A novel graph cuts based liver segmentation method

Hongzhe Yang*, Yongtian Wang, Jian Yang, Yue Liu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

This paper presents a novel liver segmentation method based on the fast marching and graph cuts methods. The algorithm is composed of three main steps: first, rough edge of the liver is extracted from the CT image by fast marching method. Second, hard constrain of the foreground and background which is used for initial calculation of graph cut is obtained by mathematical morphology method. Third, based on the former calculation, the graph cuts are utilized to refine the segmentation boundary of the liver. The developed method greatly reduces the complexity of the commonly used graph cuts methods, which can obtain the hard constrains automatically. Also, the developed method reduces the dependence of empirical parameters of the fast marching based method. Experimental results show that the developed method is very effective for the segmentation of liver from CT images.

Original languageEnglish
Title of host publication2010 International Conference on Medical Image Analysis and Clinical Application, MIACA 2010
Pages50-53
Number of pages4
DOIs
Publication statusPublished - 2010
Event2010 International Conference on Medical Image Analysis and Clinical Application, MIACA 2010 - Guangzhou, Guangdong, China
Duration: 11 Jun 201013 Jun 2010

Publication series

Name2010 International Conference on Medical Image Analysis and Clinical Application, MIACA 2010

Conference

Conference2010 International Conference on Medical Image Analysis and Clinical Application, MIACA 2010
Country/TerritoryChina
CityGuangzhou, Guangdong
Period11/06/1013/06/10

Fingerprint

Dive into the research topics of 'A novel graph cuts based liver segmentation method'. Together they form a unique fingerprint.

Cite this