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

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.

Modules

Use Cases

Most frequently used for these scenarios:

Use Case 1: Specific tissue classification and study
- 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.
Use Case 2: Restrict areas for image quantitative analysis
- 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.