Deformation Based Features for Alzheimer's Disease Detection with Linear SVM

Detection of Alzheimer's disease over brain Magnetic Resonance Imaging (MRI) data is a priority goal in the Neurosciences. In previous works we have studied the accuracy of feature vectors obtained from VBM studies of the MRI data. In this paper we report results working on deformation based features, obtained from the deformation vectors computed by non-linear registration processes. Feature selection is based on the correlation between the scalar values computed from the deformation maps and the control variable. Results with linear kernel SVM reach accuracies comparable to previous best results.