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In this paper, we studied the association between the change of structuralbrain volumes to the potential development of Alzheimer's disease (AD). Using asimple abstraction technique, we converted regional cortical and subcorticalvolume differences over two time points for each study subject into a graph. Wethen obtained substructures of interest using a graph decomposition algorithmin order to extract pivotal nodes via multi-view feature selection. Intensiveexperiments using robust classification frameworks were conducted to evaluatethe performance of using the brain substructures obtained under differentthresholds. The results indicated that compact substructures acquired byexamining the differences between patient groups were sufficient todiscriminate between AD and healthy controls with an area under the receiveroperating curve of 0.72.

From Brain Imaging to Graph Analysis: a study on ADNI's patient cohort