Journal of Korea Multimedia Society (한국멀티미디어학회논문지)
- Volume 9 Issue 12
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- Pages.1588-1595
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- 2006
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- 1229-7771(pISSN)
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- 2384-0102(eISSN)
Segmentation of Liver Regions in the Abdominal CT Image by Multi-threshold and Watershed Algorithm
- Kim, Pil-Un (Dept. of Medical & Biological Eng., Graduate School, Kyungpook National University) ;
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Lee, Yun-Jung
(Dept. of Medical & Biological Eng., Graduate School, Kyungpook National University) ;
- Kim, Gyu-Dong (Dept. of Medical & Biological Eng., Graduate School, Kyungpook National University) ;
- Jung, Young-Jin (Dept. of Medical & Biological Eng., Graduate School, Kyungpook National University) ;
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Cho, Jin-Ho
(Dept. of Biomedical Eng., School of Medicine, Kyungpook National University) ;
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Chang, Yong-Min
(Dept. of Radiology, School of Medicine, Kyungpook National University) ;
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Kim, Myoung-Nam
(Dept. of Biomedical Eng., School of Medicine, Kyungpook National University)
- Published : 2006.12.30
Abstract
In this paper, we proposed a liver extracting procedure for computer aided liver diagnosis system. Extraction of liver region in an abdominal CT image is difficult due to interferences of other organs. For this reason, liver region is extracted in a region of interest(ROI). ROI is selected by the window which can measure the distribution of Hounsfield Unit(HU) value of liver region in an abdominal CT image. The distribution is measured by an existential probability of HU value of lever region in the window. If the probability of any window is over 50%, the center point of the window would be assigned to ROI. Actually, liver region is not clearly discerned from the adjacent organs like muscle, spleen, and pancreas in an abdominal CT image. Liver region is extracted by the watershed segmentation algorithm which is effective in this situation. Because it is very sensitive to the slight valiance of contrast, it generally produces over segmentation regions. Therefore these regions are required to merge into the significant regions for optimal segmentation. Finally, a liver region can be selected and extracted by prier information based on anatomic information.