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

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Revision as of 07:15, 14 September 2019

Home < Documentation < Nightly < Extensions < BrainVolumeRefinement


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


Introduction and Acknowledgements

This work was partially funded by CAPES and CNPq, Brazilian Agencies. Information on CAPES can be obtained on the CAPES website and CNPq website.
Authors: Antonio Carlos da S. Senra Filho, CSIM Laboratory (University of Sao Paulo, Department of Computing and Mathematics)
Fabrício Henrique Simozo, CSIM Laboratory (University of Sao Paulo, Department of Computing and Mathematics)
Prof. Luiz Otávio Murta Junior, 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

BVeR-logo.png

The Brain Volume Refinement (BVeR) extension is designed to assist neuroscience studies. The BVeR algorithm is suitable for a broad use of healthy brain structural MRI images, e.g. T1w and T2w, offering broad application in many large data analyses. The main contribution of the proposed method is related to the reduction of manual interference in the brain volume refinement after an automatic skull stripping procedure been performed, helping to reduce human errors and processing time. Even though the BVeR method does not provide a fully brain extraction algorithm, it can be helpful as a ad hoc image processing step in which increase the quality of well-known brain extraction algorithm in the literature. Any brain extracting frameworks can be refined with this method, e.g. FSL-BET, FreeSurfer, BEasT, 3DSkullStrip, ROBEX, OptiBET and many others.

Modules

  • Structural T1w and T2w brain volume correction: BVeR

Use Cases

Most frequently used for these scenarios:

  • Use Case 1: Cortical thickness surface delineation.
    • When dealing with grey-matter overestimate due to badly brain extraction step.
  • Use Case 2: Brain atrophy
    • Assist in the total brain volume estimate also reducing the non-brain tissues belonging outside the grey-matter tissue frontier.

Similar Extensions

  • NA

References

  • Insight-Journal

Information for Developers


Repositories: