• DocumentCode
    1673350
  • Title

    Vessel Tracking Algorithms in Ultrasound Imaging

  • Author

    Li, Shuo ; Liu, Dong C.

  • Author_Institution
    Sch. of Comput. Sci., Sichuan Univ., Chengdu
  • fYear
    2008
  • Firstpage
    2481
  • Lastpage
    2484
  • Abstract
    Doctors usually observe patients´ ultrasound vessel images to obtain clinical information about vascular diseases, and sometimes they want to measure the vessel diameter from the images. The aim of this paper is to provide a convenient method to measure the vessel diameter from the images. However, the shapes of vessels are usually anomalous, and the diameters are usually different on different part of the vessel, so it is difficult to decide the direction of the diameter as well as the length of the diameter at any given point on vessel. In this paper we proposed a Euclidean Distance Transform (EDT) based skeletonization method to find the midline of the vessel. Along the midline, we can calculate the vessel diameter locally from the intersection of vessel wall and the line perpendicular to the tangent of the midline pixels. Because of the fuzziness of the detected midline, this tangent vector is derived by a least square line fitting for robustness. Algorithms have been tested using 3D power mode kidney imaging. Results show that the proposed method can enhance the tree-like vascular structure of the kidney and offer an interactive way to measure the vessel diameter on the image.
  • Keywords
    biomedical ultrasonics; blood vessels; kidney; EDT based skeletonization method; Euclidean distance transform; kidney imaging; tree-like vascular structure; ultrasound imaging; vessel tracking algorithms; vessel wall; Arteries; Diseases; Euclidean distance; Morphology; Pixel; Shape; Skeleton; Topology; Ultrasonic imaging; Ultrasonic variables measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedical Engineering, 2008. ICBBE 2008. The 2nd International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-1747-6
  • Electronic_ISBN
    978-1-4244-1748-3
  • Type

    conf

  • DOI
    10.1109/ICBBE.2008.953
  • Filename
    4535833