Machine Learning Approach for Myotonic Dystrophy Diagnostic Support from MRI
Pp. 141-148 (8)
Alexandre Savio, Maite Garcia-Sebastian, Andone Sistiaga, Darya Chyzhyk, Esther Fernandez, Fermin Moreno, Elsa Fernandez, Manuel Grana, Jorge Villanua and Adolfo Lopez de Munain
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.
Myotonic Dystrophy, Support Vector Machines, Voxel Based Morphometry, MRI
Departamento de Neurociencias, UPV/EHU.