Alzheimer's disease (AD) is a neurodegenerative disorder that causes cortical atrophy and impaired cognitive
functions. The diagnosis is difficult to make and is often made over a longer period of time using a combination of
neuropsychological tests, and structural and functional imaging. Due to the impact of early intervention the
challenge of distinguishing early AD from normal ageing has received increasing attention. This study uses cortical
thickness measurements to characterize the atrophy in nine mild AD patients (mean MMSE-score 23.3 (std: 2.6))
compared to five healthy middle-aged subjects. A fully automated method based on deformable models is used for
delineation of the inner and outer boundaries of the cerebral cortex from Magnetic Resonance Images. This allows
observer independent high-resolution quantification of the cortical thickness. The cortex analysis facilitates
detection of alterations throughout the entire cortical mantle. To perform inter-subject thickness comparison in
which the spatial information is retained, a feature-based registration algorithm is developed which uses local
cortical curvature, normal vector, and a distance measure. A comparison of the two study groups reveals that the
lateral side of the hemispheres shows diffuse thinner areas in the mild AD group but especially the medial side
shows a pronounced thinner area which can be explained by early limbic changes in AD. For classification principal
component analysis is applied to reduce the high number of thickness measurements (>200,000) into fewer features.
All mild AD and healthy middle-aged subjects are classified correctly (sensitivity and specificity 100%).
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