AI in Ophthalmic Diagnostics
Explore AI-assisted retinal screening, ocular imaging and responsible implementation.
Organised by Technology Innovation Hub (TIH), IIT Guwahati
7 sessions · 10.5 hours
Duration
Online / hybrid
Format
Schedule
Tuesday and Friday, 6:30–8:00 PM IST; session 7 on Tuesday of Week 4. Contact CFT for the next cohort's start date.
About this programme
Explore AI-assisted retinal screening, ocular imaging and responsible implementation.
A seven-session programme covering fundus photography, OCT, diabetic retinopathy screening, computer vision and evidence-based evaluation of ophthalmic AI. Guided demonstrations and case studies connect technical concepts to screening workflows, validation and human oversight.
What you can take forward
- Understand AI applications and limitations across ophthalmic imaging
- Evaluate screening metrics, bias, privacy and external validation
- Design an AI-assisted retinal screening workflow with referral and governance safeguards
Programme outline
Seven sessions. A practical view of the field.
Medical students, ophthalmologists, eye-care professionals and researchers
Session schedule
Tuesday and Friday, 6:30–8:00 PM IST; session 7 on Tuesday of Week 4. Contact CFT for the next cohort's start date.
How each session is structured
Each 90-minute session combines 45 minutes of faculty instruction, 30 minutes of guided demonstration or case study, and 15 minutes of discussion.
- 0190 minutes
Foundations of AI in Ophthalmic Diagnostics
Coverage
AI/ML/deep learning; retinal anatomy and diagnostic modalities; fundus photography, OCT and visual fields; clinical workflow and AI limitations.
Applied activity
Compare illustrative fundus images with AI-generated flags.
- 0290 minutes
Diabetic Retinopathy: AI Screening and Referral
Coverage
Lesion patterns; fundus image quality; DR grading; screening thresholds; sensitivity, specificity and referral escalation.
Applied activity
Review labelled fundus examples and simulated screening decisions.
- 0390 minutes
OCT, Glaucoma and Macular Disease Analytics
Coverage
OCT layer segmentation; optic nerve and retinal nerve fibre layer measures; macular abnormalities; multimodal inputs.
Applied activity
Inspect OCT segmentation and compare image-derived features.
- 0490 minutes
Computer Vision and Explainable AI
Coverage
CNNs and vision transformers; classification, detection and segmentation; dataset splits; heatmaps and failure modes.
Applied activity
Visualise image-processing workflow and saliency maps.
- 0590 minutes
Anterior Segment and Emerging Ocular AI
Coverage
Corneal imaging; slit-lamp and cataract assessment research; ocular surface imaging; eye tracking; maturity of evidence.
Applied activity
Compare published anterior-segment datasets and example predictions.
- 0690 minutes
Validation, Ethics and Regulatory Readiness
Coverage
External validation; calibration; prevalence effects; bias; data protection; consent; regulatory claims and human oversight.
Applied activity
Critique an ophthalmic AI study using a validation checklist.
- 0790 minutes
Deploying AI Screening in Healthcare
Coverage
Portable imaging; teleophthalmology; quality assurance; referral pathways; implementation costs; monitoring and governance.
Applied activity
Design a district-level AI-assisted retinal screening workflow.
Suggested assessment
Brief pre/post knowledge checks and a final applied case or workflow exercise. Suggested completion threshold: at least 80% attendance plus submission of the final exercise.
Partners
AI in healthcare and vision sciences, underwater exploration, robotics, sensors, cyber-physical systems and tech/product development.
Explore partner programmesFocus domains
The domain labels describe this programme’s catalogue alignment, not a separate promise of availability in every field.