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  • Ophthalmology (Eye & Ear Hospital)
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    A Computer-Aided Diagnosis System of Nuclear Cataract

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    Author
    Li, H; Lim, JH; Liu, J; Mitchell, P; Tan, AG; Wang, JJ; Wong, TY
    Date
    2010-07-01
    Source Title
    IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
    Publisher
    IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
    University of Melbourne Author/s
    WANG, JIE; Wong, Tien
    Affiliation
    Ophthalmology Eye and Ear Hospital
    Metadata
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    Document Type
    Journal Article
    Citations
    Li, H., Lim, J. H., Liu, J., Mitchell, P., Tan, A. G., Wang, J. J. & Wong, T. Y. (2010). A Computer-Aided Diagnosis System of Nuclear Cataract. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 57 (7), pp.1690-1698. https://doi.org/10.1109/TBME.2010.2041454.
    Access Status
    This item is currently not available from this repository
    URI
    http://hdl.handle.net/11343/31634
    DOI
    10.1109/TBME.2010.2041454
    Abstract
    Cataracts are the leading cause of blindness worldwide, and nuclear cataract is the most common form of cataract. An algorithm for automatic diagnosis of nuclear cataract is investigated in this paper. Nuclear cataract is graded according to the severity of opacity using slit lamp lens images. Anatomical structure in the lens image is detected using a modified active shape model. On the basis of the anatomical landmark, local features are extracted according to clinical grading protocol. Support vector machine regression is employed for grade prediction. This is the first time that the nucleus region can be detected automatically in slit lamp images. The system is validated using clinical images and clinical ground truth on >5000 images. The success rate of structure detection is 95% and the average grading difference is 0.36 on a 5.0 scale. The automatic diagnosis system can improve the grading objectivity and potentially be used in clinics and population studies to save the workload of ophthalmologists.
    Keywords
    Artificial Intelligence and Image Processing

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