A Hybrid Model for Liver Shape Segmentation with Customized Fast Marching and Improved GMM-EM

  • Weizhuo Huang
  • Yinwei ZhanEmail author
  • Rongqian Yang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11902)


This paper describes an approach to segment liver shape from abdominal CT sequences, required by the analysis of liver diseases. A rough segmentation is first conducted via a customized Fast Marching method to obtain an approximate 3D liver region for subsequent procedure. Then, an improvement of GMM-EM algorithm is made to extract the accurate liver region. Experimental results, evaluated on non-tumor series and tumor series of 10 cases, show that the proposed method performs better than several other typical segmentation models in running time and precision.


Liver segmentation Fast Marching GMM-EM K-means++ 



This work is supported by the Science and Technology Planning Project of Guangdong Province with grant numbers 2017B010110007 and 2017B010110015.


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of ComputerGuangdong University of TechnologyGuangzhouChina
  2. 2.School of Materials Science and EngineeringSouth China University of TechnologyGuangzhouChina

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