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Multimodal dataset using OCTA and fundus images for the study of diabetic retinopathy
Pooja Bidwai1, Shilpa Gite1, Aditi Gupta2
1Symbiosis Centre for Applied Artificial Intelligence (SCAAI) Symbiosis Institute of Technology, Symbiosis International (Deemed University) (SIU), Lavale, Pune 412115, India.
Abstract:
This article presents a Multimodal database consisting of 222 images of 76 people wherein 111 are OCTA images and 111 are color fundus images taken at the Natasha Eye Care and Research Institute of Pune Maharashtra, India. Nonmydriatic fundus images were acquired using a confocal SLO widefield fundus imaging Eidon machine. Nonmydriatic OCTA images were acquired using the Optovue Avanti Edition machine Initially, the clinical approach described in this article was used to obtain the retinal images. Following that, the dataset was categorized by two experienced eye specialists. To identify instances of Non-Proliferative Diabetic Retinopathy (NPDR) with their various stages, medical professionals and scholars can use this data. Research scholars and ophthalmologists can utilize the data created to develop the initial stages of automated identification techniques for diabetic retinopathy (DR).
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