Recent Advances in Biomedical Signal Processing

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Biomedical signal processing is a rapidly expanding field with a wide range of applications, from the construction of artificial limbs and aids for disabilities to the development of sophisticated ...
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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

Abstract

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.

Keywords:

Myotonic Dystrophy, Support Vector Machines, Voxel Based Morphometry, MRI

Affiliation:

Departamento de Neurociencias, UPV/EHU.