Semi-automatic Segmentation of the Liver and its Evaluation on the MICCAI 2007 Grand Challenge Data Set

Abstract

Abstract. In this paper, we evaluate a semi-automatic liver segmentation method based on a level-set approach and a dynamically adapted speed func-tion. The approach also relies on a-priori anatomic information to reduce leak-age at the liver-rib interface. The numerical algorithms have been integrated into a complete system that permits loading DICOM images, segmenting these images, and visualizing the liver surface. Although the normal operation of the system assumes manual contour corrections, such corrections were not allowed for this evaluation. Results show that except for cases with large tumors that ex-tend to the liver surface, the method we propose is comparable to a human rater. 1.