The current health care approach for chronic care, such as glaucoma, has limitations for access to expert care and tomeet the growing needs of a larger population of older adults who will develop glaucoma. The computer aideddiagnosis system (CAD) shows great promise to fill this gap. Our purpose is to expand the initial fundus datasetcalled Retinal fundus Images for Glaucoma Analysis (RIGA) to develop collaborative image processing methods toautomate quantitative optic nerve assessments from fundus photos. All the subjects were women and enrolled in anIRBMED protocol. The fundus photographs were taken using Digital Retinography System (DRS), which isdedicated for diabetic retinopathy screening. Among initial 245 photos, there were 166 photos that met qualityassurance metrics for analysis and serve as RIGA2 dataset. Three glaucoma fellowship trained ophthalmologistsperformed various tasks on these photos. In addition, the cup to disc ratio (CDR) and the neuroretinal rim thicknessfor the subjects were assessed by slit lamp biomicroscopy and served as the gold standard measure. This RIGA2dataset is additional 2D color disc photos resource, and multiple extracted features that serves the researchcommunity as a form of crowd sourcing analytical power in the growing teleglaucoma field.
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