Segmentation of Kidneys and Pelvic Organs from CT by Posterior Optimization of M-reps
Stephen M. Pizer, Edward L. Chaney, Robert E. Broadhurst, Xifeng Fang, Ja-Yeon Jeong, Joshua V. Stough, Gregg S. Tracton · 2006
Kidneys from multi-patient populations and pelvic organs from multi-day populations from a single patient were segmented by training a prior on m-rep shape and a likelihood function on regional histogram quantiles and then optimizing the posterior, finding the most probable m-rep given the image intensities. The results are compared to human segmentations and show that the log posterior objective function provides segmentations in as good or better agreement with humans than the humans agree with each other.