Relaxation time based classification of magnetic resonance brain images

Fabio Baselice; Giampaolo Ferraioli; Vito Pascazio

doi:10.1117/12.2082263

20 March 2015 Relaxation time based classification of magnetic resonance brain images

Fabio Baselice, Giampaolo Ferraioli, Vito Pascazio

Author Affiliations +

Proceedings Volume 9413, Medical Imaging 2015: Image Processing; 941341 (2015) https://doi.org/10.1117/12.2082263
Event: SPIE Medical Imaging, 2015, Orlando, Florida, United States

Abstract

Brain tissue classification in Magnetic Resonance Imaging is useful for a wide range of applications. Within this manuscript a novel approach for brain tissue joint segmentation and classification is presented. Starting from the relaxation time estimation, we propose a novel method for identifying the optimal decision regions. The approach exploits the statistical distribution of the involved signals in the complex domain. The technique, compared to classical threshold based ones, is able to improve the correct classification rate. The effectiveness of the approach is evaluated on a simulated case study.

Citation Download Citation

Fabio Baselice, Giampaolo Ferraioli, and Vito Pascazio "Relaxation time based classification of magnetic resonance brain images", Proc. SPIE 9413, Medical Imaging 2015: Image Processing, 941341 (20 March 2015); https://doi.org/10.1117/12.2082263

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