Documentation/Nightly/Modules/BVeR

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For the stable Slicer documentation, visit the 4.10 page.

Introduction and Acknowledgements

Extension: Brain Volume Refinement
Webpage: http://dcm.ffclrp.usp.br/csim/
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,

CSIM Laboratory  
University of Sao Paulo  
CAPES Brazil  

Module Description

BVeR-icon.png

This module offers an alternative to manual correction of brain volumes. 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.

Use Cases

  • 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.


Panels and their use

File:Bver icon.png
User Interface


Similar Modules

None

References

  • Insight-Journal...

Information for Developers