Preliminary study on statistical shape model applied to diagnosis of liver cirrhosis

Shinya Kohara, Tomoko Tateyama, Amir Hossein Foruzan, Akira Furukawa, Shuzo Kanasaki, Makoto Wakamiya, Xiong Wei, Yen Wei Chen

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

14 Citations (Scopus)

Abstract

In computational anatomy, statistical shape model (SSM) is used for the quantitative evaluation of variations in the shapes of different organs. This paper focuses on the construction of a SSM of the liver and its application to computer-assisted diagnosis of cirrhosis. We prove the potential application of SSMs in the classification of normal and cirrhotic livers. In constructing a SSM of the liver, we first normalize volume data followed by the construction of the model using principal component analysis. The coefficients of the model are used as indicators of liver pathology. The effectiveness of the constructed model is evaluated by the classification accuracy of both normal and abnormal data.

Original languageEnglish
Title of host publicationICIP 2011
Subtitle of host publication2011 18th IEEE International Conference on Image Processing
Pages2921-2924
Number of pages4
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event2011 18th IEEE International Conference on Image Processing, ICIP 2011 - Brussels, Belgium
Duration: 11-09-201114-09-2011

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Conference

Conference2011 18th IEEE International Conference on Image Processing, ICIP 2011
Country/TerritoryBelgium
CityBrussels
Period11-09-1114-09-11

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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