Application of computational anatomy methods to MRI data for the diagnosis of Alzheimer´S disease

In this paper we propose a new method for quantification of the rate of brain tissue deformation of patients with neurode-generative diseases. Our method allows for generating intermediary (virtual) MR brain volumes from real scans. In addition, we introduce two new descriptor spaces: (i) joint brain tissue deformation displacement vector magnitude and Jacobian and (ii) joint polar angles of displacement vector. In order to conduct our analysis, we built a visualization environment that illustrates images and flows, and it quantifies parameters. Through the calculation of the parameters, of the intermediary MR volumes, we create N-fold information simulating the deformation process. While our method is suitable for every neurodegenerative disease, we empirically tested our scheme on patients with diagnosed Alzheimer´s disease, mild cognitive impairment and normal controls from the ADNI database. We focus on regions containing either ventricles or hippocampus. A distinction between different subjects could clearly be made.