• DocumentCode
    3650827
  • Title

    Drusen quantification for early identification of age related macular degeneration (AMD) using color fundus imaging

  • Author

    Alauddin Bhuiyan;C. Karmakar;Di Xiao;Kotagiri Ramamohanarao;Yogi Kanagasingam

  • Author_Institution
    Australian E-Health Research Centre, Commonwealth Scientific and Industrial Research Organization (CSIRO), Perth, Australia
  • fYear
    2013
  • fDate
    7/1/2013 12:00:00 AM
  • Firstpage
    7392
  • Lastpage
    7395
  • Abstract
    Age-related macular degeneration (AMD) is a major cause of visual impairment in the elderly and identifying people with the early stages of AMD is important when considering the design and implementation of preventative strategies for late AMD. Quantification of drusen size and total area covered by drusen is an important risk factor for progression. In this paper, we propose a method to detect drusen and quantify drusen size along with the area covered with drusen in macular region from standard color retinal images. We used combined local intensity distribution, adaptive intensity thresholding and edge information to detect potential drusen areas. The proposed method detected the presence of any drusen with 100% accuracy (50/50 images). For drusen detection accuracy (DDA), the segmentations produced by the automated method on individual images achieved mean sensitivity and specificity values of 74.94% and 81.17%, respectively.
  • Keywords
    "Retina","Image edge detection","Accuracy","Shape","Image segmentation","Image color analysis","Histograms"
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE
  • ISSN
    1094-687X
  • Electronic_ISBN
    1558-4615
  • Type

    conf

  • DOI
    10.1109/EMBC.2013.6611266
  • Filename
    6611266