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Improved Automatic Liver Segmentation of a Contrast Enhanced CT Image

  • Kyung-Sik Seo
  • Jong-An Park
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3767)

Abstract

This paper presents an improved automatic liver segmentation method using a left partial histogram threshold (LPHT) algorithm. The LPHT algorithm removes other neighboring abdominal organs regardless of pixel variation of contrast enhanced computed tomography (CE-CT) images. After histogram transformation, adaptive multi-modal threshold is used to find the range of gray-level values of the liver structure. The LPHT algorithm is performed to removing other neighboring organs. Then, binary morphological filtering is processed to remove unnecessary objects and smooth the boundary. 48 CE-CT slices of twelve patients were selected to test the proposed automatic liver segmentation. As evaluation methods, normalized average area and area error rate were used. The results of experiments show similar performance between the proposed algorithm and the manual method by a medical doctor.

Keywords

Liver Region Contrast Enhanced Compute Tomography Automatic Segmentation Liver Structure Liver Segmentation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Kyung-Sik Seo
    • 1
  • Jong-An Park
    • 1
  1. 1.Dept. of Information & Communications EngineeringChosun UniversityGwangjuKorea

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