Liver extraction in the abdominal CT image by watershed segmentation algorithm

Pil Un Kim, Yun–Jung Lee, Youngjin Jung, Jin Ho Cho, Myoung Nam Kim

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

4 Scopus citations

Abstract

In this paper, we proposed a liver extracting procedure for computer aided liver diagnosis system. An extraction of liver region is difficult due to interferences of other organs in the abdominal CT image. For this reason, liver region is extracted in ROI. ROI is selected by using the window for measuring the distribution of liver region's Hounsfield Unit in abdominal CT image. The distribution is measured by using an existential probability of liver's value in the window. If the probability of any window exceeded 50%, it would be assigned to ROI. Actually, liver region is not clearly discerned from the adjacent organs as muscle, spleen, and pancreas in abdominal CT image. Liver region is extracted by the watershed segmentation algorithm which is effective in this situation. This segmentation algorithm is very sensitive to the slight variance of contrast. So it generally produces over-segmentation regions. For optimal segmentation these regions are required to merge into the significant regions. Finally, a liver region is selected and extracted by prior information based on anatomic information.

Original languageEnglish
Title of host publicationIFMBE Proceedings
EditorsSun I. Kim, Tae Suk Suh
PublisherSpringer Verlag
Pages2563-2566
Number of pages4
Edition1
ISBN (Print)9783540368397
DOIs
StatePublished - 2007
Event10th World Congress on Medical Physics and Biomedical Engineering, WC 2006 - Seoul, Korea, Republic of
Duration: 27 Aug 20061 Sep 2006

Publication series

NameIFMBE Proceedings
Number1
Volume14
ISSN (Print)1680-0737
ISSN (Electronic)1433-9277

Conference

Conference10th World Congress on Medical Physics and Biomedical Engineering, WC 2006
Country/TerritoryKorea, Republic of
CitySeoul
Period27/08/061/09/06

Keywords

  • Abdominal CT
  • Image processing
  • Liver extraction
  • Watershed segmentation

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