PROBABILISTIC REFINEMENT OF MODEL-BASED SEGMENTATION

摘要

A system for segmenting current diagnostic images includes a workstation (30) which segments a volume of interest in previously generated diagnostic images of a selected volume of interest generated from a plurality of patients. One or more processors (32) are programmed to register the segmented previously generated images and merge the segmented previously generated images into a probability map that depicts a probability that each voxel represents the volume of interest (24) or background (26) and a mean segmentation boundary (40). A segmentation processor (50) registers the probability map with a current diagnostic image (14) to generate a transformed probability map (62). A previously-trained classifier (70) classifies voxels of the diagnostic image with a probability that each voxel depicts the volume of interest or the background. A merge processor (80) merges the probabilities from the classifier and the transformed probability map. A segmentation boundary processor (84) determines the segmentation boundary for the volume of interest based on the current image based on the merge probabilities.