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Proceedings Paper

An automatic method for fast and accurate liver segmentation in CT images using a shape detection level set method
Author(s): Jeongjin Lee; Namkug Kim; Ho Lee; Joon Beom Seo; Hyung Jin Won; Yong Moon Shin; Yeong Gil Shin
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Paper Abstract

Automatic liver segmentation is still a challenging task due to the ambiguity of liver boundary and the complex context of nearby organs. In this paper, we propose a faster and more accurate way of liver segmentation in CT images with an enhanced level set method. The speed image for level-set propagation is smoothly generated by increasing number of iterations in anisotropic diffusion filtering. This prevents the level-set propagation from stopping in front of local minima, which prevails in liver CT images due to irregular intensity distributions of the interior liver region. The curvature term of shape modeling level-set method captures well the shape variations of the liver along the slice. Finally, rolling ball algorithm is applied for including enhanced vessels near the liver boundary. Our approach are tested and compared to manual segmentation results of eight CT scans with 5mm slice distance using the average distance and volume error. The average distance error between corresponding liver boundaries is 1.58 mm and the average volume error is 2.2%. The average processing time for the segmentation of each slice is 5.2 seconds, which is much faster than the conventional ones. Accurate and fast result of our method will expedite the next stage of liver volume quantification for liver transplantations.

Paper Details

Date Published: 26 March 2007
PDF: 8 pages
Proc. SPIE 6512, Medical Imaging 2007: Image Processing, 65122V (26 March 2007); doi: 10.1117/12.710175
Show Author Affiliations
Jeongjin Lee, Seoul National Univ. (South Korea)
Namkug Kim, Univ. of Ulsan College of Medicine, Asan Medical Ctr. (South Korea)
Ho Lee, Seoul National Univ. (South Korea)
Joon Beom Seo, Univ. of Ulsan College of Medicine, Asan Medical Ctr. (South Korea)
Hyung Jin Won, Univ. of Ulsan College of Medicine, Asan Medical Ctr. (South Korea)
Yong Moon Shin, Univ. of Ulsan College of Medicine, Asan Medical Ctr. (South Korea)
Yeong Gil Shin, Seoul National Univ. (South Korea)

Published in SPIE Proceedings Vol. 6512:
Medical Imaging 2007: Image Processing
Josien P. W. Pluim; Joseph M. Reinhardt, Editor(s)

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