Local manifold learning for multiatlas segmentation: application to hippocampal segmentation in healthy population and Alzheimer's disease.

Aims: Automated hippocampal segmentation is an important issue in many neuroscience studies.

Methods: We presented and evaluated a novel segmentation method that utilized a manifold learning technique under the multiatlas-based segmentation scenario. A manifold representation of local patches for each voxel was achieved by applying an Isomap algorithm, which can then be used to obtain spatially local weights of atlases for label fusion.