anand000009999/Ocunexa-Clinical-Kiosk
OCUNEXA โ Explainable AI for Diabetic Retinopathy Screening in Rural India (SIH26038)
An explainable, human-in-the-loop AI screening and clinical decision-support system designed to enable accessible, reliable and scalable Diabetic Retinopathy (DR) screening in rural and resource-constrained healthcare settings.
๐ฉบ Overview
Diabetic Retinopathy is a major cause of preventable vision loss, yet access to regular retinal screening remains limited in rural areas due to shortage of ophthalmologists, large screening populations, variable-quality fundus images and poor connectivity.
OCUNEXA (LaxmiAI / NetraX) addresses these challenges through an intelligent retinal screening pipeline that combines automated image quality assessment, retinal structure analysis, lesion detection (YOLO26 Nano), vascular graph analysis (GAT GNN), explainable AI (KAN B-Splines) and confidence-based ophthalmologist escalation.
The system is designed to support healthcare workers at Primary Health Centres (PHCs) while keeping ophthalmologists in the clinical decision loop.
๐ก Proposed Solution
The complete screening pipeline follows:
Portable Fundus Camera โ Image Quality Assessment โ Enhancement โ Retinal Structure & ETDRS Mapping โ YOLO26 + GNN/GAT Analysis โ Feature Fusion โ 5-Level DR Grading โ Confidence Gate โ Explainable Report โ Referral / Monitoring
๐๏ธ System Architecture
PORTABLE FUNDUS CAMERA
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IMAGE QUALITY ASSESSMENT
(Tenengrad, Illumination, FOV)
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[Accept] [Reject] โโโบ Recapture Required
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IMAGE ENHANCEMENT
(CLAHE, Green Channel, Denoise)
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RETINAL STRUCTURE & ETDRS MAPPING
(Optic Disc, Fovea, Grid Zones)
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YOLO26 GNN KAN
Segment Vascular Fusion
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FEATURE FUSION
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5-LEVEL DR GRADING
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CONFIDENCE GATE
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High Confidence Low / Conflicting
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Report / Ophthalmologist
Referral Review