Summary: UCLA researchers in the Department of Computational Medicine have developed a computer program capable of automatically and accurately diagnosing optical diseases using OCT.
Background: Optical diseases, such as age-related macular degeneration, are serious issues that, if left untreated, can result in partial and even complete blindness. Current diagnosis methods are time consuming and expensive as specially trained physicians are needed to perform and analyze the eye exam results. This leads to both longer diagnosis times and incomplete diagnoses as there may have been unexamined data that physicians did not have time to comprehensively review. There is a need for an automated method that can accurately review images and determine a diagnose to reduce costs and improve patient care.
Innovation: Researchers at UCLA have developed a computer program that can diagnose ocular diseases using information gathered from optical coherence tomography (OCT). The program has been successfully tested to make an accurate diagnosis requiring fewer images compared to a trained physician. By automating this process, this program reduces workload spent by medical professions reviewing images and allows them to review images on an as needed, rather than required, basis. In addition, removing human optimizes the clinical workflow by reducing the workload on physicians and providing additional protection from misdiagnosis. Patent: Methods and systems for biomarker prediction using optical coherence tomography
Potential Applications: • Diagnosis of ocular diseases • Potential use with other imaging devices like MRIs
Advantages: • Very accurate with less data • Can be applied for multiple diagnosis • Helps to optimize clinical workflow • Automated
Development to Date: The program has successful been able to determine diagnoses based on provided images. Related Publications: A generative AI model for accurate reconstruction of retinal blood flow from static OCT scans