On the Use of Morphometry Based Features for Alzheimer's Disease Detection on MRI

Authors:
Maite García-Sebastián;Alexandre Savio;Manuel Graña;Jorge Villanúa
Affiliations:
Grupo de Inteligencia Computacional,;Grupo de Inteligencia Computacional,;Grupo de Inteligencia Computacional,;Osatek, Hospital Donostia Paseo Dr. Beguiristain 109, San Sebastián, Spain 20014
Venue:
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
Year:
2009

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Abstract

We have studied feature extraction processes for the detection of Alzheimer's disease on brain Magnetic Resonance Imaging (MRI) based on Voxel-based morphometry (VBM). The clusters of voxel locations detected by the VBM were applied to select the voxel intensity values upon which the classification features were computed. We have explored the use of the data from the original MRI volumes and the GM segmentation volumes. In this paper, we apply the Support Vector Machine (SVM) algorithm to perform classification of patients with mild Alzheimer's disease vs. control subjects. The study has been performed on MRI volumes of 98 females, after careful demographic selection from the Open Access Series of Imaging Studies (OASIS) database, which is a large number of subjects compared to current reported studies.