Results of an Adaboost Approach on Alzheimer's Disease Detection on MRI

Abstract. In this paper we explore the use of the Voxel-based Morphometry (VBM) detection clusters to guide the feature extraction processes for the detection of Alzheimer's disease on brain Magnetic Resonance Imaging (MRI). The voxel location detection clusters given by the VBM were applied to select the voxel values upon which the classication features were computed. We have evaluated feature vectors computed over the data from the original MRI volumes and from the GM segmentation volumes, using the VBM clusters as voxel selection masks. We use the Support Vector Machine (SVM) algorithm to perform classication of patients with mild Alzheimer's disease vs. control subjects. We have also considered combinations of isolated cluster based classiers and an Adaboost strategy applied to the SVM built on the feature vectors. The study has been performed on MRI volumes of 98 females, after careful demographic selection from the Open Access Series of Imaging Studies (OASIS) databa...

• Type: Conference
• Year: 2009
• Where: IWINAC
• Authors: Alexandre Savio, Maite García-Sebastián, Manuel Graña, Jorge Villanúa
• Keywords: Detection Clusters, Feature Vectors, IWINAC 2009, MRI Volumes