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Please use this identifier to cite or link to this item: https://doi.org/10.1109/IEMBS.2010.5627290
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dc.titleClosed angle glaucoma detection in RetCam images
dc.contributor.authorCheng, J.
dc.contributor.authorLiu, J.
dc.contributor.authorLee, B.H.
dc.contributor.authorWong, D.W.K.
dc.contributor.authorYin, F.
dc.contributor.authorAung, T.
dc.contributor.authorBaskaran, M.
dc.contributor.authorShamira, P.
dc.contributor.authorWong, T.Y.
dc.date.accessioned2014-11-26T07:49:33Z
dc.date.available2014-11-26T07:49:33Z
dc.date.issued2010
dc.identifier.citationCheng, J., Liu, J., Lee, B.H., Wong, D.W.K., Yin, F., Aung, T., Baskaran, M., Shamira, P., Wong, T.Y. (2010). Closed angle glaucoma detection in RetCam images. 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 : 4096-4099. ScholarBank@NUS Repository. https://doi.org/10.1109/IEMBS.2010.5627290
dc.identifier.isbn9781424441235
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/109748
dc.description.abstractClosed/Open angle glaucoma classification is important for glaucoma diagnosis. RetCam is a new imaging modality that captures the image of iridocorneal angle for the classification. However, manual grading and analysis of the RetCam image is subjective and time consuming. In this paper, we propose a system for intelligent analysis of iridocorneal angle images, which can differentiate closed angle glaucoma from open angle glaucoma automatically. Two approaches are proposed for the classification and their performances are compared. The experimental results show promising results. © 2010 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/IEMBS.2010.5627290
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentOPHTHALMOLOGY
dc.description.doi10.1109/IEMBS.2010.5627290
dc.description.sourcetitle2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
dc.description.page4096-4099
dc.identifier.isiut000287964004124
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