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Introduction and Acknowledgements

Acknowledgments: 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,

CSIM Laboratory  
University of Sao Paulo  
CNPq Brazil  
CAPES Brazil  

Extension Description


Multiple sclerosis (MS) is a degenerative neurological disease growing relevance. The segmentation of lesions on magnetic resonance imaging (MRI) and its boundaries with healthy tissue remains a challenge for correct diagnosis of MS patients. Currently, many imaging methods Magnetic resonance imaging have been applied to this problem, but with success modest.The diffusion tensor imaging (DTI) have been discussed as an important imaging technique which could be useful for the diagnosis of MS. However, main barrier is the low signal to noise ratio (SNR) existing in such imaging techniques, which eventually diminish the efficiency of the method of segmentation. This extension aims to provide image processing tools in order to segment and detect MS lesions and the surrounding NAWM in the patient disease progression.


Use Cases

Sample data to use with modules.


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