• DocumentCode
    2560284
  • Title

    CNN-based automatic retinal vascular tree extraction

  • Author

    Alonso-Montes, C. ; Vilariño, D.L. ; Penedo, M.G.

  • Author_Institution
    Dept. of Comput. Sci., Coruna Univ., Spain
  • fYear
    2005
  • fDate
    28-30 May 2005
  • Firstpage
    61
  • Lastpage
    64
  • Abstract
    The retinal vascular tree has become an important task of medical image processing in different scientific areas. Many studies have focused on developing an automatic algorithm, however little attention has been paid to improve computational processing time of these algorithms. In this paper, an automatic methodology for retinal vascular tree extraction using cellular neural networks (CNNs) is proposed. The aim of using CNNs is to improve computational time in order to achieve real-time requirements.
  • Keywords
    blood vessels; cellular neural nets; eye; medical image processing; CNN-based automatic retinal vascular tree extraction; cellular neural networks; medical image processing; Active contours; Angiography; Biomedical image processing; Biomedical imaging; Cellular neural networks; Computer architecture; Computer science; Histograms; Image segmentation; Retina;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cellular Neural Networks and Their Applications, 2005 9th International Workshop on
  • Print_ISBN
    0-7803-9185-3
  • Type

    conf

  • DOI
    10.1109/CNNA.2005.1543161
  • Filename
    1543161