• DocumentCode
    936093
  • Title

    Recursive tracking of vascular networks in angiograms based on the detection-deletion scheme

  • Author

    Liu, Iching ; Sun, Ying

  • Author_Institution
    PB Diagnostic Syst. Inc., Westwood, MA, USA
  • Volume
    12
  • Issue
    2
  • fYear
    1993
  • fDate
    6/1/1993 12:00:00 AM
  • Firstpage
    334
  • Lastpage
    341
  • Abstract
    A computer algorithm was developed for automated identification of 2-D vascular networks in X-ray angiograms. This was accomplished by using an adaptive tracking algorithm in a three-stage recursive procedure. First, given a starting position and direction, a segment in the vascular network was identified. Second, by filling it with the surrounding background pixel values, the detected segment was deleted from the angiogram. The detection-deletion scheme was employed to prevent the problem of tracking-path reentry in those areas where vessels overlap. Third, all branch points were detected by use of matched filtering along both edges of the vessel. The detected branch points were used as the starting points in the next recursion. The recursive procedure terminated when no new branch point was found. The algorithm showed a good performance when it was applied to angiograms of coronary and radial arteries. To provide a quantitative evaluation, vascular networks identified by the algorithm were compared to those identified by a human. The algorithm made some false-negative errors, but very few false-positive errors
  • Keywords
    diagnostic radiography; medical image processing; 3-stage recursive procedure; X-ray angiograms; adaptive tracking algorithm; automated identification; background pixel values; branch points; computer algorithm; coronary artery; detection-deletion scheme; false-negative errors; false-positive errors; matched filtering; medical diagnostic imaging; radial artery; recursive tracking; vascular networks; Algorithm design and analysis; Arteries; Biomedical imaging; Blood vessels; Computer networks; Data mining; Hemodynamics; Image segmentation; Intelligent networks; Sun;
  • fLanguage
    English
  • Journal_Title
    Medical Imaging, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0062
  • Type

    jour

  • DOI
    10.1109/42.232264
  • Filename
    232264