Identification of the optic nerve head with genetic algorithms

By Enrique J. Carmona, M. Rincón, J. García-Feijóo, J. Martínez-de-la-Casa. Artif. Intell. Medicine, 2008

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Deep Retinal Image Understanding (2016, methodology): “The same applies for optic disc segmentation, where our algorithm processes an image of DRIONS-DB in 65 ms and 110 ms for the larger images of RIM-ONE dataset.”
Continuous Adaptation for Interactive Object Segmentation by Learning from Corrections (2019, methodology): “DRIONS-DB [14] Rooftop [53] Method clicks@90% IoU clicks@80% IoU”
FEEDBACK ON A PUBLICLY DISTRIBUTED IMAGE DATABASE: THE MESSIDOR DATABASE (2014, background): “DRIONS-DB contains retinal images for optic nerve head segmentation benchmarking (Carmona et al. (2008)).”
IDRiD: Diabetic Retinopathy - Segmentation and Grading Challenge. (2020, methodology): “It uses external datasets DRIONS-DB ( Carmona et al., 2008 ) and DRIVE ( van Ginneken et al., 2004 ) available with OD and vessel ground truths respectively.”
Drishti-GS: Retinal image dataset for optic nerve head(ONH) segmentation (2014, background): “Structural changes in the ONH, which consists of optic disk (OD) and cup region, is one of the standard way to assess the amount of glaucomatous damage.”