A compact retinal camera with adaptive optics which was designed for clinical practice was used to test a new
adaptive optics control algorithm to correct for the angular ray deviations of a model eye. The new control
algorithm is based on pupil movements rather than the measurement of the slopes of the wavefront with an
optoelectronic sensor. The method for the control algorithm was based on the hypothesis that majority of the
changes of the aberrations of the eye are due to head and eye movements and it is possible to correct for the
aberrations of the eye by shifting the paraxial correction according to the new position of the pupil. Since
the fixational eye movements are very small, the eye movements are assumed to be translational rather than
rotational. Using the new control algorithm it was possible to simulate the aberrations of the moving model eye
based on pupil tracking. The RMS of the residual wavefront error of the simulation had a magnitude similar
to the RMS of the residual wavefront error of the adaptive optics correction based on optoelectronic sensor for
angular ray deviations. If our hypothesis is true and other factors such as the tear film or the crystalline lens
fluctuations do not cause changes in the aberrations of the eye as much as motion does, the method is expected
to work in vivo as it did for a model eye which had no intrinsic factors that cause aberration changes.
The effects of pupil motion on retinal imaging are studied in this paper. Involuntary eye or head movements
are always present in the imaging procedure, decreasing the output quality and preventing a more detailed
diagnostics. When the image acquisition is performed using an adaptive optics (AO) system, substantial gain is
foreseen if pupil motion is accounted for. This can be achieved using a pupil tracker as the one developed by
Imagine Eyes R®, which provides pupil position measurements at a 80Hz sampling rate. In any AO loop, there
is inevitably a delay between the wavefront measurement and the correction applied to the deformable mirror,
meaning that an optimal compensation requires prediction. We investigate several ways of predicting pupil
movement, either by retaining the last value given by the pupil tracker, which is close to the optimal solution in
the case of a pure random walk, or by performing position prediction thanks to auto-regressive (AR) models with
parameters updated in real time. We show that a small improvement in prediction with respect to predicting
with the latest measured value is obtained through adaptive AR modeling. We evaluate the wavefront errors
obtained by computing the root mean square of the difference between a wavefront displaced by the assumed
true position and the predicted one, as seen by the imaging system. The results confirm that pupil movements
have to be compensated in order to minimize wavefront errors.
Adaptive Optics (AO) is particularly suitable for correction of aberrations that change over time - a necessity for high
resolution imaging of the retina. The rapidly changing aberrations originating from eye movements require wavefront
sensors (WFS) with high repetition rates. Our approach is enhancing aberration correction by integrating a Pupil
Tracking System (PTS) into the AO loop of the retinal imaging system. In this study we assessed the performance of the
PTS developed for this purpose. Tests have demonstrated that the device achieves an accuracy of <15 μm in a ±2 mm
range of eye movements with a standard deviation <10 μm. PTS can tolerate ±5 mm defocus with an increase of 4 μm in
mean standard deviation. In vivo measurements done with temporarily paralyzed pupils have resulted in a precision of approximately 13 μm.
High-resolution imaging of the retina is a challenge due to the optical aberrations introduced by the eye, a living system
in constant change and motion. Adaptive Optics (AO) is particularly suited to the continuous, dynamic correction of
aberrations as they change over time. In particular, eye pupil displacements induce fast-changing wave front errors
which lead to a need for faster wave front sensors. We propose a new approach for ocular adaptive optics by adding a
Pupil Tracking System (PTS) into the AO loop. This system is different from the existing eye tracking devices by its
speed, high precision in a short range and therefore its suitability for integration in an AO loop. Performance tests done
using an artificial eye with a pupil diameter of 7 mm have shown promising results. These tests have demonstrated that
the device achieves an accuracy of <15 μm in a ±2 mm range of eye movements with a standard deviation <10 μm, and
requires less than 12 ms for each detection.
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