Graph based MRI brain scan classification and correlation discovery

The shape of the human brain is correlated with many life events and psychological conditions. In this paper, we use a graph-based approach to represent the shape of the brain, including the shape of the ventricular system and shape relative to the skull. This graph representation is applied to classification of individuals based on level of cognitive impairment due to Alzheimer´s Disease, level of education, and gender. The portions of the graph which are important to each distinction are found and visualized as an overlay on structural magnetic resonance images (MRI). We find that whole-brain analysis in this manner allows automatic classification of images based on gender if the whole brain is included, but not strictly based on the ventricular system. Alzheimer´s Disease is found to strongly affect ventricle shape. Education is found to correlate with the shape of the medial longitudinal fissure and the Sylvian fissure, which may be due to increases in overall brain mass due to education. Gender is predicted primarily by information in the MRI regarding facial structure and head shape. Finally, age is found to be easier to classify than any of the above distinctions. The classifier is found to have 90.9% accuracy differentiating scans of individuals 40 and younger from those of individuals 60 or older.