Guest Edited Collection: Quantitative and computational techniques in optical coherence tomography

Abstract

Abstract Optical coherence tomography (OCT) is a three-dimensional optical imaging technique, frequently (but not exclusively) used for retinal imaging, that was first reported in the early 1990s. Since this time the technological development of OCT has been strongly influenced by its potential as a medical imaging technique. The first clinical prototype for use in ophthalmology was completed in 1994, paving the way for the first commercially available ophthalmic OCT system to be released to the market in 1996. Since then, OCT has become a mainstay of ophthalmology. OCT is also widely used in research, in an array of biomedical applications, and increasingly in industrial settings. Although there is still much activity in advancing OCT technology, there has been an increased emphasis in applying OCT to translational research. One direction of this research is in the development of quantitative and computational techniques to aid in the retrieval of clinically useful information from OCT images. This Collection brings together original research articles, which exploit realistic mathematical models of OCT image formation and machine learning approaches to obtain insight not otherwise available from raw OCT images. This includes research for measuring clinically relevant parameters such as retinal nerve fibre layer thickness, fractional flow reserve, and corneal biomechanics, and for performing feature identification and image process tasks.