A Computer-Aided Diagnosis System of Nuclear Cataract
Author
Li, H; Lim, JH; Liu, J; Mitchell, P; Tan, AG; Wang, JJ; Wong, TYDate
2010-07-01Source Title
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERINGPublisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INCAffiliation
Ophthalmology Eye and Ear HospitalMetadata
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Journal ArticleCitations
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 repositoryAbstract
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 ProcessingExport Reference in RIS Format
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