A Strabismus Detection System Based on Digital Twin

Strabismus is a disease caused by extraocular muscles, which not only has serious consequences on vision, but also has a serious impact on patients' psychology, work and employment, quality of life, and other aspects. With the development of deep learning and artificial intelligence, modern computational image processing technology has been further improved, especially in areas such as image denoising, edge detection, image segmentation, target recognition, feature extraction, etc., making computer-aided intelligent strabismus diagnosis technology increasingly attracting the attention of researchers. However, the research in the field of intelligent strabismus diagnosis is not yet mature. This article constructs twin data based on the eye images of strabismus patients, references typical strabismus sign detection data and image libraries, and then uses the improved Faster R-CNN algorithm to implement an intelligent strabismus detection system based on “digital twins”, providing a certain reference for the in-depth research of intelligent strabismus detection and diagnosis.