Optimizing Optical Coherence Tomography Scanning Efficiency with Low-Rate Acquisition and AI-Based Image Synthesis

Perimeter Medical has been developing a novel optical coherent tomography (OCT) technique combined with AI to analyze tissue edges quickly. This project aims to make the method faster by acquiring images more efficiently. This will help surgeons assess tissues quicker and shorten surgery times, which in turn will lead to less time for patients to remain under sedation. Using an AI synthesis approach, we strive to speed up the OCT scanning process. The proposed strategy is to test this approach using some existing OCT images to teach an AI algorithm how to generate the missing ones. We will compare the predicted OCT image results to the originals using image quality metrics to ensure the generated images are accurate. This project will be the first step in evaluating the feasibility of a faster OCT imaging in helping surgeons and patients alike.

Faculty Supervisor:

Kumaradevan Punithakumar;Michelle Noga

Student:

Partner:

Perimeter

Discipline:

Computer science

Sector:

Health and Related Sciences & Technology; Artificial Intelligence

University:

University of Alberta

Program: