Automated image analysis for Diabetic Retinopathy Screening with iPhone-based fundus camera

Purpose : Vision loss from diabetic retinopathy (DR) in ever-increasing population of diabetic patients can be prevented by early screening and diagnosis. To meet this growing need for screening, we present a cost-effective, end-to-end, point-of-care DR screening setup comprising a) iPhone based retinal camera, Ocular Cellscope, and b) analysis software for automated DR screening Methods : The

Automated diabetic retinopathy detection in smartphone-based fundus photography using artificial intelligence

Objectives To assess the role of artificial intelligence (AI)-based automated software for detection of diabetic retinopathy (DR) and sight-threatening DR (STDR) by fundus photography taken using a smartphone-based device and validate it against ophthalmologist’s grading. Methods Three hundred and one patients with type 2 diabetes underwent retinal photography with Remidio ‘Fundus on phone’ (FOP), a