Adaptive optics with pupil tracking for high resolution retinal imaging

Abstract

Adaptive optics, when integrated into retinal imaging systems, compensates for rapidly changing ocular aberrations in real time and results in improved high resolution images that reveal the photoreceptor mosaic. Imaging the retina at high resolution has numerous potential medical applications, and yet for the development of commercial products that can be used in the clinic, the complexity and high cost of the present research systems have to be addressed. We present a new method to control the deformable mirror in real time based on pupil tracking measurements which uses the default camera for the alignment of the eye in the retinal imaging system and requires no extra cost or hardware. We also present the first experiments done with a compact adaptive optics flood illumination fundus camera where it was possible to compensate for the higher order aberrations of a moving model eye and in vivo in real time based on pupil tracking measurements, without the real time contribution of a wavefront sensor. As an outcome of this research, we showed that pupil tracking can be effectively used as a low cost and practical adaptive optics tool for high resolution retinal imaging because eye movements constitute an important part of the ocular wavefront dynamics.

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

“…Comparing what is expected from a pupil tracking at 10 Hz (which corresponds to an ideal AO set-up at 10 Hz with perfect WFS measurement and DM correction) with a pupil tracking at 80 Hz, the performance improvement in terms of wavefront rms is significant. We have compared the error budget caused by the pupil displacement with real experiments presented in [16], for a system running at around 10 Hz. It is shown that for such a system, the maximum degradation impact due to pupil displacement when compared with the use of a PT at 80 Hz may be significant.…”

“…The advantage of a PT as the one analyzed here is that it can run at a faster rate than the wavefront sensor, as mentioned in [16]. Any analysis of error budget here requires therefore the computation of differences between a reference phase screen (the corrected one) and a displaced phase screen.…”

“…In [16], the authors present an AO system running at about 10 Hz (8.4 precisely), and the AO loop led to an average rms of 0.12 ± 0.05 μm for the three studied subjects (a PT was used in this experiment at the same sampling frequency of 8.4 Hz to verify that eye aberrations were mainly frozen wavefronts moving with the eye). If we suppose that the error budget due to the eye displacement is at this frequency at most 40 nm rms (the value at 95% in Fig.…”

“…However, a number of authors noted that eye motion played a major role, see, e.g., [14,15]. Thus, at least for the purpose of efficient DM control computation, a plausible conjecture is that a major part of performance degradation can be modeled as resulting from the relative displacements of a fixed or slow-moving and subjectdependent pupil aberration, as stated in [16]. One way to investigate the implications of this conjecture in terms of achievable performance is to consider an ideal case where the aberration seen by the AO system results only from the relative horizontal and vertical relative displacements (with respect to the imaging system) of an otherwise fixed pupil aberration.…”

“…In 2012, Sahin et al [16] implemented a PT-based real-time control scheme where DM's inputs were computed by shifting a previously estimated eye aberration across the horizontal and vertical axis according to pupil displacement measurements. This experiment conducted on a robotic 'model eye' and three human test subjects showed that the PT-based control achieved a level of correction performance broadly similar to a conventional AO controller.…”