• DocumentCode
    3409692
  • Title

    Graph-based optimal cross section boundary for vessel segmentation and stenosis quantification

  • Author

    Ning Zhu ; Chung, Albert C. S.

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Hong Kong Univ. of Sci. & Technol., Hong Kong, China
  • fYear
    2012
  • fDate
    Sept. 30 2012-Oct. 3 2012
  • Firstpage
    2041
  • Lastpage
    2044
  • Abstract
    In this paper, we propose a graph-based method to find the optimal cross section boundary for vessel segmentation. The voxels on the cross sectional plane are assumed to lay on the circles around the centerline point. The voxels on the circles with different radii are then transformed to a graph, by which the objective of finding the optimal boundary is converted to choosing the optimal path in the graph. A new cost function for the edge cost of the graph is proposed to obtain a smooth, optimal boundary of the cross section. Based on the optimal cross section boundary, we also propose a method for stenosis detection and quantification. The proposed method for segmentation and stenosis detection has been evaluated to be accurate and highly computationally efficient.
  • Keywords
    blood vessels; graph theory; image segmentation; medical image processing; centerline point; computational efficiency; cross sectional plane; graph optimal path; graph transformation; graph-based method; graph-based optimal cross section boundary; optimal cross section boundary; stenosis detection; stenosis quantification; vessel segmentation stenosis quantification; Accuracy; Approximation methods; Arteries; Computed tomography; Cost function; Image segmentation; Shape; Graph-Based Optimal Path; Stenosis Quantification; Vessel Segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2012 19th IEEE International Conference on
  • Conference_Location
    Orlando, FL
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4673-2534-9
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2012.6467291
  • Filename
    6467291