Optical Coherence Tomography Angiography-OCTA dataset for the study of Diabetic Retinopathy
This dataset addresses the need for accessible data to improve diabetic retinopathy diagnosis, but it is incremental as it adds to existing resources without introducing new methods.
The study presents a dataset of 268 retinal OCTA images from 179 individuals, annotated by ophthalmologists, to enable the development of automated diagnostic tools for early detection of diabetic retinopathy.
This study presents a dataset consisting of 268 retinal images from 179 individuals, including 133 left-eye and 135 right-eye images, collected from Natasha Eye Care and Research Institute in Pune, Maharashtra, India. The images were captured using a nonmydriatic Optical Coherence Tomography Angiography (OCTA) device, specifically the Optovue Avanti Edition machine as per the protocol mentioned in this paper. Two ophthalmologists then annotated the images. This dataset can be used by researchers and doctors to develop automated diagnostic tools for early detection of diabetic retinopathy (DR).