Data-based online nonlinear extremum-seeker for wavefront sensorless adaptive optics OCT (Conference Presentation)

Abstract

Adaptive optics has been successfully applied to cellular resolution imaging of the retina, enabling visualization of the characteristic mosaic patterns of the outer retina. Wavefront sensorless adaptive optics (WSAO) is a novel technique that facilitates high resolution ophthalmic imaging; it replaces the Hartmann-Shack Wavefront Sensor with an image-driven optimization algorithm and mitigates some the challenges encountered with sensor-based designs. However, WSAO generally requires longer time to perform aberrations correction than the conventional closed-loop adaptive optics. When used for in vivo retinal imaging applications, motion artifacts during the WSAO optimization process will affect the quality of the aberration correction. A faster converging optimization scheme needs to be developed to account for rapid temporal variation of the wavefront and continuously apply corrections. In this project, we investigate the Databased Online Nonlinear Extremum-seeker (DONE), a novel non-linear multivariate optimization algorithm in combination with in vivo human WSAO OCT imaging. We also report both hardware and software updates of our compact lens based WSAO 1060nm swept source OCT human retinal imaging system, including real time retinal layer segmentation and tracking (ILM and RPE), hysteresis correction for the multi-actuator adaptive lens, precise synchronization control for the 200kHz laser source, and a zoom lens unit for rapid switching of the field of view. Cross sectional images of the retinal layers and en face images of the cone photoreceptor mosaic acquired in vivo from research volunteers before and after WSAO optimization are presented.