Machine Learning Approach for Myotonic Dystrophy Diagnostic Support from MRI

In this paper we report the application of a Machine Learning approach to research support in Myotonic Dystrophy (MD) from structural Magnetic Resonance Imaging (sMRI). The approach consists of a feature extraction process based on the results of Voxel Based Morphometry (VBM) analysis of sMRI obtained from a set of patient and control subjects, followed by a classification step performed by Support VectorMachine (SVM) classifiers trained on the features extracted from the data set.