Abstract
Magnetic resonance image texture analysis (MRI-TA) has been already demonstrated as a powerful tool to extract image information better than visual examination of grey levels. Human muscular dystrophy is a disease of which diagnosis is rather easy but it remains a lack of atraumatic methods for its follow-up as well as for the management of treatments presently in progress. MRI appears to be a potential tool for disease follow-up and treatment monitoring. The present study is part of the European project MYO-MRI (http://myo-mri.eu/) aimed at improving diagnosis and understanding of muscle pathology. This paper focuses on the use of Legendre and Zernike moment-based texture analysis of MRI T2-weighted images to follow from 2 to 14 months 5 healthy and 5 Golden Retriever Muscular Dystrophy Dogs (GRMD), acknowledged to be the most accurate animal model available for human Duchenne Muscular Dystrophy. Regions-Of-Interest (ROIs) were characterized by moments and the features so extracted were analyzed by Principal Component Analysis and classified by means of Support Vector Machine. The preliminary results show relevant discriminations between dogs populations in reference to disease status and evolution.
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