Pupil tracking with a Hartmann-Shack wavefront sensor

Retinal adaptive optics imaging with a pyramid wavefront sensor

The pyramid wavefront sensor (P-WFS) has replaced the Shack-Hartmann (SH-) WFS as the sensor of choice for high-performance adaptive optics (AO) systems in astronomy. Many advantages of the P-WFS, such as its adjustable pupil sampling and superior sensitivity, are potentially of great benefit for AO-supported imaging in ophthalmology as well. However, so far no high quality ophthalmic AO imaging was achieved using this novel sensor. Usually, a P-WFS requires modulation and high precision optics that lead to high complexity and costs of the sensor. These factors limit the competitiveness of the P-WFS with respect to other WFS devices for AO correction in visual science. Here, we present a cost-effective realization of AO correction with a non-modulated P-WFS based on standard components and apply this technique to human retinal in vivo imaging using optical coherence tomography (OCT). P-WFS based high quality AO imaging was successfully performed in 5 healthy subjects and smallest retinal cells such as central foveal cone photoreceptors are visualized. The robustness and versatility of the sensor is demonstrated in the model eye under various conditions and in vivo by high-resolution imaging of other structures in the retina using standard and extended fields of view. As a quality benchmark, the performance of conventional SH-WFS based AO was used and successfully met. This work may trigger a paradigm shift with respect to the wavefront sensor of choice for AO in ophthalmic imaging.

Adaptive optics retinal imaging with automatic detection of the pupil and its boundary in real time using Shack-Hartmann images

Retinal imaging with an adaptive optics (AO) system usually requires that the eye be centered and stable relative to the exit pupil of the system. Aberrations are then typically corrected inside a fixed circular pupil. This approach can be restrictive when imaging some subjects, since the pupil may not be round and maintaining a stable head position can be difficult. In this paper, we present an automatic algorithm that relaxes these constraints. An image quality metric is computed for each spot of the Shack-Hartmann image to detect the pupil and its boundary, and the control algorithm is applied only to regions within the subject's pupil. Images on a model eye as well as for five subjects were obtained to show that a system exit pupil larger than the subject's eye pupil could be used for AO retinal imaging without a reduction in image quality. This algorithm automates the task of selecting pupil size. It also may relax constraints on centering the subject's pupil and on the shape of the pupil.

Pupil motion analysis and tracking in ophthalmic systems equipped with wavefront sensing technology

Our eyes are constantly in motion, even during "steady" fixation. In ophthalmic systems equipped with wavefront technology, both eye and head motion potentially degrade its performance and/or increase the cost and complexity, as they induce a movement of the entrance optical pupil of the system. Here, we characterize the pupil motion in an aberrometry setting, using a custom, high-speed pupil tracker (478 Hz), and draw conclusions on design considerations of future ophthalmic systems. We also demonstrate the feasibility of tracking such motion directly with a custom-built Hartmann-Shack sensor (236 Hz) using a method that offers certain benefits over previously suggested approaches, thereby paving the way to an efficient and cost-effective approach.

Eye-pupil displacement and prediction: effects on residual wavefront in adaptive optics retinal imaging

This paper studies the effect of pupil displacements on the best achievable performance of retinal imaging adaptive optics (AO) systems, using 52 trajectories of horizontal and vertical displacements sampled at 80 Hz by a pupil tracker (PT) device on 13 different subjects. This effect is quantified in the form of minimal root mean square (rms) of the residual phase affecting image formation, as a function of the delay between PT measurement and wavefront correction. It is shown that simple dynamic models identified from data can be used to predict horizontal and vertical pupil displacements with greater accuracy (in terms of average rms) over short-term time horizons. The potential impact of these improvements on residual wavefront rms is investigated. These results allow to quantify the part of disturbances corrected by retinal imaging systems that are caused by relative displacements of an otherwise fixed or slowy-varying subject-dependent aberration. They also suggest that prediction has a limited impact on wavefront rms and that taking into account PT measurements in real time improves the performance of AO retinal imaging systems.