Semi-automatic liver tumor segmentation with hidden Markov measure field model and non-parametric distribution estimation

► Method produces accurate segmentations of liver tumors from low-quality data. ► Only minimal user interaction is required. ► Highest score for benchmark data set, with average overlap error of 30.35%. ► Multiphase segmentation uses several images and adds robustness to the method. ► Novel post-processing method removes extraneous regions.