Hippocampal atrophy rate using an expectation maximization classifier with a disease-specific prior

Hippocampal atrophy is a well-known characteristic associated with Alzheimer's disease. In this work, we propose a 4D Expectation Maximization framework for measuring the atrophy rate of the hippocampus from serial magnetic resonance images. One novelty of the framework is a disease-specific prior that regularizes the segmentation near the borders of the hippocampus. Regions where the hippocampus tends to get larger in the follow-up images than in the baseline are penalized. Using the ADNI cohort, we obtained classification accuracies of 83% for healthy control and Alzheimer's disease patient groups and 60% for stable and progressive MCI groups using the baseline and 12-month follow-up images.