Chapter 9. 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 obtain...

Full description

Saved in:
Bibliographic Details
Published inRecent Advances in Biomedical Signal Processing Vol. 1; no. 1; pp. 141 - 148
Main Authors Fernandez, Elsa, Grana, Manuel, Fernandez, Esther, Villanua, Jorge, Saviod, Alexandre, Garcia-Sebastian, Maite, Lopez de Munain, Adolfo, Sistiaga, Andone, Chyzhyk, Darya, Moreno, Fermin
Format Book Chapter
LanguageEnglish
Published 01.09.2011
Subjects
Voxel Based Morphometry
MRI
Myotonic Dystrophy
Support Vector Machines
Online AccessGet full text
DOI10.2174/978160805218911101010141

Cover

More Information
Summary: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.
DOI:10.2174/978160805218911101010141