AI-Powered Glaucoma Detection

Problem Statement

Healthcare providers face rising challenges in early glaucoma diagnosis, with traditional methods relying on costly OCT scans and time-consuming manual reviews. This limits accessibility, especially in remote areas, and increases the burden on specialists. An AI glaucoma detection solution using fundus imaging automates classification, calculates the cup-to-disc ratio, and identifies key indicators with >90% accuracy. The result is automated eye screening that reduces costs, scales efficiently, and improves patient outcomes through AI ophthalmology innovation.

Solution

Tata Elxsi’s AI-powered glaucoma detection is designed to overcome limitations of manual eye screening, high costs of OCT, and reliance on specialists. This solution uses fundus imaging and advanced AI ophthalmology techniques to deliver scalable, accessible, and accurate detection of glaucoma.

• AI Glaucoma Detection – Automated classification of fundus images into “Glaucoma” and “Non-Glaucoma” cases.
• Cup-to-Disc Ratio (CDR) Calculation – Threshold-based analysis adapted for different ethnicities.
• Multi-Feature Identification – Detection of nine glaucoma-specific features including large cup, rim thinning, and disc hemorrhage.
• Deep Learning Integration – CNN, RNN, TensorFlow, and PyTorch models for high detection accuracy.
• Seamless Integration – Compatibility with existing ophthalmic equipment for hospital and clinic adoption.

Tata Elxsi’s solution enables automated eye screening at scale, reducing screening time and cost while improving early glaucoma diagnosis. This ensures wider accessibility, preventive eye health, and better patient outcomes.

Impact

• Accuracy & Reliability – Achieves >90% detection accuracy in early trials, reducing false negatives and ensuring consistent AI glaucoma detection.
• Speed & Efficiency – Cuts screening time by 40–50% compared to manual fundus examination, enabling faster decision-making.
• Accessibility – Expands reach through scalable screening in rural and underserved areas with fundus imaging.
• Specialist Burden Reduction – Lowers dependency on ophthalmologists for initial screening by up to 60%.
• Better Outcomes – Early glaucoma diagnosis improves treatment success rates by 30–40%, supporting preventive eye health.
• Cost Savings – 30–35% lower costs versus OCT-based screening, making it more affordable at scale.

Services Rendered

• AI Glaucoma Detection using fundus imaging for early-stage screening
• Automated Eye Screening with cup-to-disc ratio (CDR) calculation
• Deep Learning Eye Care with multi-feature glaucoma identification
• Scalable Screening Solutions for hospitals, clinics, and remote healthcare
• AI Ophthalmology Integration with existing ophthalmic equipment