Difference between revisions of "Documentation/Nightly/Modules/BrainTissuesMask"

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This work was partially funded by CAPES and CNPq (grant 201871/2015-7/SWE), a Brazilian research support agency. Information on CAPES can be obtained from the official websites, [http://www.capes.gov.br/ CAPES here] and [http://www.cnpq.br/ CAPES here].<br>
 
This work was partially funded by CAPES and CNPq (grant 201871/2015-7/SWE), a Brazilian research support agency. Information on CAPES can be obtained from the official websites, [http://www.capes.gov.br/ CAPES here] and [http://www.cnpq.br/ CAPES here].<br>
Author: Antonio Carlos da S. Senra Filho, CSIM Laboratory<br>
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Author: Antonio Carlos da S. Senra Filho, CSIM Laboratory (University of Sao Paulo, Department of Computing and Mathematics)<br>
 
Contact: Antonio Carlos da S. Senra Filho <email>acsenrafilho@usp.br</email><br>
 
Contact: Antonio Carlos da S. Senra Filho <email>acsenrafilho@usp.br</email><br>
 
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|Image:CSIM-logo.png|CSIM Laboratory  
 
|Image:CSIM-logo.png|CSIM Laboratory  
 
|Image:USP-logo.png|University of Sao Paulo
 
|Image:USP-logo.png|University of Sao Paulo
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|Image:CNPq-logo.png|CNPq Brazil
 
|Image:CAPES-logo.png|CAPES Brazil
 
|Image:CAPES-logo.png|CAPES Brazil
 
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[[Image:BrainTissuesMask-logo.png|left]]
 
[[Image:BrainTissuesMask-logo.png|left]]
  
Description...
 
  
 
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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:
* Use Case 1: Noise reduction as a preprocessing step for tissue segmentation
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* Use Case 1: Initial image processing step for many neuroimage analysis, such as in DTI and cortical thickness estimation.
**When dealing with single voxel classification schemes running noise reduction as a preprocessing scheme will reduce the number of single misclassified voxels.
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**It would be useful for tissue classication.
* 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
 
  
 
<gallery>
 
<gallery>
Image:BrainMNI_orig.png|MNI152 T1 brain image
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Image:Brain_T1_orig.png|T1w MRI
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Image:Brain_tissues.png|Brain gray matter, white matter and CSF tissues
 
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</gallery>
  
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{{documentation/{{documentation/version}}/module-section|Tutorials}}
 
{{documentation/{{documentation/version}}/module-section|Tutorials}}
* Usage:
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** Load the downloaded .mrb scene file into Slicer
 
** Go to the Sequence browser module to browse the data set
 
  
 
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{{documentation/{{documentation/version}}/module-section|Panels and their use}}
{{documentation/{{documentation/version}}/module-parametersde
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|[[Image:braintissuesmask_gui.png|thumb|380px|User Interface]]
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Revision as of 23:17, 22 April 2016

Home < Documentation < Nightly < Modules < BrainTissuesMask


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


Introduction and Acknowledgements

This work was partially funded by CAPES and CNPq (grant 201871/2015-7/SWE), a Brazilian research support agency. Information on CAPES can be obtained from the official websites, CAPES here and CAPES here.
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  

Module Description


Use Cases

Most frequently used for these scenarios:

  • Use Case 1: Initial image processing step for many neuroimage analysis, such as in DTI and cortical thickness estimation.
    • It would be useful for tissue classication.


Tutorials

Panels and their use

User Interface


Similar Modules

References

Repositories: