• DocumentCode
    2941559
  • Title

    Closed angle glaucoma detection in RetCam images

  • Author

    Jun Cheng ; Jiang Liu ; Beng Hai Lee ; Wong, Damon Wing Kee ; Fengshou Yin ; Tin Aung ; Baskaran, Mani ; Shamira, P. ; Tien Yin Wong

  • Author_Institution
    Inst. for Infocomm Res., A*STAR, Singapore, Singapore
  • fYear
    2010
  • fDate
    Aug. 31 2010-Sept. 4 2010
  • Firstpage
    4096
  • Lastpage
    4099
  • Abstract
    Closed/Open angle glaucoma classification is important for glaucoma diagnosis. RetCam is a new imaging modality that captures the image of iridocorneal angle for the classification. However, manual grading and analysis of the RetCam image is subjective and time consuming. In this paper, we propose a system for intelligent analysis of iridocorneal angle images, which can differentiate closed angle glaucoma from open angle glaucoma automatically. Two approaches are proposed for the classification and their performances are compared. The experimental results show promising results.
  • Keywords
    artificial intelligence; biomedical optical imaging; diseases; eye; image classification; medical image processing; RetCam images; closed angle glaucoma detection; closed/open angle glaucoma classification; glaucoma diagnosis; intelligent analysis; iridocorneal angle; Cornea; Image edge detection; Imaging; Iris; Lenses; Sensitivity; Transforms; Glaucoma, Angle-Closure; Humans; Photography;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE
  • Conference_Location
    Buenos Aires
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-4123-5
  • Type

    conf

  • DOI
    10.1109/IEMBS.2010.5627290
  • Filename
    5627290