Non-proliferative diabetic retinopathy detection using Rosmarus Quagga optimized explainable generative meta learning based deep convolutional neural network model.
Journal:
International ophthalmology
PMID:
40338363
Abstract
PURPOSE: Non-Proliferative Diabetic Retinopathy (NPDR) is a complication of diabetes disease where there is damage of the blood vessels in retina but with no signs of formation of new vessels. It is present in the earlier stages and therefore the control of diabetes combined with constant check-up can address the challenge. Existing models face several challenges such as heterogeneity of the lesion with regard to size, shape, and distribution. Therefore, to reduce those existing challenges, in this research, a novel model Rosmarus Quagga optimized Explainable generative Meta learning based Deep Convolutional Neural Network (RQ-EGMCN) is proposed for Non-Proliferative Diabetic Retinopathy. The main purpose of the proposed research is to develop and validate the effective diagnosis of severe DR with lesion recognition using the retinal images.