Optical coherence tomography – machine learning

Summary Machine learning is a method of data analysis. It gives computers the ability to learn from data and to build models from which predictions can be made. Even though OCT is mainly used to visualize retinal structures and compute thickness maps, it conveys information on subtle changes within the retina before structural ones can be identified. Exposing the machine learning model to a set of examples allows it to build a model from which predictions can be made on new data and explain differences between groups. This lecture will explain the underlying principles of machine learning and discuss potential applications in ophthalmology and CNS disorders through the imaging of the retina.