• DocumentCode
    2098050
  • Title

    A Thinning-based Liver Vessel Skeletonization Method

  • Author

    Chen, Yufei ; Drechsler, Klaus ; Zhao, Weidong ; Laura, Cristina Oyarzun

  • Author_Institution
    Post-doctoral Res. Center of Control Sci. & Eng., Tongji Univ., Shanghai, China
  • fYear
    2011
  • fDate
    17-18 Sept. 2011
  • Firstpage
    152
  • Lastpage
    155
  • Abstract
    In the clinical practice of diagnosis and treatment of liver disease, how to effectively represent and analyze the vascular structure has been a widely studied topic for a long time. In this paper, we propose a method for the three dimensional skeletal graph generation of liver vessels using 3D thinning algorithm and graph theory. First of all, the principal methods for skeletonization are introduced, followed by their comparative analysis. Secondly, the 3D thinning-based skeletonization method together with a filling hole pre-processing on liver vessel image are employed to form the liver skeleton. A graph-based technique is then employed on the skeleton image to efficiently form the liver vascular graph. The thinning-based liver vessel skeletonization method was evaluated on liver vessel images with other two kinds of skeletonization approaches to show its effectiveness and efficiency.
  • Keywords
    diseases; graph theory; image thinning; liver; medical image processing; patient diagnosis; patient treatment; 3D skeletal graph generation; 3D thinning algorithm; graph theory; liver disease diagnosis; liver disease treatment; thinning-based liver vessel skeletonization; vascular structure; Biomedical imaging; Computed tomography; Image segmentation; Liver; Skeleton; Three dimensional displays; Topology; liver vessel; skeletonization; three-dimensional thinning algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Internet Computing & Information Services (ICICIS), 2011 International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4577-1561-7
  • Type

    conf

  • DOI
    10.1109/ICICIS.2011.44
  • Filename
    6063216