Overview
AI analyzes retinal images and OCT to detect diabetic retinopathy glaucoma and macular disease. Automated screening expands access to eye care and early intervention. Integration with referral pathways ensures timely treatment.
Techniques
Deep learning models process fundus photos and OCT volumes for classification and segmentation. Quality control flags poor images for repeat acquisition. Multimodal fusion improves diagnostic accuracy.
Deployment
Cloud and edge solutions enable scalable screening and teleophthalmology. Training of technicians and quality assurance maintain image quality. Data governance protects patient privacy and consent.
Impact
Early detection reduces vision loss and improves population eye health. Screening programs measure referral rates and treatment outcomes. Continuous evaluation ensures program effectiveness.