Atlas-based hippocampus segmentation in Alzheimer’s disease and mild cognitive impairment

Purpose. To assess the performance of standard image registration techniques for automated MRI-based segmentation of the hippocampus in elderly subjects with Alzheimer’s Disease (AD) and mild cognitive impairment (MCI). Methods. Structural MR images of 54 age- and gender-matched healthy elderly individuals, subjects with probable AD, and subjects with MCI were collected at the University of Pittsburgh Alzheimer’s Disease Research Center. Hippocampi in subject images were automatically segmented by using AIR, SPM, FLIRT, and the fully-deformable method of Chen to align the images to the Harvard atlas, MNI atlas, and randomly-selected, manually-labeled subject images. Mixed-effects statistical models analyzed the effects of side of the brain, disease state, registration method, choice of atlas, and manual tracing protocol on the agreement between automated segmentations and expert manual segmentations. Results. Registration methods that produced higher degrees of geometric deformation produced automated segmentations with higher agreement with manual segmentations. Automated-manual agreement between Chen’s metho