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Abstract #4047

Deformation Based Classification of Alzheimer’s Disease

Thomas Bonde Larsen1, Akshay Pai1, and Sune Darkner1

1Computer Science, University of Copenhagen, Copenhagen, Denmark

Effective and accurate diagnosis of Alzheimer’s disease (AD) purely based on structural magnetic resonance imaging (MRI) is a very pertinent clinical problem. We present a simple but highly accurate registration-based method to discriminate between the three classes of healthy controls (HC), mild cognitively impaired (MCI) and AD. The method uses the norm of the tangent space of the deformation in a K-nearest neighbor KNN classifier. The result show that for 60 subjects, 20 in each class using n-fold cross-validation an overall accuracy of 81.6% with 75% for HC, 85% MCI and 85% for AD.

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