Shape analysis of brain ventricles for improved classification of alzheimer's patients

One of the hallmarks of Alzheimer's disease (AD) is the loss of neurons in the brain. In many cases, the medical experts use MR (magnetic resonance) images to qualitatively measure the neuronal loss by the shrinkage (atrophy) of the structures-of-interest, or sometimes more easily by the enlargement of the fluid-filled structures, such as the ventricles. For quantitative analysis, volume is the common choice. Volume, or area in 2D, is a gross measure and it cannot capture shape differences that can improve the diagnostic accuracy. Because most existing methods use complex and difficult-to-reproduce shape descriptors, the experts prefer more easily and robustly extractable area and volume in their diagnosis. In this paper, we introduce several novel and easily-extractable 2D shape descriptors for brain ventricle, and show that they and some of the well-known simple shape descriptors, such as perimeter, are better descriptors in the classification of AD patients and healthy controls.