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Segmentation of optic cup and disc for diagnosis of glaucoma on retinal fundus images

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dc.contributor.author Joshua, AO
dc.contributor.author Nelwamondo, Fulufhelo V
dc.contributor.author Mabuza-Hocquet, Gugulethu P
dc.date.accessioned 2019-03-26T06:40:28Z
dc.date.available 2019-03-26T06:40:28Z
dc.date.issued 2019-01
dc.identifier.citation Joshua, A.O., Nelwamondo, F.V. and Mabuza-Hocquet, G.P. 2019. Segmentation of optic cup and disc for diagnosis of glaucoma on retinal fundus images. 2019 Southern African Universities Power Engineering Conference, Central University of Technology, Free State Bloemfontein, South Africa, 28-30 January 2019, pp. 183-187 en_US
dc.identifier.isbn 978-1-7281-0369-3
dc.identifier.uri http://hdl.handle.net/10204/10856
dc.description Due to copyright restrictions, the attached pdf contains the accepted version of the published paper. Please consult the publisher's website for access to the published version. en_US
dc.description.abstract Glaucoma has been attributed to be the leading cause of blindness in the world second only to diabetic retinopathy. About 66.8 million people in the world have glaucoma and about 6.7 million are suffering from blindness as a result of glaucoma. A cause of glaucoma is the enlargement of the optic cup such that it occupies the optic disc area. Hence, the estimation of optic Cup to Disc ratio (CDR) is a valuable tool in diagnosing glaucoma. The CDR can be obtained by segmenting the optic cup and optic disc from the fundus image. In this work, an improved U-net Convolutional Neural Network (CNN) architecture was used to segment the optic disc and the optic cup from the fundus image. The dataset used was obtained from the DRISHTI-GS database and the RIM-ONE v.3. The proposed pipeline and architecture outperforms existing techniques on Optic Disc (OD) and Optic Cup (OC) segmentation on the Dice-score metric and prediction time. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.relation.ispartofseries Worklist;22045
dc.subject Retinal fundus image en_US
dc.subject Glaucoma en_US
dc.subject Optic disc segmentation en_US
dc.subject Cup to disc ratio en_US
dc.subject Image segmentation en_US
dc.title Segmentation of optic cup and disc for diagnosis of glaucoma on retinal fundus images en_US
dc.type Conference Presentation en_US
dc.identifier.apacitation Joshua, A., Nelwamondo, F. V., & Mabuza-Hocquet, G. P. (2019). Segmentation of optic cup and disc for diagnosis of glaucoma on retinal fundus images. IEEE. http://hdl.handle.net/10204/10856 en_ZA
dc.identifier.chicagocitation Joshua, AO, Fulufhelo V Nelwamondo, and Gugulethu P Mabuza-Hocquet. "Segmentation of optic cup and disc for diagnosis of glaucoma on retinal fundus images." (2019): http://hdl.handle.net/10204/10856 en_ZA
dc.identifier.vancouvercitation Joshua A, Nelwamondo FV, Mabuza-Hocquet GP, Segmentation of optic cup and disc for diagnosis of glaucoma on retinal fundus images; IEEE; 2019. http://hdl.handle.net/10204/10856 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Joshua, AO AU - Nelwamondo, Fulufhelo V AU - Mabuza-Hocquet, Gugulethu P AB - Glaucoma has been attributed to be the leading cause of blindness in the world second only to diabetic retinopathy. About 66.8 million people in the world have glaucoma and about 6.7 million are suffering from blindness as a result of glaucoma. A cause of glaucoma is the enlargement of the optic cup such that it occupies the optic disc area. Hence, the estimation of optic Cup to Disc ratio (CDR) is a valuable tool in diagnosing glaucoma. The CDR can be obtained by segmenting the optic cup and optic disc from the fundus image. In this work, an improved U-net Convolutional Neural Network (CNN) architecture was used to segment the optic disc and the optic cup from the fundus image. The dataset used was obtained from the DRISHTI-GS database and the RIM-ONE v.3. The proposed pipeline and architecture outperforms existing techniques on Optic Disc (OD) and Optic Cup (OC) segmentation on the Dice-score metric and prediction time. DA - 2019-01 DB - ResearchSpace DP - CSIR KW - Retinal fundus image KW - Glaucoma KW - Optic disc segmentation KW - Cup to disc ratio KW - Image segmentation LK - https://researchspace.csir.co.za PY - 2019 SM - 978-1-7281-0369-3 T1 - Segmentation of optic cup and disc for diagnosis of glaucoma on retinal fundus images TI - Segmentation of optic cup and disc for diagnosis of glaucoma on retinal fundus images UR - http://hdl.handle.net/10204/10856 ER - en_ZA


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