Optic Disk and Cup Segmentation From Monocular Color Retinal Images for Glaucoma Assessment

By Gopal Datt Joshi, Jayanthi Sivaswamy, S. R. Krishnadas. IEEE Transactions on Medical Imaging, 2011

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Joint Optic Disc and Cup Segmentation Based on Multi-Label Deep Network and Polar Transformation (2018, methodology): “The performances are shown in Table I. R-Bend [9] provides a parameterization technique based on vessel bends, and ASM [42] employs the circular Hough transform initialization to segment the OD and OC regions.”
REFUGE Challenge: A Unified Framework for Evaluating Automated Methods for Glaucoma Assessment from Fundus Photographs (2019, unknown): “Alternative features such as vessels bendings (Joshi et al., 2011) or intensity changes (Xu et al.”
CNNs for automatic glaucoma assessment using fundus images: an extensive validation (2019, background): “[7] is based on anatomical evidence such as vessel bends at the cup boundary to segment the optic cup.”
Drishti-GS: Retinal image dataset for optic nerve head(ONH) segmentation (2014, background): “Index Terms— Glaucoma, Dataset, Optic Nerve Head, Cup, Optic Disk”
Disc-Aware Ensemble Network for Glaucoma Screening From Fundus Image (2018, background): “have been proposed [8]–[12], which segment the main struc-”