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

  • Maite García-Sebastián
  • Alexandre Savio
  • Manuel Graña
  • Jorge Villanúa
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5517)

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.

Keywords

Support Vector Machine Radial Basis Function Kernel Voxel Intensity Feature Extraction Process Magnetic Resonance Image Volume 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Maite García-Sebastián
    • 1
  • Alexandre Savio
    • 1
  • Manuel Graña
    • 1
  • Jorge Villanúa
    • 2
  1. 1.Grupo de Inteligencia ComputacionalSpain
  2. 2.Osatek, Hospital Donostia Paseo Dr. Beguiristain 109San SebastiánSpain

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