Wavefront measurement using computational adaptive optics

Wide Dynamic Range Digital Aberration Measurement and Fast Anterior-Segment OCT Imaging †

Ocular aberrometry with a wide dynamic range for assessing vision performance and anterior segment imaging that provides anatomical details of the eye are both essential for vision research and clinical applications. Defocus error is a major limitation of digital wavefront aberrometry (DWA), as the blurring of the detected point spread function (PSF) significantly reduces the signal-to-noise ratio (SNR) beyond the ±3 D range. With the aid of Badal-like precompensation of defocus, the dynamic defocus range of the captured aberrated PSFs can be effectively extended. We demonstrate a dual-modality MHz VCSEL-based swept-source OCT (SS-OCT) system with easy switching between DWA and OCT imaging modes. The system is capable of measuring aberrations with defocus dynamic range of 20 D as well as providing fast anatomical imaging of the anterior segment at an A-scan rate of 1.6 MHz.

Adaptive optics for optical microscopy [Invited]

Optical microscopy is widely used to visualize fine structures. When applied to bioimaging, its performance is often degraded by sample-induced aberrations. In recent years, adaptive optics (AO), originally developed to correct for atmosphere-associated aberrations, has been applied to a wide range of microscopy modalities, enabling high- or super-resolution imaging of biological structure and function in complex tissues. Here, we review classic and recently developed AO techniques and their applications in optical microscopy.

Computational refocusing of Jones matrix polarization-sensitive optical coherence tomography and investigation of defocus-induced polarization artifacts

Here we demonstrate a long-depth-of-focus imaging method using polarization sensitive optical coherence tomography (PS-OCT). This method involves a combination of Fresnel-diffraction-model-based phase sensitive computational refocusing and Jones-matrix based PS-OCT (JM-OCT). JM-OCT measures four complex OCT images corresponding to four polarization channels. These OCT images are computationally refocused as preserving the mutual phase consistency. This method is validated using a static phantom, postmortem zebrafish, and ex vivo porcine muscle samples. All the samples demonstrated successful computationally-refocused birefringence and degree-of-polarization-uniformity (DOPU) images. We found that defocusing induces polarization artifacts, i.e., incorrectly high birefringence values and low DOPU values, which are substantially mitigated by computational refocusing.

Application of Adaptive Optics in Ophthalmology

The eye, the photoreceptive organ used to perceive the external environment, is of great importance to humans. It has been proven that some diseases in humans are accompanied by fundus changes; therefore, the health status of people may be interpreted from retinal images. However, the human eye is not a perfect refractive system for the existence of ocular aberrations. These aberrations not only affect the ability of human visual discrimination and recognition, but restrict the observation of the fine structures of human eye and reduce the possibility of exploring the mechanisms of eye disease. Adaptive optics (AO) is a technique that corrects optical wavefront aberrations. Once integrated into ophthalmoscopes, AO enables retinal imaging at the cellular level. This paper illustrates the principle of AO in correcting wavefront aberrations in human eyes, and then reviews the applications and advances of AO in ophthalmology, including the adaptive optics fundus camera (AO-FC), the adaptive optics scanning laser ophthalmoscope (AO-SLO), the adaptive optics optical coherence tomography (AO-OCT), and their combined multimodal imaging technologies. The future development trend of AO in ophthalmology is also prospected.

Label-free metabolic and structural profiling of dynamic biological samples using multimodal optical microscopy with sensorless adaptive optics

Label-free optical microscopy has matured as a noninvasive tool for biological imaging; yet, it is criticized for its lack of specificity, slow acquisition and processing times, and weak and noisy optical signals that lead to inaccuracies in quantification. We introduce FOCALS (Fast Optical Coherence, Autofluorescence Lifetime imaging, and Second harmonic generation) microscopy capable of generating NAD(P)H fluorescence lifetime, second harmonic generation (SHG), and polarization-sensitive optical coherence microscopy (OCM) images simultaneously. Multimodal imaging generates quantitative metabolic and morphological profiles of biological samples in vitro, ex vivo, and in vivo. Fast analog detection of fluorescence lifetime and real-time processing on a graphical processing unit enables longitudinal imaging of biological dynamics. We detail the effect of optical aberrations on the accuracy of FLIM beyond the context of undistorting image features. To compensate for the sample-induced aberrations, we implemented a closed-loop single-shot sensorless adaptive optics solution, which uses computational adaptive optics of OCM for wavefront estimation within 2 s and improves the quality of quantitative fluorescence imaging in thick tissues. Multimodal imaging with complementary contrasts improves the specificity and enables multidimensional quantification of the optical signatures in vitro, ex vivo, and in vivo, fast acquisition and real-time processing improve imaging speed by 4-40 × while maintaining enough signal for quantitative nonlinear microscopy, and adaptive optics improves the overall versatility, which enable FOCALS microscopy to overcome the limits of traditional label-free imaging techniques.

Digital ocular swept source optical coherence aberrometry

Ocular aberrometry is an essential technique in vision science and ophthalmology. We demonstrate how a phase-sensitive single mode fiber-based swept source optical coherence tomography (SS-OCT) setup can be employed for quantitative ocular aberrometry with digital adaptive optics (DAO). The system records the volumetric point spread function at the retina in a de-scanning geometry using a guide star pencil beam. Succeeding test-retest repeatability assessment with defocus and astigmatism analysis on a model eye within ± 3 D dynamic range, the feasibility of technique is demonstrated in-vivo at a B-scan rate of >1 kHz in comparison with a commercially available aberrometer.

Wavefront sensor-less adaptive optics using deep reinforcement learning

Image degradation due to wavefront aberrations can be corrected with adaptive optics (AO). In a typical AO configuration, the aberrations are measured directly using a Shack-Hartmann wavefront sensor and corrected with a deformable mirror in order to attain diffraction limited performance for the main imaging system. Wavefront sensor-less adaptive optics (SAO) uses the image information directly to determine the aberrations and provide guidance for shaping the deformable mirror, often iteratively. In this report, we present a Deep Reinforcement Learning (DRL) approach for SAO correction using a custom-built fluorescence confocal scanning laser microscope. The experimental results demonstrate the improved performance of the DRL approach relative to a Zernike Mode Hill Climbing algorithm for SAO.

Closed-loop wavefront sensing and correction in the mouse brain with computed optical coherence microscopy

Optical coherence microscopy (OCM) uses interferometric detection to capture the complex optical field with high sensitivity, which enables computational wavefront retrieval using back-scattered light from the sample. Compared to a conventional wavefront sensor, aberration sensing with OCM via computational adaptive optics (CAO) leverages coherence and confocal gating to obtain signals from the focus with less cross-talk from other depths or transverse locations within the field-of-view. Here, we present an investigation of the performance of CAO-based aberration sensing in simulation, bead phantoms, and ex vivo mouse brain tissue. We demonstrate that, due to the influence of the double-pass confocal OCM imaging geometry on the shape of computed pupil functions, computational sensing of high-order aberrations can suffer from signal attenuation in certain spatial-frequency bands and shape similarity with lower order counterparts. However, by sensing and correcting only low-order aberrations (astigmatism, coma, and trefoil), we still successfully corrected tissue-induced aberrations, leading to 3× increase in OCM signal intensity at a depth of ∼0.9 mm in a freshly dissected ex vivo mouse brain.

Automated fast computational adaptive optics for optical coherence tomography based on a stochastic parallel gradient descent algorithm

The transverse resolution of optical coherence tomography is decreased by aberrations introduced from optical components and the tested samples. In this paper, an automated fast computational aberration correction method based on a stochastic parallel gradient descent (SPGD) algorithm is proposed for aberration-corrected imaging without adopting extra adaptive optics hardware components. A virtual phase filter constructed through combination of Zernike polynomials is adopted to eliminate the wavefront aberration, and their coefficients are stochastically estimated in parallel through the optimization of the image metrics. The feasibility of the proposed method is validated by a simulated resolution target image, in which the introduced aberration wavefront is estimated accurately and with fast convergence. The computation time for the aberration correction of a 512 × 512 pixel image from 7 terms to 12 terms requires little change, from 2.13 s to 2.35 s. The proposed method is then applied for samples with different scattering properties including a particle-based phantom, ex-vivo rabbit adipose tissue, and in-vivo human retina photoreceptors, respectively. Results indicate that diffraction-limited optical performance is recovered, and the maximum intensity increased nearly 3-fold for out-of-focus plane in particle-based tissue phantom. The SPGD algorithm shows great potential for aberration correction and improved run-time performance compared to our previous Resilient backpropagation (Rprop) algorithm when correcting for complex wavefront distortions. The fast computational aberration correction suggests that after further optimization our method can be integrated for future applications in real-time clinical imaging.

Computed optical coherence microscopy of mouse brain ex vivo

The compromise between lateral resolution and usable imaging depth range is a bottleneck for optical coherence tomography (OCT). Existing solutions for optical coherence microscopy (OCM) suffer from either large data size and long acquisition time or a nonideal point spread function. We present volumetric OCM of mouse brain ex vivo with a large depth coverage by leveraging computational adaptive optics (CAO) to significantly reduce the number of OCM volumes that need to be acquired with a Gaussian beam focused at different depths. We demonstrate volumetric reconstruction of ex-vivo mouse brain with lateral resolution of 2.2  μm, axial resolution of 4.7  μm, and depth range of ∼1.2  mm optical path length, using only 11 OCT data volumes acquired on a spectral-domain OCM system. Compared to focus scanning with step size equal to the Rayleigh length of the beam, this is a factor of 4 fewer datasets required for volumetric imaging. Coregistered two-photon microscopy confirmed that CAO-OCM reconstructions can visualize various tissue microstructures in the brain. Our results also highlight the limitations of CAO in highly scattering media, particularly when attempting to reconstruct far from the focal plane or when imaging deep within the sample.

Automated sensorless single-shot closed-loop adaptive optics microscopy with feedback from computational adaptive optics

Traditional wavefront-sensor-based adaptive optics (AO) techniques face numerous challenges that cause poor performance in scattering samples. Sensorless closed-loop AO techniques overcome these challenges by optimizing an image metric at different states of a deformable mirror (DM). This requires acquisition of a series of images continuously for optimization - an arduous task in dynamic in vivo samples. We present a technique where the different states of the DM are instead simulated using computational adaptive optics (CAO). The optimal wavefront is estimated by performing CAO on an initial volume to minimize an image metric, and then the pattern is translated to the DM. In this paper, we have demonstrated this technique on a spectral-domain optical coherence microscope for three applications: real-time depth-wise aberration correction, single-shot volumetric aberration correction, and extension of depth-of-focus. Our technique overcomes the disadvantages of sensor-based AO, reduces the number of image acquisitions compared to traditional sensorless AO, and retains the advantages of both computational and hardware-based AO.

Local wavefront mapping in tissue using computational adaptive optics OCT

The identification and correction of wavefront aberrations is often necessary to achieve high-resolution optical images of biological tissues, as imperfections in the optical system and the tissue itself distort the imaging beam. Measuring the localized wavefront aberration provides information on where the beam is distorted and how severely. We have recently developed a method to estimate the single-pass wavefront aberrations from complex optical coherence tomography (OCT) data. Using this method, localized wavefront measurement and correction using computational OCT was performed in ex vivo tissues. The computationally measured wavefront varied throughout the imaged OCT volumes and, therefore, a local wavefront correction outperformed a global wavefront correction. The local wavefront measurement was also used to generate tissue aberration maps. Such aberration maps could potentially be used as a new form of tissue contrast.

Aberration-diverse optical coherence tomography for suppression of multiple scattering and speckle

Multiple scattering is a major barrier that limits the optical imaging depth in scattering media. In order to alleviate this effect, we demonstrate aberration-diverse optical coherence tomography (AD-OCT), which exploits the phase correlation between the deterministic signals from single-scattered photons to suppress the random background caused by multiple scattering and speckle. AD-OCT illuminates the sample volume with diverse aberrated point spread functions, and computationally removes these intentionally applied aberrations. After accumulating 12 astigmatism-diverse OCT volumes, we show a 10 dB enhancement in signal-to-background ratio via a coherent average of reconstructed signals from a USAF target located 7.2 scattering mean free paths below a thick scattering layer, and a 3× speckle contrast reduction from an incoherent average of reconstructed signals inside the scattering layer. This AD-OCT method, when implemented using astigmatic illumination, is a promising approach for ultra-deep volumetric optical coherence microscopy.