• DocumentCode
    2720065
  • Title

    Detection of the tear meniscus shape using asymmetric graph-cuts

  • Author

    Yedidya, Tamir ; Hartley, Richard ; Guillon, Jean-Pierre ; Kanagasingam, Yogesan

  • fYear
    2010
  • fDate
    14-17 April 2010
  • Firstpage
    944
  • Lastpage
    947
  • Abstract
    We present a new fully automatic algorithm to evaluate the shape and regularity of the tear meniscus in eye images taken using a slit-lamp after instilling fluorescein. Our method analyzes the meniscus in the corneal and conjunctival areas and detects abnormalities such as conjunctival folds. We use graph-cuts to minimize a cost function to simultaneously produce a segmentation of the meniscus and the best shape prior for the eyelids. The pairwise term is asymmetric in order to capture the global properties of the meniscus and add a sense of direction. We tested our method on 43 images and provide a grading of the quality of the meniscus.
  • Keywords
    bio-optics; biomedical optical imaging; eye; fluorescence; image segmentation; medical image processing; shape recognition; conjunctival folds; corneal areas; cost function; eyelids; fluorescein; global properties; graph-cuts; segmentation; slit-lamp; tear meniscus regularity; tear meniscus shape detection; Australia; Cost function; Eyelids; Eyes; Gold; Image segmentation; Pattern analysis; Reservoirs; Shape; Testing; Asymmetry; Dry Eye; Graph-Cuts; Segmentation; Tear meniscus;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Imaging: From Nano to Macro, 2010 IEEE International Symposium on
  • Conference_Location
    Rotterdam
  • ISSN
    1945-7928
  • Print_ISBN
    978-1-4244-4125-9
  • Electronic_ISBN
    1945-7928
  • Type

    conf

  • DOI
    10.1109/ISBI.2010.5490143
  • Filename
    5490143