NetraSetu: Explainable DR Screening

What it does

NetraSetu is an explainable AI-powered diabetic retinopathy screening solution designed for rural India. It analyzes retinal images to support early detection, provides transparent and understandable results, and helps healthcare workers make informed referral decisions. By enabling affordable, accessible, and trustworthy screening, NetraSetu aims to reduce preventable vision loss and strengthen eye care in underserved communities.

Offline-capable, explainable diabetic retinopathy screening built on a MATLAB pipeline: image quality AI, lesion evidence, calibrated grading and specialist triage.

Built on a MATLAB image-processing and deep-learning pipeline: judge the photograph, enhance it, show the lesions, grade it on the international scale — and hand doubtful eyes to a human. Blur, illumination, evenness, contrast and field-of-view are scored first. Ungradable images get spoken recapture instructions instead of a false result. Microaneurysms, haemorrhages and exudates are circled on the image, with a Grad-CAM++ map for the predicted grade. Temperature-scaled confidence and entropy-based uncertainty route doubtful cases to an ophthalmologist rather than guessing. The whole pipeline executes on the device so screening continues without connectivity; records sync later. A queueing…from netrasetu-zinovagroup.vercel.app

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