Automatic optimization high-speed high-resolution OCT retinal imaging at 1μm

Abstract

High-resolution OCT retinal imaging is important in providing visualization of various retinal structures to aid researchers in better understanding the pathogenesis of vision-robbing diseases. However, conventional optical coherence tomography (OCT) systems have a trade-off between lateral resolution and depth-of-focus. In this report, we present the development of a focus-stacking optical coherence tomography (OCT) system with automatic optimization for high-resolution, extended-focal-range clinical retinal imaging. A variable-focus liquid lens was added to correct for de-focus in real-time. A GPU-accelerated segmentation and optimization was used to provide real-time layer-specific enface visualization as well as depth-specific focus adjustment. After optimization, multiple volumes focused at different depths were acquired, registered, and stitched together to yield a single, high-resolution focus-stacked dataset. Using this system, we show high-resolution images of the ONH, from which we extracted clinically-relevant parameters such as the nerve fiber layer thickness and lamina cribrosa microarchitecture.