Multi-Atlas Label Propagation with Atlas Encoding by Randomized Forests [Special Left Field Award]

We describe our submission to the MICCAI 2013 SATA Challenge. The method is based on multi-atlas based label propagation, its major characteristic being that is uses the concept of an atlas forest to represent an atlas. This results in an efficient scheme, which requires only a single registration to label a target. Fusion of the probabilistic label proposals from each atlas is done by averaging across atlases. Results are submitted for the unregistered Diencephalon data set.