Deep Learning for Segmentation and Progression Analysis of Diabetic Macular Edema (DME) on Optical Coherence Tomography
CoI: Dr. Adi Al Owaifeer (King Khaled Eye Specialist Hospital)
Description: Diabetic Macular Edema (DME) is a major cause of vision loss among working-age individuals and places a growing burden on Saudi healthcare. This project, conducted in collaboration with KKESH, will develop two deep-learning models using de-identified longitudinal OCT data: a segmentation model to quantify retinal layers, fluid, cysts, and deposits, and a progression model to classify disease status as improving, stable, or worsening. The models aim to provide objective, reproducible, and personalized support for DME diagnosis and treatment planning, while reducing unnecessary procedures and healthcare costs. The validated models will be integrated into existing clinical workflows, documented as reproducible Python modules, and support a Q1 journal submission and future national-scale research.