• DocumentCode
    17568
  • Title

    Accurate Vessel Segmentation With Constrained B-Snake

  • Author

    Yuanzhi Cheng ; Xin Hu ; Ji Wang ; Yadong Wang ; Tamura, Shinichi

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Harbin Inst. of Technol., Harbin, China
  • Volume
    24
  • Issue
    8
  • fYear
    2015
  • fDate
    Aug. 2015
  • Firstpage
    2440
  • Lastpage
    2455
  • Abstract
    We describe an active contour framework with accurate shape and size constraints on the vessel cross-sectional planes to produce the vessel segmentation. It starts with a multiscale vessel axis tracing in a 3D computed tomography (CT) data, followed by vessel boundary delineation on the cross-sectional planes derived from the extracted axis. The vessel boundary surface is deformed under constrained movements on the cross sections and is voxelized to produce the final vascular segmentation. The novelty of this paper lies in the accurate contour point detection of thin vessels based on the CT scanning model, in the efficient implementation of missing contour points in the problematic regions and in the active contour model with accurate shape and size constraints. The main advantage of our framework is that it avoids disconnected and incomplete segmentation of the vessels in the problematic regions that contain touching vessels (vessels in close proximity to each other), diseased portions (pathologic structure attached to a vessel), and thin vessels. It is particularly suitable for accurate segmentation of thin and low contrast vessels. Our method is evaluated and demonstrated on CT data sets from our partner site, and its results are compared with three related methods. Our method is also tested on two publicly available databases and its results are compared with the recently published method. The applicability of the proposed method to some challenging clinical problems, the segmentation of the vessels in the problematic regions, is demonstrated with good results on both quantitative and qualitative experimentations; our segmentation algorithm can delineate vessel boundaries that have level of variability similar to those obtained manually.
  • Keywords
    computerised tomography; image segmentation; medical image processing; 3D computed tomography data; CT scanning model; accurate vessel segmentation; active contour framework; clinical problems; constrained B-snake; multiscale vessel axis; vascular segmentation; vessel boundary delineation; vessel cross-sectional planes; Active contours; Deformable models; Image segmentation; Joining processes; Mathematical model; Shape; Splines (mathematics); Vessel segmentation; computed tomography angiography (CTA); constrained B-snake; shape and size constraints; vessel-axis-tracing;
  • fLanguage
    English
  • Journal_Title
    Image Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1057-7149
  • Type

    jour

  • DOI
    10.1109/TIP.2015.2417683
  • Filename
    7081358