A morphologic analysis of cirrhotic liver in CT images

Yen Wei Chen, Jie Luo, Xianhua Han, Tomoko Tateyama, Akira Furukawa, Shuzo Kanasaki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)


Cirrhosis will cause significant morphological changes on both liver and spleen. In this paper, we constructed not only the liver statistical shape models (SSM), but also the spleen SSM and a joint SSM of the liver and the spleen for a morphologic analysis of the cirrhotic liver in CT images. We also proposed a mode selection method based on both its accumulation contribution rate and its correlation with doctor's opinions (labels). The classification performance for normal and abnormal livers is significantly improved by our proposed method. The classification accuracies for normal and cirrhotic livers are 88% and 90%, respectively.

Original languageEnglish
Title of host publicationImage Analysis and Recognition - 10th International Conference, ICIAR 2013, Proceedings
Number of pages8
Publication statusPublished - 2013
Externally publishedYes
Event10th International Conference on Image Analysis and Recognition, ICIAR 2013 - Povoa do Varzim, Portugal
Duration: 26-06-201328-06-2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7950 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference10th International Conference on Image Analysis and Recognition, ICIAR 2013
CityPovoa do Varzim

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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