• DocumentCode
    2505461
  • Title

    Boundary delineation for hepatic hemangioma in ultrasound images

  • Author

    Bahrami, Naeim ; Rezatofighi, Seyed Hamid ; Adeli, Aliyeh Mahdavi ; Setarehdan, S. Kamaledin

  • Author_Institution
    Control & Intell. Process. Center of Excellence, Univ. of Tehran, Tehran, Iran
  • fYear
    2011
  • fDate
    Aug. 30 2011-Sept. 3 2011
  • Firstpage
    7989
  • Lastpage
    7992
  • Abstract
    Hemangioma is one of the most common benign congenital complications of the human body which can arise in interior organs and external limbs. The main aim of this work is to present a new method for automatic detection of liver hemangioma and its boundaries in ultrasound images, using image processing techniques. Overall there are two phases, the preprocessing procedure and the boundary delineation phase. The preprocessing phase includes three main stages: 1. Image contrast enhancement using Difference of Offset Gaussian (DoOG) method, 2. Applying Canny edge filtering, 3. Applying an adaptive threshold in order to detect the ROI (hemangioma). Following, the snake algorithm is used to segment the hemangioma region in the second phase. For the quantitative assessment of the proposed method for the segmentation stage, the results derived via the proposed algorithms have been compared with the corresponding segmented regions determined by an expert using three similarity criteria. The results showed 73 percent similarity without pre-processing and 90 percent similarity with pre-processing.
  • Keywords
    biomedical ultrasonics; blood vessels; cancer; edge detection; image enhancement; image segmentation; liver; medical image processing; Canny edge filtering; automatic detection; boundary delineation; boundary delineation phase; difference of offset Gaussian method; hepatic hemangioma; image contrast enhancement; image processing; preprocessing phase; snake algorithm; ultrasound images; Filtering algorithms; Image edge detection; Image segmentation; Liver; Measurement; Noise; Ultrasonic imaging; Active contour model; Difference of offset Gaussian; Hemangioma; Image processing; Liver; Ultrasound; Algorithms; Automation; Hemangioma; Humans; Image Processing, Computer-Assisted; Liver Neoplasms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE
  • Conference_Location
    Boston, MA
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-4121-1
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2011.6091970
  • Filename
    6091970