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

Optimization of DMD-based independent amplitude and phase modulation by analysis of target complex wavefront

The paper presents the results of a comprehensive study on the optimization of independent amplitude and phase wavefront manipulation which is implemented using a binary digital micromirror device. The study aims to investigate the spatial resolution and quantization achievable using this approach and its optimization based on the parameters of the target complex wave and the modulation error estimation. Based on a statistical analysis of the data, an algorithm for selecting parameters (carrier frequency of binary pattern and aperture for the first diffraction order filtering) that ensures the optimal quality of the modulated wavefront was developed. The algorithm takes into account the type of modulation, that is, amplitude, phase, or amplitude-phase, the size of the encoded distribution, and its requirements for spatial resolution and quantization. The results of the study will greatly contribute to the improvement of modulated wavefront quality in various applications with different requirements for spatial resolution and quantization.

Experimental determination of shift-less aberration bases for sensorless adaptive optics in nonlinear microscopy

Adaptive optics can improve the performance of optical systems and devices by correcting phase aberrations. While in most applications wavefront sensing is employed to drive the adaptive optics correction, some microscopy methods may require sensorless optimization of the wavefront. In these cases, the correction is performed by describing the aberration as a linear combination of a base of influence functions, optimizing an image quality metric as a function of the coefficients. The influence functions base is generally chosen to either efficiently represent the adaptive device used or to describe generic wavefronts in an orthogonal fashion. A rarely discussed problem is that most correction bases have elements which introduce, together with a correction of the aberration, a shift of the imaging field of view in three dimensions. While simple methods to solve the problem are available for linear microscopy methods, nonlinear microscopy techniques such as multiphoton or second harmonic generation microscopy require non-trivial base determination. In this paper, we discuss the problem, and we present a method for calibrating a shift-less base on a spatial light modulator for two-photon microscopy.

Adaptive optics for dynamic aberration compensation using parallel model-based controllers based on a field programmable gate array

Adaptive optics (AO) is an effective technique for compensating the aberrations in optical systems and restoring their performance for various applications such as image formation, laser processing, and beam shaping. To reduce the controller complexity and extend the compensation capacity from static aberrations to dynamic disturbances, the present study proposes an AO system consisting of a self-built Shack-Hartmann wavefront sensor (SHWS), a deformable mirror (DM), and field programmable gate array (FPGA)-based controllers. This AO system is developed for tracking static and dynamic disturbances and tuning the controller parameters as required to achieve rapid compensation of the incoming wavefront. In the proposed system, the FPGA estimates the coefficients of the eight Zernike modes based on the SHWS with CameraLink operated at 200 Hz. The estimated coefficients are then processed by eight parallel independent discrete controllers to generate the voltage vectors to drive the DM to compensate the aberrations. To have the DM model for controller design, the voltage vectors are identified offline and are optimized by closed-loop controllers. Furthermore, the controller parameters are tuned dynamically in accordance with the main frequency of the aberration as determined by a fast Fourier transform (FFT) process. The experimental results show that the AO system provides a low complexity and effective means of compensating both static aberrations and dynamic disturbance up to 20 Hz.

Conformal convolutional neural network (CCNN) for single-shot sensorless wavefront sensing

Wavefront sensing technique is essential in deep tissue imaging, which guides spatial light modulator to compensate wavefront distortion for better imaging quality. Recently, convolutional neural network (CNN) based sensorless wavefront sensing methods have achieved remarkable speed advantages via single-shot measurement methodology. However, the low efficiency of convolutional filters dealing with circular point-spread-function (PSF) features makes them less accurate. In this paper, we propose a conformal convolutional neural network (CCNN) that boosts the performance by pre-processing circular features into rectangular ones through conformal mapping. The proposed conformal mapping reduces the number of convolutional filters that need to describe a circular feature, thus enables the neural network to recognize PSF features more efficiently. We demonstrate our CCNN could improve the wavefront sensing accuracy over 15% compared to a traditional CNN through simulations and validate the accuracy improvement in experiments. The improved performances make the proposed method promising in high-speed deep tissue imaging.

Anisoplanatic adaptive optics in parallelized laser scanning microscopy

Inhomogeneities in the refractive index of a biological microscopy sample can introduce phase aberrations, severely impairing the quality of images. Adaptive optics can be employed to correct for phase aberrations and improve image quality. However, conventional adaptive optics can only correct a single phase aberration for the whole field of view (isoplanatic correction) while, due to the highly heterogeneous nature of biological tissues, the sample induced aberrations in microscopy often vary throughout the field of view (anisoplanatic aberration), limiting significantly the effectiveness of adaptive optics. This paper reports on a new approach for aberration correction in laser scanning confocal microscopy, in which a spatial light modulator is used to generate multiple excitation points in the sample to simultaneously scan different portions of the field of view with completely independent correction, achieving anisoplanatic compensation of sample induced aberrations, in a significantly shorter time compared to sequential isoplanatic correction of multiple image subregions. The method was tested in whole Drosophila brains and in larval Zebrafish, each showing a dramatic improvement in resolution and sharpness when compared to conventional isoplanatic adaptive optics.

Adaptive optics in the mouse eye: wavefront sensing based vs. image-guided aberration correction

Adaptive Optics (AO) is required to achieve diffraction limited resolution in many real-life imaging applications in biology and medicine. AO is essential to guarantee high fidelity visualization of cellular structures for retinal imaging by correcting ocular aberrations. Aberration correction for mouse retinal imaging by direct wavefront measurement has been demonstrated with great success. However, for mouse eyes, the performance of the wavefront sensor (WFS) based AO can be limited by several factors including non-common path errors, wavefront reconstruction errors, and an ill-defined reference plane. Image-based AO can avoid these issues at the cost of algorithmic execution time. Furthermore, image-based approaches can provide improvements to compactness, accessibility, and even the performance of AO systems. Here, we demonstrate the ability of image-based AO to provide comparable aberration correction and image resolution to the conventional Shack-Hartmann WFS-based AO approach. The residual wavefront error of the mouse eye was monitored during a wavefront sensorless optimization to allow comparison with classical AO. This also allowed us to improve the performance of our AO system for small animal retinal imaging.

Optimal model-based sensorless adaptive optics for epifluorescence microscopy

We report on a universal sample-independent sensorless adaptive optics method, based on modal optimization of the second moment of the fluorescence emission from a point-like excitation. Our method employs a sample-independent precalibration, performed only once for the particular system, to establish the direct relation between the image quality and the aberration. The method is potentially applicable to any form of microscopy with epifluorescence detection, including the practically important case of incoherent fluorescence emission from a three dimensional object, through minor hardware modifications. We have applied the technique successfully to a widefield epifluorescence microscope and to a multiaperture confocal microscope.