5 March 2007 Segmentation of liver region with tumorous tissues
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Segmentation of an abnormal liver region based on CT or MR images is a crucial step in surgical planning. However, precisely carrying out this step remains a challenge due to either connectivities of the liver to other organs or the shape, internal texture, and homogeneity of liver that maybe extensively affected in case of liver diseases. Here, we propose a non-density based method for extracting the liver region containing tumor tissues by edge detection processing. False extracted regions are eliminated by a shape analysis method and thresholding processing. If the multi-phased images are available then the overall outcome of segmentation can be improved by subtracting two phase images, and the connectivities can be further eliminated by referring to the intensity on another phase image. Within an edge liver map, tumor candidates are identified by their different gray values relative to the liver. After elimination of the small and nonspherical over-extracted regions, the final liver region integrates the tumor region with the liver tissue. In our experiment, 40 cases of MDCT images were used and the result showed that our fully automatic method for the segmentation of liver region is effective and robust despite the presence of hepatic tumors within the liver.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xuejun Zhang, Xuejun Zhang, Gobert Lee, Gobert Lee, Tetsuji Tajima, Tetsuji Tajima, Teruhiko Kitagawa, Teruhiko Kitagawa, Masayuki Kanematsu, Masayuki Kanematsu, Xiangrong Zhou, Xiangrong Zhou, Takeshi Hara, Takeshi Hara, Hiroshi Fujita, Hiroshi Fujita, Ryujiro Yokoyama, Ryujiro Yokoyama, Hiroshi Kondo, Hiroshi Kondo, Hiroaki Hoshi, Hiroaki Hoshi, Shigeru Nawano, Shigeru Nawano, Kenji Shinozaki, Kenji Shinozaki, } "Segmentation of liver region with tumorous tissues", Proc. SPIE 6512, Medical Imaging 2007: Image Processing, 651235 (5 March 2007); doi: 10.1117/12.709272; https://doi.org/10.1117/12.709272


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