• DocumentCode
    2767303
  • Title

    Robust Dynamic Skeleton Extraction for Blood Vessels Based on the Level Set Method

  • Author

    Cui, Zhiming ; Xu, Jing ; Feng, Darning ; Wu, Jian

  • Author_Institution
    Inst. of Intell. Inf. Process. & Applic., Soochow Univ., Suzhou, China
  • Volume
    7
  • fYear
    2009
  • fDate
    14-16 Aug. 2009
  • Firstpage
    373
  • Lastpage
    378
  • Abstract
    Skeleton has very important applications in objects expression, data compression, computer vision and animation. In the discrete space, the basic skeleton algorithms have two categories: one is thinning, the other is based on the distance transformation, in a high-dimensional space generated from the surface to form the ridge to create a skeleton. The skeleton which is based on the distance transform algorithm is accurate and smooth, but we must carefully check its continuity. Such a check of the continuity would be very difficult when the skeleton structure is complex. The biggest advantage of thinning algorithm is that it can ensure that the skeleton is in a row and keeps the main topology of the initial target, but the general position is not accurate. In this paper, combining thinning algorithms and level set model, a dynamic robust vascular skeleton extraction algorithm is proposed. First using thinning technology to generate initial skeleton in a row, and then based on the level set model, it will guide the initial framework to the correct position. In this paper, the skeleton extracted from our algorithm not only maintains the exact location and the smooth appearance in a row at the same time curbs the noise of the border with a good robustness.
  • Keywords
    Gaussian noise; blood vessels; brain; feature extraction; image reconstruction; image segmentation; image sequences; medical image processing; Gaussian noise interference; artery; blood vessels; brain; discrete space; distance transformation; dynamic robust vascular skeleton extraction algorithm; high-dimensional space; higher-accuracy fast marching method; image segmentation; level set method; level set model; salt and pepper noise; subtracted image sequences; thinning algorithms; three-dimensional reconstruction; Animation; Application software; Blood vessels; Computer vision; Data compression; Data mining; Discrete transforms; Level set; Robustness; Skeleton;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-0-7695-3735-1
  • Type

    conf

  • DOI
    10.1109/FSKD.2009.917
  • Filename
    5360020