• DocumentCode
    2918706
  • Title

    Novel 4-D Open-Curve Active Contour and curve completion approach for automated tree structure extraction

  • Author

    Wang, Yu ; Narayanaswamy, Arunachalam ; Roysam, Badrinath

  • Author_Institution
    Rensselaer Polytech. Inst., Troy, NY, USA
  • fYear
    2011
  • fDate
    20-25 June 2011
  • Firstpage
    1105
  • Lastpage
    1112
  • Abstract
    We present novel approaches for fully automated extraction of tree-like tubular structures from 3-D image stacks. A 4-D Open-Curve Active Contour (Snake) model is proposed for simultaneous 3-D centerline tracing and local radius estimation. An image energy term, stretching term, and a novel region-based radial energy term constitute the energy to be minimized. This combination of energy terms allows the 4-D open-curve snake model, starting from an automatically detected seed point, to stretch along and fit the tubular structures like neurites and blood vessels. A graph-based curve completion approach is proposed to merge possible fragments caused by discontinuities in the tree structures. After tree structure extraction, the centerlines serve as the starting points for a Fast Marching segmentation for which the stopping time is automatically chosen. We illustrate the performance of our method with various datasets.
  • Keywords
    feature extraction; image segmentation; solid modelling; 3-D centerline tracing; 3-D image stacks; 4-D open-curve active contour model; 4-D open-curve snake model; automated tree structure extraction; automatic seed point detection; blood vessels; fast marching segmentation; graph-based curve completion approach; image energy term; local radius estimation; region-based radial energy term; Active contours; Estimation; Force; Head; Image segmentation; Mathematical model; Solid modeling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on
  • Conference_Location
    Providence, RI
  • ISSN
    1063-6919
  • Print_ISBN
    978-1-4577-0394-2
  • Type

    conf

  • DOI
    10.1109/CVPR.2011.5995620
  • Filename
    5995620