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    Edge detection of the optic disc in retinal images based on identification of a round shape

    Access Status
    Fulltext not available
    Authors
    Chaichana, T.
    Sun, Zhonghua
    Tangjitkusolmun, S.
    Yoowattanna, S.
    Sangworasil, M.
    Date
    2008
    Type
    Conference Paper
    
    Metadata
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    Citation
    Chaichana, Thanapong and Sun, Zhonghua and Tangjitkusolmun, Supan and Yoowattanna, Sarat and Sangworasil, Manas. 2008. : Edge detection of the optic disc in retinal images based on identification of a round shape, in Mangnomek, Somkot (ed), Communications and Information Technologies, 2008. ISCIT 08. International Symposium on, 21-23 Oct 2008. Vientiane, Lao PDR: ISCIT.
    Source Title
    Communications and Information Technologies, 2008. ISCIT 08. International Symposium on
    Source Conference
    Communications and Information Technologies, 2008. ISCIT 08. International Symposium on
    Faculty
    Faculty of Science and Computing
    Department of Applied Physics
    Department of Medical Imaging Science
    Division of Engineering, Science and Computing
    Faculty of Science
    Remarks

    This paper is to be presented at the conference above.

    URI
    http://hdl.handle.net/20.500.11937/41825
    Collection
    • Curtin Research Publications
    Abstract

    This paper presents a novel method for identification of the position of the optic disc in retinal images. The method is based on the preliminary detection of the main edgedetection of retinal image. The segmentation optic disc is estimated as a circular area. We searched for areas of optic disc using Hough transform which detected several straight lines and approximated them as a circular line. The position of optic discwas identified as the center of the circle. An evaluation of the proposed procedure was performed using a set of 40 images from the DRIVE database, containing images from both healthy (33) and diseased (7) subjects. The optic disc position was correctly identified in 39 out of 40 images and the efficiency was 97.5 percent. The results illustrate that the proposed method can be used for pathological analysis of retinal images.

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