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.
  
 
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{{documentation/{{documentation/version}}/module-section|Use Cases}}
 
{{documentation/{{documentation/version}}/module-section|Use Cases}}
 
Most frequently used for these scenarios:
 
Most frequently used for these scenarios:
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* Use Case 1: Specific tissue classification and study
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* Use Case 1: Specific tissue classification
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** There are several quantitative approaches that are applied only in a certain tissue type (for instance, cortical thickness) in which a previous brain segmentation could be needed.
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** 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 areas for image quantitative analysis
 
* Use Case 2: Restrict areas for image quantitative analysis
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** A white matter could be used for specific measurements in some diseases, for example, in Multiple Sclerosis it could be useful to define only the white matter region in order to test a automatic segmentation algorithm.
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** 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.
  
 
<gallery widths="200px" perrow="3">
 
<gallery widths="200px" perrow="3">
 
Image:T1_fullBrain.png|A T1 weighted MRI image illustrating a usual brain
 
Image:T1_fullBrain.png|A T1 weighted MRI image illustrating a usual brain
 
Image:T1_tissues.png|White matter, gray matter and CSF tissues segmented from the previous MRI image
 
Image:T1_tissues.png|White matter, gray matter and CSF tissues segmented from the previous MRI image
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Image:WM_3DReconstruction.png|A 3D reconstruction using only the white matter mask
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Image:WM_3DReconstruction.png|A white matter mask 3D reconstruction  
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Image:GM_3DReconstruction.png|A gray matter mask 3D reconstruction
 
</gallery>
 
</gallery>
  
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{{documentation/{{documentation/version}}/extension-section|References}}
 
{{documentation/{{documentation/version}}/extension-section|References}}
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* paper
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N/A
  
 
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Revision as of 16:25, 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 disease progression and global brain structural quantitative parameters (brain atrophy, for instance). For this reason, tissue segmentation procedures have been intensively studied in the recent years. This extension aims to offer a fast, robust and simple solutions for brain tissue segmentation, in which 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: Specific 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 areas 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.

  • A T1 weighted MRI image illustrating a usual brain

  • White matter, gray matter and CSF tissues segmented from the previous MRI image

  • A white matter mask 3D reconstruction

  • A gray matter mask 3D reconstruction

Similar Extensions

EM Segmenter

References

N/A

Information for Developers

Work in progress
 Section under construction.


Repositories:

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