TBD

Imaging through highly diffusive media is challenging because of the extensive spreading of light propagation in both time and space. The most advanced technique utilizes an expensive time-of-flight imaging system. Here, we present a simple and efficient approach for computational diffuse optical tomography. A typical CMOS camera captures the transmission light through an object buried between two thick diffusive media. Multiple illumination points provide more information, allowing reconstruction of the hidden object at a higher quality than computational time-of-flight diffuse optical tomography. The demonstration shows a low-cost diffuse optical tomography with high accuracy and low computational complexity.

Non-invasive imaging with high resolution deep within biological materials without the use of harmful ionizing radiation is of great interest in the field of medical imaging. Second- and third- harmonic generation are excellent mechanisms to circumvent this issue by providing outstanding contrast and optical sectioning [1]. In general, these signals are weak and prone to scattering which introduce great challenges when imaging deep within turbid media. We will discuss recently demonstrated nonlinear distortion, which can detect very weak backscattered SHG optical fields in a widefield holography configuration, from which distortion from aberrations and scattering can be computationally estimated and corrected. This approach uses field phase information to allow diffraction limited imaging within deep tissue.

Wavefront shaping attempts to image deep inside scattering tissue by modulating the incoming and/or outgoing wavefronts. Previously such modulations were estimated using non-linear two photon fluorescent feedback. Alternatively, to use a simpler linear fluorescent feedback, strong fluorescent beads are manually added to the tissue. However, the fluorescent components of a tissue are order-of-magnitude weaker than such beads, and the feedback signal required for previous algorithms cannot be detected. We suggest a new, noise robust approach, which works with a confocal modulation of both the illumination and imaging arms. We successfully use it to image EGFP labeled neurons through scattering tissue.

We introduce a phase conjugation method that utilizes multiple incoherent guidestars to control light in complex media. The technique involves the characterization of mutually incoherent scattered fields, followed by their time-reversal. With this approach, we achieve precise light focusing on individual and multiple guidestars, as well as efficient energy delivery to an extended target through scattering media. This method has various potential applications, including optical manipulation, targeted stimulation and deep optical imaging.

Perfect imaging is one of the ultimate goals for humankind in perceiving the world, yet it is fundamentally limited by the optical aberrations resulting from imperfect imaging systems or dynamic imaging environments. To address this long-standing problem, we develop a new framework of digital adaptive optics for universal incoherent imaging applications based on scanning light-field imaging systems. With digital measurement and synthesis of the incoherent light field with unprecedented precision, we have demonstrated a series of killer applications that are hard for traditional methods, including long-term high-speed intravital 3D imaging in mammals, gigapixel imaging with a single lens, high-speed multi-site aberration corrections for ground-based telescopes against turbulence, and real-time megapixel depth sensing. We anticipate that digital adaptive optics may facilitate broad applications in almost all fields, including industrial inspection, mobile devices, autonomous driving, surveillance, medical diagnosis, biology, and astronomy.

This talk describes our recently-developed guidestar-free approach to imaging through scattering and other optical aberrations; neural wavefront shaping (NeuWS). NeuWS integrates maximum likelihood estimation, measurement modulation, and neural signal representations to reconstruct diffraction-limited images through strong static and dynamic scattering media without guidestars, sparse targets, controlled illumination, nor specialized image sensors. We experimentally demonstrate guidestar-free, wide field-of-view, high-resolution, diffraction-limited imaging of extended, nonsparse, and static/dynamic scenes captured through static/dynamic aberrations.

Measurement and correction of optical aberrations in optical microscopy can be achieved through either hardware or computation. I will describe several recent projects from my laboratory where hardware including Shack-Hartmann wavefront sensors and segmented deformable mirrors, as well as a computational approach based on machine learning were used for aberration measurement and correction. These approaches were combined with several imaging modalities including widefield, confocal, and two-photon fluorescence microscopy for high-resolution imaging of in vivo structures.

Optical-resolution fluorescence imaging in complex samples is challenging due to random light scattering, with significant implications across multiple fields. Here, we adapt computational reflection-matrix techniques developed for scattering compensation in phase-sensitive coherent imaging, to incoherent fluorescence imaging that solely relies on intensity detection. Moreover, we numerically and experimentally demonstrate that the adoption of random illuminations can substantially decrease the number of measurements necessary for effective reflection-matrix solutions.

Wavefront-sensorless adaptive optics (AO) is commonly used to enable aberration estimation and correction using the information in images. We have introduced a machine learning (ML) approach that embeds physical understanding of the imaging process into a sensorless AO method. This enabled correction of aberrations with as few as two sample exposures across different microscope modalities. We extend the capabilities of such systems to more challenging imaging applications, including larger and more complex aberrations, lower signal levels, and specimen variations. We present a concept that permits estimation of multiple aberrations modes from a single image.

Applying super-resolution imaging techniques to recover object behind scattering media can obtain more information. Our previous work stochastic optical scattering localization imaging breaks the diffraction-limit via object blinking. Here, we proposed a more practical method using speckle fluctuation to achieve super-resolution imaging. The speckle fluctuation in the illumination part cause object fluctuating, resulting in a series of speckle fluctuation frames in the camera. By analyzing the high order cumulants of deconvolution frames, not only the noise artifacts are suppressed but also resolution enhanced by a factor of square root of N , where N is the cumulant order.

A powerful aberration correction toolbox for intensity error correction is presented enabling restoration of the beam uniformity and the beam shape. The proposed method, referred to as intensity adaptive optics (I-AO), features the design of a dual-loop feedback control system that can function in both a sensor-based and sensorless mode. The feasibility of the approach is validated with quantitative analysis of the focal quality for an aberrated system, using both compensation methods, and paves the way for a new avenue for AO technology. These findings will benefit a wide range of applications spanning from aerospace to microscopy.

Diattenuation aberration is considered as an important element of polarization-related aberrations in various optical systems. It can disorder both the state of polarization and the intensity of a beam, and thus negatively impact the optical resolution and the correctness of the vectorial information of the optical system. Polarization adaptive optics (P-AO) has been proposed recently and serves as a novel tool to conduct polarization error corrections. However, previous cases typically focus on retardance-related aberrations, with little treatment of aberrations related to diattenuation. In this presentation, we harness the topological number of a skyrmionic beam as a criterion to discuss the boundary of the correction ability of P-AO method towards diattenuation aberration.

Microscopes face challenges due to inherent aberrations caused by various sources, with the sample itself presenting a significant obstacle. To overcome this, adaptive optics (AO) techniques have been developed, including sensor-based and sensorless approaches. Our innovative method leverages multi-conjugated AO, correcting aberrations over an extended field of view. Using deformable lenses from Dynamic Optics, we achieve efficient correction up to 4th order Zernike aberrations. Combining transmissive AO elements with the sensorless method, our compact design requires minimal modifications to existing microscopes. Implementing and testing the setup, we achieve remarkable resolution (1.5 um) and correction over a 1000 um field of view. This advancement opens new possibilities for high-quality imaging in various research fields.

Light-based methods are fundamental in biomedical and life sciences as non-invasive diagnostic and treatment tools. However, the scattering nature of biological tissue limits the maximum depth at which they can operate – typically, below one millimeter. Here, we show how ultrasound waves inside a resonant cavity can locally modulate the optical properties of a turbid medium. In agreement with Monte Carlo simulations, our experimental results demonstrate, at an optical density of 15, an enhancement in light confinement up to a factor of 7 compared to conventional methods.

Spatial and temporal speckle statistics are useful for numerous imaging applications, but remain underutilized due to the difficulty in simulating and analyzing them. To tackle this challenge, we introduce a new Monte-Carlo algorithm that can efficiently simulate complex-valued, physically-correct speckles. We demonstrate that our speckles follow the exact same statistics of speckles produced by exact wave solvers, and agree with previous analytic formulas addressing partial settings of the problem. We demonstrate the potential usage of the simulator in several imaging applications.

Advances in brain–machine interfaces (BMIs) have been driven by a proliferation of neural sensing and stimulating modalities, as well as an increase in the number of neurons that can be simultaneously recorded or stimulated. These advances have led to new insights into neural systems and the development of novel clinical tools. Ideally, a BMI should be minimally invasive, extremely safe and offer sufficient longevity. It should have a feedback system to close the communication loop and have high spatiotemporal resolution and throughput. Imaging and stimulating neurons optically, rather than electrically, holds tremendous promise due to the cellular selectivity and high spatial and temporal resolutions of the technique. Computer-Generated Holography (CGH) using Spatial Light Modulators (SLMs) can sculpt light to address ensembles of neurons simultaneously, however available SLM speeds constrain the bandwidth and throughput of such interfaces. Additionally, high CGH compute times limit the ability to provide the real-time computations required to close the loop. We propose a high-speed Microelectromechanical Systems (MEMS) based SLMs capable of switching at kilohertz speeds coupled with a high-speed CGH algorithm that can open the door to closed-loop all-optical neural interfaces with high spatial and temporal precision.

The main hindrance to optical imaging at elevated depths is the scattering of light exhibited by biological tissues. Consequently, various wavefront shaping techniques have been developed in order to achieve focusing in scattering media. In our scattering compensation experiments, the spatial light modulator is replaced by a novel integrated photonics-based wavefront shaper. We work on focusing through a static scatterer using near-infrared light. The photonic integrated circuit (PIC) used in this research consists of a 1D array of optical emitters with independently controlled phases. This PIC-based wavefront shaper was fabricated on a CMOS-compatible platform offering the prospect of large-scale fabrication.

Wavefront sensing is often the loop speed limiting factor in adaptive optics (AO) implementations. Currently available wavefront sensos rely on the use of high-speed cameras with small temporal resolution, but they often stream data to a buffer limiting the speed of feedback control loops. Neuromorphic cameras respond to changes in intensity, streaming only dynamic information from the scene in an Address-Event Representation format. In this work, we demonstrate the estimation of wavefront slopes utilizing a neuromorphic camera in a Shack-Hartman wavefront sensor configuration integrated in a simple but fast AO control loop.

Phase-only spatial light modulators (SLMs) are extensively utilized for controlling the phase of light in diverse applications. However, liquid-crystal-on-silicon (LCOS) SLMs exhibit undesired spatial variations in both phase response and optical flatness across the SLM panel, which necessitates calibration for achieving accurate phase control. Here, we propose a rapid and straightforward calibration approach to address these non-uniformities at the single-pixel level. Our method leverages Twyman-Green interferometry without relying on a piezoelectric transducer, significantly reducing the measurement time to approximately 4.5 seconds by collecting only 18 interferograms of SLM patterns with constant gray levels. This remarkable speed ensures minimal vulnerability to environmental disturbances during interferometry. We provide a comprehensive description of the calibration procedure, evaluate the performance of the calibrated local pixel response, and validate the flatness calibration using SLM-based phase shift interferometry.

The human eye has aberrations that degrade the quality of vision. Adaptive Optics visual simulators allow closed-loop correction of the eye’s wave aberrations to produce diffraction-limited retinal image quality, or to manipulate the optics of the eye to probe the spatial limits of vision and neural adaptation. On the other hand, the wave aberrations can be controlled to expand depth-of-focus or provide multiple foci in eyes that have lost the ability to accommodate (presbyopia) and more recently to slow down myopia progression. We will present different wavefront control strategies (deformable mirrors, spatial light modulators and opto-tunable lenses) in visual simulators, and measured effects of correction and induction of wave aberrations and multifocal phase maps on visual function and perception.

We report a fast, easy-to-use adaptive optics (AO) method and its implementation in both Light-Sheet and Two-Photon fluorescence microscopy setups. We demonstrate fast (typically 1 second), and accurate aberrations correction at large depths (hundreds of microns) mostly in brain tissue of animal models such as Drosophila, Zebra Fish and mouse. We quantifiy the gain brought by AO in terms of signal (up to x5), contrast, achievable imaging depth and segmentation capability of neuronal structures for both imaging modalities. The approach paves the way to future automated AO-based 3D microscopy systems.

Deep brain imaging at cellular resolution is challenging due to strong and dynamic tissue scattering. Previous techniques for scattering correction are either slow or not in reflection mode, hindering them from imaging deep in the mouse brain in vivo. Here, we have developed a new two-photon microscope with ultrafast scattering correction for deep brain imaging. We use a compressive sensing algorithm to calculate correction masks from much fewer measurements than previous methods and couple light into high-transmission channels of scattering tissue using a digital micromirror device. We demonstrate real-time correction of dynamic scattering by focusing through various dynamic scattering samples.

We recently proposed a new wavefront shaping concept, coined as Smartlens, in which the phase of the transmitted light is shaped by engineering the temperature landscape in a thermo-optical material. Individually or in arrays, these microscale devices can generate complex functions based on either pure, or a combination of, Zernike polynomials, including lenses or electrically-tuneable aberration correctors. We will see how this concept could complement the existing optical shaping toolbox by offering low-chromatic-aberration, polarization-insensitive and transmission-mode micro-components. I will then delve into the potential of a single reconfigurable Smartlens to embed adaptive optics within a fluorescence endoscope. Finally, I will show that a Smartlens Array can enable multiplane Ca2+ or voltage imaging in Zebrafish at KHz frame rates.

Fiber bundles are used in endoscopy for pixelated image transfer. Due to scattering of the effective refractive index, the phase information is lost, however. Digital optical phase conjugation has been used to reverse this effect partially, which enables endoscopes without distal optics and diffraction-limited 3D capability. However, imaging is limited to a single wavelength. We demonstrate multispectral and broadband imaging using spatial light modulators with a phase shift exceeding 2pi. Imaging can be achieved by correcting the sending, receiving or both beam paths, enabling single shot-RGB or confocal fluorescence imaging.

We present a diffuser-based computational X-ray coherent imaging method using a speckle-correlation scattering matrix (SSM), which is based on the spatial pseudorandomness of generated speckle patterns. An X-ray diffuser was introduced to ensure the generation of pseudorandom speckle patterns on the detector. Using the SSM method, we achieved 13.9 nm image resolution, which surpasses the feature size of the diffuser (300 nm). We also apply our method to the shot-by-shot pulse characterization of an X-ray free-electron laser; and analyze the statistical properties of each pulse in intensity, position, angle, and shape.