Analysis of ventricle regions in Alzheimer's brain MR images using level set based methods

Abstract

In this work, an attempt has been made to analyse ventricle region of the T1 weighted coronal Magnetic Resonance (MR) brain images and study the progression of severity in Alzheimer’s Disease (AD) conditions. Two level set methods namely Distance Regularised Level Set Evolution (DRLSE) and geodesic active contour are used to extract the desired region of interest. Eighty geometric features are derived from the segmented ventricle region. The most significant parameters are found using principal component analysis. Results demonstrate that the DRLSE shows better performance in extraction of the boundary of the ventricle region than geodesic active contour method. The geometrical feature, area is found to have a high correlation with brain to ventricle index for all subjects. Further, it is observed that this feature gives a distinct separation between normal and abnormal AD subjects (p value = 0.00012). It also provides high correlation for normal (.97) and abnormal AD subjects (<0.9). Hence, this analysis could be a useful supplement to physicians in diagnosis and treatment of Alzheimer’s and other neurodegenerative disorders.