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dc.contributor.authorLi, H
dc.contributor.authorLim, JH
dc.contributor.authorLiu, J
dc.contributor.authorMitchell, P
dc.contributor.authorTan, AG
dc.contributor.authorWang, JJ
dc.contributor.authorWong, TY
dc.date.available2014-05-22T03:51:11Z
dc.date.issued2010-07-01
dc.identifierhttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000278811900016&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=d4d813f4571fa7d6246bdc0dfeca3a1c
dc.identifier.citationLi, 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.
dc.identifier.issn0018-9294
dc.identifier.urihttp://hdl.handle.net/11343/31634
dc.description.abstractCataracts 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.
dc.languageEnglish
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.subjectArtificial Intelligence and Image Processing
dc.titleA Computer-Aided Diagnosis System of Nuclear Cataract
dc.typeJournal Article
dc.identifier.doi10.1109/TBME.2010.2041454
melbourne.peerreviewPeer Reviewed
melbourne.affiliationThe University of Melbourne
melbourne.affiliation.departmentOphthalmology Eye and Ear Hospital
melbourne.source.titleIEEE Transactions on Biomedical Engineering
melbourne.source.volume57
melbourne.source.issue7
melbourne.source.pages1690-1698
dc.description.pagestart1690
melbourne.publicationid152225
melbourne.elementsid327510
melbourne.contributor.authorWANG, JIE
melbourne.contributor.authorWong, Tien
dc.identifier.eissn1558-2531
melbourne.accessrightsThis item is currently not available from this repository


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