IMAGE SEGMENTATION VIA MULTI-ATLAS FUSION WITH CONTEXT LEARNING

摘要

Systems and methods are provided for segmenting tissue within a computed tomography (CT) scan of a region of interest into one of a plurality of tissue classes. A plurality of atlases are registered to the CT scan to produce a plurality of registered atlases. A context model representing respective likelihoods that each voxel of the CT scan is a member of each of the plurality of tissue classes is determined from the CT scan and a set of associated training data. A proper subset of the plurality of registered atlases is selected according to the context model and the registered atlases. The selected proper subset of registered atlases are fused to produce a combined segmentation.