Hans R. G. W. Verstraete

Model-based sensor-less wavefront aberration correction in optical coherence tomography

Several sensor-less wavefront aberration correction methods that correct nonlinear wavefront aberrations by maximizing the optical coherence tomography (OCT) signal are tested on an OCT setup. A conventional coordinate search method is compared to two model-based optimization methods. The first model-based method takes advantage of the well-known optimization algorithm (NEWUOA) and utilizes a quadratic model. The second model-based method (DONE) is new and utilizes a random multidimensional Fourier-basis expansion. The model-based algorithms achieve lower wavefront errors with up to ten times fewer measurements. Furthermore, the newly proposed DONE method outperforms the NEWUOA method significantly. The DONE algorithm is tested on OCT images and shows a significantly improved image quality.

Towards model-based adaptive optics optical coherence tomography

The transfer function for optical wavefront aberrations in single-mode fiber based optical coherence tomography is determined. The loss in measured OCT signal due to optical wavefront aberrations is quantified using Fresnel propagation and the calculation of overlap integrals. A distinction is made between a model for a mirror and a scattering medium model. The model predictions are validated with measurements on a mirror and a scattering medium obtained with an adaptive optics optical coherence tomography setup. Furthermore, a one-step defocus correction, based on a single A-scan measurement, is derived from the model and verified. Finally, the pseudo-convex structure of the optical coherence tomography transfer function is validated with the convergence of a hill climbing algorithm. The implications of this model for wavefront sensorless aberration correction are discussed.

Wavefront sensorless adaptive optics OCT with the DONE algorithm for in vivo human retinal imaging [Invited]

In this report, which is an international collaboration of OCT, adaptive optics, and control research, we demonstrate the Data-based Online Nonlinear Extremum-seeker (DONE) algorithm to guide the image based optimization for wavefront sensorless adaptive optics (WFSL-AO) OCT for in vivo human retinal imaging. The ocular aberrations were corrected using a multi-actuator adaptive lens after linearization of the hysteresis in the piezoelectric actuators. The DONE algorithm succeeded in drastically improving image quality and the OCT signal intensity, up to a factor seven, while achieving a computational time of 1 ms per iteration, making it applicable for many high speed applications. We demonstrate the correction of five aberrations using 70 iterations of the DONE algorithm performed over 2.8 s of continuous volumetric OCT acquisition. Data acquired from an imaging phantom and in vivo from human research volunteers are presented.

High speed wavefront sensorless aberration correction in digital micromirror based confocal microscopy

The quality of fluorescence microscopy images is often impaired by the presence of sample induced optical aberrations. Adaptive optical elements such as deformable mirrors or spatial light modulators can be used to correct aberrations. However, previously reported techniques either require special sample preparation, or time consuming optimization procedures for the correction of static aberrations. This paper reports a technique for optical sectioning fluorescence microscopy capable of correcting dynamic aberrations in any fluorescent sample during the acquisition. This is achieved by implementing adaptive optics in a non conventional confocal microscopy setup, with multiple programmable confocal apertures, in which out of focus light can be separately detected, and used to optimize the correction performance with a sampling frequency an order of magnitude faster than the imaging rate of the system. The paper reports results comparing the correction performances to traditional image optimization algorithms, and demonstrates how the system can compensate for dynamic changes in the aberrations, such as those introduced during a focal stack acquisition though a thick sample.

Online Optimization With Costly and Noisy Measurements Using Random Fourier Expansions

This paper analyzes data-based online nonlinear extremum-seeker (DONE), an online optimization algorithm that iteratively minimizes an unknown function based on costly and noisy measurements. The algorithm maintains a surrogate of the unknown function in the form of a random Fourier expansion. The surrogate is updated whenever a new measurement is available, and then used to determine the next measurement point. The algorithm is comparable with Bayesian optimization algorithms, but its computational complexity per iteration does not depend on the number of measurements. We derive several theoretical results that provide insight on how the hyperparameters of the algorithm should be chosen. The algorithm is compared with a Bayesian optimization algorithm for an analytic benchmark problem and three applications, namely, optical coherence tomography, optical beam-forming network tuning, and robot arm control. It is found that the DONE algorithm is significantly faster than Bayesian optimization in the discussed problems while achieving a similar or better performance.

Feedforward operation of a lens setup for large defocus and astigmatism correction

In this manuscript, we present a lens setup for large defocus and astigmatism correction. A deformable defocus lens and two rotational cylindrical lenses are used to control the defocus and astigmatism. The setup is calibrated using a simple model that allows the calculation of the lens inputs so that a desired defocus and astigmatism are actuated on the eye. The setup is tested by determining the feedforward prediction error, imaging a resolution target, and removing introduced aberrations.

Numerical Evaluation of Advanced Optimization Algorithms for Wavefront Aberration Correction in OCT

Several advanced optimization algorithms are tested and optimized on an OCT wavefront aberration model. Lower errors are achieved with ten time less measurements when compared to a conventional coordinate-search algorithm.

Adaptive optics plug-and-play setup for high-resolution microscopes with multi-actuator adaptive lens

Adaptive Optics (AO) has revealed as a very promising technique for high-resolution microscopy, where the presence of optical aberrations can easily compromise the image quality. Typical AO systems however, are almost impossible to implement on commercial microscopes. We propose a simple approach by using a Multi-actuator Adaptive Lens (MAL) that can be inserted right after the objective and works in conjunction with an image optimization software allowing for a wavefront sensorless correction. We presented the results obtained on several commercial microscopes among which a confocal microscope, a fluorescence microscope, a light sheet microscope and a multiphoton microscope.

Wavefront control with a multi-actuator adaptive Lens in imaging applications

The use of adaptive lenses instead of deformable mirrors can simplify the implementation of an adaptive optics system. The recently introduced Multi-actuator Adaptive Lens (MAL) can be used in closed loop with a wavefront sensor to correct for time-variant wavefront aberrations. The MAL can guarantee a level of correction and a response time similar to the ones obtained with deformable mirrors. The adaptive lens is based on the use of piezoelectric actuators and, without any obstruction or electrodes in the clear aperture, can guarantee a fast response time, less than ~10ms. Our tests show that the MAL can be used both in combination with a wavefront sensor in a “classical” adaptive optics closed loop, or in a wavefront sensorless configuration. The latter has allowed us to design more compact and simple imaging systems for different microscopy platforms. We will show that the Multi-actuator Adaptive Lens has been successfully used for in-vivo OCT ophthalmic imaging in both mice and humans, as well as confocal and two photon microscopy. We tested and compared different optimization strategies such as coordinate search and the DONE algorithm. The results suggest that the MAL optimization can correct for eye aberrations with a pupil of 5mm or sample induced aberrations in microscopy.

Real time optimization algorithm for wavefront sensorless adaptive optics OCT (Conference Presentation)

Optical Coherence Tomography (OCT) has revolutionized modern ophthalmology, providing depth resolved images of the retinal layers in a system that is suited to a clinical environment. A limitation of the performance and utilization of the OCT systems has been the lateral resolution. Through the combination of wavefront sensorless adaptive optics with dual variable optical elements, we present a compact lens based OCT system that is capable of imaging the photoreceptor mosaic. We utilized a commercially available variable focal length lens to correct for a wide range of defocus commonly found in patient eyes, and a multi-actuator adaptive lens after linearization of the hysteresis in the piezoelectric actuators for aberration correction to obtain near diffraction limited imaging at the retina. A parallel processing computational platform permitted real-time image acquisition and display. The Data-based Online Nonlinear Extremum seeker (DONE) algorithm was used for real time optimization of the wavefront sensorless adaptive optics OCT, and the performance was compared with a coordinate search algorithm. 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. Applying the DONE algorithm in vivo for wavefront sensorless AO-OCT demonstrates that the DONE algorithm succeeds in drastically improving the signal while achieving a computational time of 1 ms per iteration, making it applicable for high speed real time applications.