Detecting hippocampal shape changes in Alzheimer's disease using statistical shape models

Kaikai Shen, Pierrick Bourgeat, Jurgen Fripp, Fabrice Meriaudeau, Olivier Salvado, Benoit M. Dawant, David R. Haynor
2011 Medical Imaging 2011: Image Processing  
The hippocampus is affected at an early stage in the development of Alzheimer's disease (AD). Using brain Magnetic Resonance (MR) images, we can investigate the effect of AD on the morphology of the hippocampus. Statistical shape models (SSM) are usually used to describe and model the hippocampal shape variations among the population. We use the shape variation from SSM as features to classify AD from normal control cases (NC). Conventional SSM uses principal component analysis (PCA) to compute
more » ... the modes of variations among the population. Although these modes are representative of variations within the training data, they are not necessarily discriminant on labelled data. In this study, a Hotelling's T 2 test is used to qualify the landmarks which can be used for PCA. The resulting variation modes are used as predictors of AD from NC. The discrimination ability of these predictors is evaluated in terms of their classification performances using support vector machines (SVM). Using only landmarks statistically discriminant between AD and NC in SSM showed a better separation between AD and NC.
doi:10.1117/12.877869 dblp:conf/miip/ShenBFMS11 fatcat:zbonq5sfenf7posu3myazjqz5e