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

Kaikai Shen; Pierrick Bourgeat; Jurgen Fripp; Fabrice Meriaudeau; Olivier Salvado

doi:10.1117/12.877869

14 March 2011 Detecting hippocampal shape changes in Alzheimer's disease using statistical shape models

Kaikai Shen, Pierrick Bourgeat, Jurgen Fripp, Fabrice Meriaudeau, Olivier Salvado

Proceedings Volume 7962, Medical Imaging 2011: Image Processing; 796243 (2011) https://doi.org/10.1117/12.877869
Event: SPIE Medical Imaging, 2011, Lake Buena Vista (Orlando), Florida, United States

Abstract

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 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. These predictors also showed better correlation to the cognitive scores such as mini-mental state examination (MMSE) and Alzheimer's disease assessment scale (ADAS).

Citation Download Citation

Kaikai Shen, Pierrick Bourgeat, Jurgen Fripp, Fabrice Meriaudeau, and Olivier Salvado "Detecting hippocampal shape changes in Alzheimer's disease using statistical shape models", Proc. SPIE 7962, Medical Imaging 2011: Image Processing, 796243 (14 March 2011); https://doi.org/10.1117/12.877869

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available