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Liver Segmentation from CT Images Using a Modified Distance Regularized Level Set Model Based on a Novel Balloon Force

Authors

Nuseiba M. Altarawneh1, SuhuaiLuo1, Brian Regan1 and Changming Sun2, 1The University of Newcastle, Australia and 2CSIRO, Australia

Abstract

Organ segmentation from medical images is still an open problem and liver segmentation is a much more challenging task among other organ segmentations. This paper presents a liver segmentation method from a sequence of computer to mography images.We propose a novel balloon force that controls the direction of the evolution process and slows down the evolving contour in regions with weak or without edges and discourages the evolving contour from going far away from the liver boundary or from leaking at a region that has a weak edge, or does not have an edge. The model is implemented using a modified Distance Regularized Level Set (DRLS) model. The experimental results show that the method can achieve a satisfactory result. Comparing with the original DRLS model, our model is more effective in dealing with over segmentation problems.

Keywords

Liver segmentation, level set method, Distance Regularized Level Set (DRLS) model

Full Text  Volume 4, Number 12