Please use this identifier to cite or link to this item: http://repository.unmul.ac.id/handle/123456789/3278
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dc.contributor.authorSeptiarini, Anindita-
dc.date.accessioned2019-12-16T00:34:13Z-
dc.date.available2019-12-16T00:34:13Z-
dc.date.issued2017-07-
dc.identifier.issn1863-1703 (Print) 1863-1711 (Online)-
dc.identifier.urihttp://repository.unmul.ac.id/handle/123456789/3278-
dc.description.abstractThis research proposes a robust method for disc localization and cup segmentation that incorporates masking to avoid misclassifying areas as well as forming the structure of the cup based on edge detection. Our method has been evaluated using two fundus image datasets, namely: D-I and D-II comprising of 60 and 38 images, respectively. The proposed method of disc localization achieves an average Fscore of 0.96 and average boundary distance of 7.7 for D-I, and 0.96 and 9.1, respectively, for D-II. The cup segmentation method attains an average Fscore of 0.88 and average boundary distance of 13.8 for D-I, and 0.85 and 18.0, respectively, for D-II. The estimation errors (mean ± standard deviation) of our method for the value of vertical cup-to-disc diameter ratio against the result of the boundary by the expert of DI and D-II have similar value, namely 0.04 ± 0.04. Overall, the result of our method indicates its robustness for glaucoma evaluation.en_US
dc.language.isoenen_US
dc.publisherSpringer-Verlag Londonen_US
dc.relation.ispartofseriesSignal, Image and Video Processing;-
dc.subjectGlaucoma, Disc segmentation, Cup segmentation, Thresholding, Morphologyen_US
dc.titleOptic disc and cup segmentation by automatic thresholding with morphological operation for glaucoma evaluationen_US
dc.typeArticleen_US
Appears in Collections:J - Computer Sciences and Information Technology



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