AI in Ophthalmology triage automation

Access to specialist care, especially in rural and remote locations, is a growing challenge in Alberta. Patients with conditions such as age-related macular degeneration, diabetes, and macular edema must travel to large urban centres for assessment by retinal specialist ophthalmologists. Assessment typically requires OCT imaging, which is now broadly available through optometrist offices across the province. The ability to streamline or semi-automate retinal image analysis has the potential to improve patient access, the patient experience and virtual care within their communities.
The intern will help develop, refine, and test a retinal image analysis system using image processing techniques, natural language processing techniques and the latest advances in large multi-modal models, on a large dataset of OCT images from a retinal practice, with diagnosis and interpretations. This project is exploratory, with the potential for further technology development by the partner organization.

Faculty Supervisor:

Irene Cheng

Student:

Partner:

OKAKI

Discipline:

Computer science

Sector:

Health and Related Sciences & Technology; Information and cultural industries; Professional, scientific and technical services

University:

University of Alberta

Program: