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Author:

Wu, Weiwei (Wu, Weiwei.) | Zhou, Zhuhuang (Zhou, Zhuhuang.) | Wu, Shuicai (Wu, Shuicai.) (Scholars:吴水才) | Zhang, Yanhua (Zhang, Yanhua.) (Scholars:张延华)

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Abstract:

Accurate segmentation of liver from abdominal CT scans is critical for computer-assisted diagnosis and therapy. Despite many years of research, automatic liver segmentation remains a challenging task. In this paper, a novel method was proposed for automatic delineation of liver on CT volume images using supervoxel-based graph cuts. To extract the liver volume of interest (VOI), the region of abdomen was firstly determined based on maximum intensity projection (MIP) and thresholding methods. Then, the patient-specific liver VOI was extracted from the region of abdomen by using a histogram-based adaptive thresholding method and morphological operations. The supervoxels of the liver VOI were generated using the simple linear iterative clustering (SLIC) method. The foreground/background seeds for graph cuts were generated on the largest liver slice, and the graph cuts algorithm was applied to the VOI supervoxels. Thirty abdominal CT images were used to evaluate the accuracy and efficiency of the proposed algorithm. Experimental results show that the proposed method can detect the liver accurately with significant reduction of processing time, especially when dealing with diseased liver cases.

Keyword:

Author Community:

  • [ 1 ] [Wu, Weiwei]Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing 100124, Peoples R China
  • [ 2 ] [Zhang, Yanhua]Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing 100124, Peoples R China
  • [ 3 ] [Zhou, Zhuhuang]Beijing Univ Technol, Coll Life Sci & Bioengn, Beijing 100124, Peoples R China
  • [ 4 ] [Wu, Shuicai]Beijing Univ Technol, Coll Life Sci & Bioengn, Beijing 100124, Peoples R China

Reprint Author's Address:

  • 吴水才

    [Wu, Shuicai]Beijing Univ Technol, Coll Life Sci & Bioengn, Beijing 100124, Peoples R China

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Source :

COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE

ISSN: 1748-670X

Year: 2016

Volume: 2016

ESI Discipline: MATHEMATICS;

ESI HC Threshold:71

CAS Journal Grade:4

Cited Count:

WoS CC Cited Count: 71

SCOPUS Cited Count: 93

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 8

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