QUT researchers use AI to bring sharper focus to eye testing

QUT researchers have applied artificial intelligence (AI) deep learning techniques to develop a more accurate and detailed method for analysing images of the back of the eye to help clinicians better detect and track eye diseases, such as glaucoma and aged-related macular degeneration. Their findings have been published in Nature Scientific Reports. Study lead author QUT Senior Research Fellow Dr David Alonso-Caneiro, from the Faculty of Health School of Optometry and Vision Science, said the team had explored a range of state-of-the-art deep learning techniques to analyse Optical Coherence Tomography (OCT) images. OCT is a common instrument used by optometrists and ophthalmologists. It takes cross-sectional images of the eye which show different tissue layers.