Adaptive optics for structured illumination microscopy

Selective-plane-activation structured illumination microscopy

The background light from out-of-focus planes hinders resolution enhancement in structured illumination microscopy when observing volumetric samples. Here we used selective plane illumination and reversibly photoswitchable fluorescent proteins to realize structured illumination within the focal plane and eliminate the out-of-focus background. Theoretical investigation of the imaging properties and experimental demonstrations show that selective plane activation is beneficial for imaging dense microstructures in cells and cell spheroids.

Phasing segmented telescopes via deep learning methods: application to a deployable CubeSat

Capturing high-resolution imagery of the Earth's surface often calls for a telescope of considerable size, even from low Earth orbits (LEOs). A large aperture often requires large and expensive platforms. For instance, achieving a resolution of 1 m at visible wavelengths from LEO typically requires an aperture diameter of at least 30 cm. Additionally, ensuring high revisit times often prompts the use of multiple satellites. In light of these challenges, a small, segmented, deployable CubeSat telescope was recently proposed creating the additional need of phasing the telescope's mirrors. Phasing methods on compact platforms are constrained by the limited volume and power available, excluding solutions that rely on dedicated hardware or demand substantial computational resources. Neural networks (NNs) are known for their computationally efficient inference and reduced onboard requirements. Therefore, we developed a NN-based method to measure co-phasing errors inherent to a deployable telescope. The proposed technique demonstrates its ability to detect phasing errors at the targeted performance level [typically a wavefront error (WFE) below 15 nm RMS for a visible imager operating at the diffraction limit] using a point source. The robustness of the NN method is verified in presence of high-order aberrations or noise and the results are compared against existing state-of-the-art techniques. The developed NN model ensures its feasibility and provides a realistic pathway towards achieving diffraction-limited images.

Reference-free in situ rapid regional calibration of phase-only spatial light modulators

Spatial light modulators (SLMs) have become an indispensable element in modern optics for their versatile performance in many applications. Among various types of SLMs, such as digital micromirror devices (DMD), liquid crystal-based phase-only spatial light modulators (LC-SLMs), and deformable mirrors (DM), LC-SLMs are often the method of choice due to their high efficiency, precise phase modulation, and abundant number of effective pixels. In general, for research grade applications, an additional SLM calibration step is required due to fabrication imperfection resulting in non-flat liquid crystal panels and varying phase responses over the SLM area. Here, we demonstrate a straightforward approach for reference-free orthogonal calibration of an arbitrary number of SLM subregions which only requires the same measurement time as global calibration. The proposed method requires minimal optical elements and can be applied to any optical setup as is. As a benchmark performance test, we achieved a 2.2-fold enhancement in correction efficiency for wavefront shaping through scattering media utilizing the calibrated 2160 subregions of the SLM, in comparison with a single global look-up table (LUT).

Tandem aberration correction optics (TACO) in wide-field structured illumination microscopy

Structured illumination microscopy (SIM) is a powerful super-resolution imaging technique that uses patterned illumination to down-modulate high spatial-frequency information of samples. However, the presence of spatially-dependent aberrations can severely disrupt the illumination pattern, limiting the quality of SIM imaging. Conventional adaptive optics (AO) techniques that employ wavefront correctors at the pupil plane are not capable of effectively correcting these spatially-dependent aberrations. We introduce the Tandem Aberration Correction Optics (TACO) approach that combines both pupil AO and conjugate AO for aberration correction in SIM. TACO incorporates a deformable mirror (DM) for pupil AO in the detection path to correct for global aberrations, while a spatial light modulator (SLM) is placed at the plane conjugate to the aberration source near the sample plane, termed conjugate AO, to compensate spatially-varying aberrations in the illumination path. Our numerical simulations and experimental results show that the TACO approach can recover the illumination pattern close to an ideal condition, even when severely misshaped by aberrations, resulting in high-quality super-resolution SIM reconstruction. The TACO approach resolves a critical traditional shortcoming of aberration correction for structured illumination. This advance significantly expands the application of SIM imaging in the study of complex, particularly biological, samples and should be effective in other wide-field microscopies.

Deep learning-driven adaptive optics for single-molecule localization microscopy

The inhomogeneous refractive indices of biological tissues blur and distort single-molecule emission patterns generating image artifacts and decreasing the achievable resolution of single-molecule localization microscopy (SMLM). Conventional sensorless adaptive optics methods rely on iterative mirror changes and image-quality metrics. However, these metrics result in inconsistent metric responses and thus fundamentally limit their efficacy for aberration correction in tissues. To bypass iterative trial-then-evaluate processes, we developed deep learning-driven adaptive optics for SMLM to allow direct inference of wavefront distortion and near real-time compensation. Our trained deep neural network monitors the individual emission patterns from single-molecule experiments, infers their shared wavefront distortion, feeds the estimates through a dynamic filter and drives a deformable mirror to compensate sample-induced aberrations. We demonstrated that our method simultaneously estimates and compensates 28 wavefront deformation shapes and improves the resolution and fidelity of three-dimensional SMLM through >130-µm-thick brain tissue specimens.

Local aberration control to improve efficiency in multiphoton holographic projections

Optical aberrations affect the quality of light propagating through a turbid medium, where refractive index is spatially inhomogeneous. In multiphoton optical applications, such as two-photon excitation fluorescence imaging and optogenetics, aberrations non-linearly impair the efficiency of excitation. We demonstrate a sensorless adaptive optics technique to compensate aberrations in holograms projected into turbid media. We use a spatial light modulator to project custom three dimensional holographic patterns and to correct for local (anisoplanatic) distortions. The method is tested on both synthetic and biological samples to counteract aberrations arising respectively from misalignment of the optical system and from samples inhomogeneities. In both cases the anisoplanatic correction improves the intensity of the stimulation pattern at least two-fold.

Super-resolution microscopy: a brief history and new avenues

Super-resolution microscopy (SRM) is a fast-developing field that encompasses fluorescence imaging techniques with the capability to resolve objects below the classical diffraction limit of optical resolution. Acknowledged with the Nobel prize in 2014, numerous SRM methods have meanwhile evolved and are being widely applied in biomedical research, all with specific strengths and shortcomings. While some techniques are capable of nanometre-scale molecular resolution, others are geared towards volumetric three-dimensional multi-colour or fast live-cell imaging. In this editorial review, we pick on the latest trends in the field. We start with a brief historical overview of both conceptual and commercial developments. Next, we highlight important parameters for imaging successfully with a particular super-resolution modality. Finally, we discuss the importance of reproducibility and quality control and the significance of open-source tools in microscopy. This article is part of the Theo Murphy meeting issue 'Super-resolution structured illumination microscopy (part 2)'.

Self-calibrated general model-based wavefront sensorless adaptive optics for both point-like and extended objects

The deformable mirror (DM) in conventional model-based wavefront sensorless adaptive optics (WFSless AO) must be calibrated in advance by an additional WFS in order to precisely generate predetermined bias modes with known amplitudes. Although the WFS is unnecessary during correction, it will increase system complexity and may be unavailable in real applications. In this paper, the model-based WFSless AO algorithms, either for point-like or extended objects, are generalized to a unified form and the calibration problem comes down to the measurement of a Gram matrix. We proposed a novel self-calibration procedure to obtain the Gram matrix without using a WFS. The calibrated Gram matrix can be used directly for simultaneous correction if using the influence functions of DM as the bias modes, requiring N+1 images to correct N modes. Alternatively, orthogonal or gradient-orthogonal mirror modes obtained from the eigenvectors of the Gram matrix can be used as the modal basis to implement independent sequential correction that requires 2N images to correct N modes. Simulations and experiments have been done to verify the feasibility of proposed self-calibration and correction methods for both point-like and extended objects in a WFSless AO system.

Adaptive optics in super-resolution microscopy

Fluorescence microscopy has become a routine tool in biology for interrogating life activities with minimal perturbation. While the resolution of fluorescence microscopy is in theory governed only by the diffraction of light, the resolution obtainable in practice is also constrained by the presence of optical aberrations. The past two decades have witnessed the advent of super-resolution microscopy that overcomes the diffraction barrier, enabling numerous biological investigations at the nanoscale. Adaptive optics, a technique borrowed from astronomical imaging, has been applied to correct for optical aberrations in essentially every microscopy modality, especially in super-resolution microscopy in the last decade, to restore optimal image quality and resolution. In this review, we briefly introduce the fundamental concepts of adaptive optics and the operating principles of the major super-resolution imaging techniques. We highlight some recent implementations and advances in adaptive optics for active and dynamic aberration correction in super-resolution microscopy.

Super-resolution structured illumination microscopy: past, present and future

Structured illumination microscopy (SIM) has emerged as an essential technique for three-dimensional (3D) and live-cell super-resolution imaging. However, to date, there has not been a dedicated workshop or journal issue covering the various aspects of SIM, from bespoke hardware and software development and the use of commercial instruments to biological applications. This special issue aims to recap recent developments as well as outline future trends. In addition to SIM, we cover related topics such as complementary super-resolution microscopy techniques, computational imaging, visualization and image processing methods. This article is part of the Theo Murphy meeting issue 'Super-resolution structured illumination microscopy (part 1)'.

Structured illumination microscopy artefacts caused by illumination scattering

Despite its wide application in live-cell super-resolution (SR) imaging, structured illumination microscopy (SIM) suffers from aberrations caused by various sources. Although artefacts generated from inaccurate reconstruction parameter estimation and noise amplification can be minimized, aberrations due to the scattering of excitation light on samples have rarely been investigated. In this paper, by simulating multiple subcellular structure with the distinct refractive index from water, we study how different thicknesses of this subcellular structure scatter incident light on its optical path of SIM excitation. Because aberrant interference light aggravates with the increase in sample thickness, the reconstruction of the 2D-SIM SR image degraded with the change of focus along the axial axis. Therefore, this work may guide the future development of algorithms to suppress SIM artefacts caused by scattering in thick samples. This article is part of the Theo Murphy meeting issue 'Super-resolution structured illumination microscopy (part 1)'.

Subcellular three-dimensional imaging deep through multicellular thick samples by structured illumination microscopy and adaptive optics

Structured Illumination Microscopy enables live imaging with sub-diffraction resolution. Unfortunately, optical aberrations can lead to loss of resolution and artifacts in Structured Illumination Microscopy rendering the technique unusable in samples thicker than a single cell. Here we report on the combination of Adaptive Optics and Structured Illumination Microscopy enabling imaging with 150 nm lateral and 570 nm axial resolution at a depth of 80 µm through Caenorhabditis elegans. We demonstrate that Adaptive Optics improves the three-dimensional resolution, especially along the axial direction, and reduces artifacts, successfully realizing 3D-Structured Illumination Microscopy in a variety of biological samples.

Three-dimensional broadband light beam manipulation in forward scattering samples

Focusing light into highly disordered biological tissue is a major challenge in optical microscopy and biomedical imaging due to scattering. However, correlations in the scattering matrix, known as "memory effects", can be used to improve imaging capabilities. Here we discuss theoretically and numerically the possibility to achieve three-dimensional ultrashort laser focusing and scanning inside forward scattering media, beyond the scattering mean free path, by simultaneously taking advantage of the angular and the chromato-axial memory effects. The numerical model is presented in details, is validated within the state of the art theoretical and experimental framework and is finally used to propose a scheme for focusing ultra-short laser pulses in depth through forward scattering media.

Optimal, blind-search modal wavefront correction in atmospheric turbulence. Part I: simulations

Modal control is an established tool in adaptive optics. It allows not only for the reduction in the controllable degrees of freedom, but also for filtering out unseen modes and optimizing gain on a mode-by-mode basis. When Zernike polynomials are employed as the modal basis for correcting atmospheric turbulence, their cross-correlations translate to correction errors. We propose optimal modal decomposition for gradient-descent-based wavefront sensorless adaptive optics, which is free of this problem. We adopt statistically independent Karhunen-Loève functions for iterative blind correction and analyze performance of the algorithm in static as well as in dynamic simulated turbulence conditions.

To be more precise: the role of intracellular trafficking in development and pattern formation

Living cells interpret a variety of signals in different contexts to elucidate functional responses. While the understanding of signalling molecules, their respective receptors and response at the gene transcription level have been relatively well-explored, how exactly does a single cell interpret a plethora of time-varying signals? Furthermore, how their subsequent responses at the single cell level manifest in the larger context of a developing tissue is unknown. At the same time, the biophysics and chemistry of how receptors are trafficked through the complex dynamic transport network between the plasma membrane-endosome-lysosome-Golgi-endoplasmic reticulum are much more well-studied. How the intracellular organisation of the cell and inter-organellar contacts aid in orchestrating trafficking, as well as signal interpretation and modulation by the cells are beginning to be uncovered. In this review, we highlight the significant developments that have strived to integrate endosomal trafficking, signal interpretation in the context of developmental biology and relevant open questions with a few chosen examples. Furthermore, we will discuss the imaging technologies that have been developed in the recent past that have the potential to tremendously accelerate knowledge gain in this direction while shedding light on some of the many challenges.

Microscope-AOtools: a generalised adaptive optics implementation

Aberrations arising from sources such as sample heterogeneity and refractive index mismatches are constant problems in biological imaging. These aberrations reduce image quality and the achievable depth of imaging, particularly in super-resolution microscopy techniques. Adaptive optics (AO) technology has been proven to be effective in correcting for these aberrations, thereby improving the image quality. However, it has not been widely adopted by the biological imaging community due, in part, to difficulty in set-up and operation of AO. The methods for doing so are not novel or unknown, but new users often waste time and effort reimplementing existing methods for their specific set-ups, hardware, sample types, etc. Microscope-AOtools offers a robust, easy-to-use implementation of the essential methods for set-up and use of AO elements and techniques. These methods are constructed in a generalised manner that can utilise a range of adaptive optics elements, wavefront sensing techniques and sensorless AO correction methods. Furthermore, the methods are designed to be easily extensible as new techniques arise, leading to a streamlined pipeline for new AO technology and techniques to be adopted by the wider microscopy community.

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.

Fast widefield imaging of neuronal structure and function with optical sectioning in vivo

Optical microscopy, owing to its noninvasiveness and subcellular resolution, enables in vivo visualization of neuronal structure and function in the physiological context. Optical-sectioning structured illumination microscopy (OS-SIM) is a widefield fluorescence imaging technique that uses structured illumination patterns to encode in-focus structures and optically sections 3D samples. However, its application to in vivo imaging has been limited. In this study, we optimized OS-SIM for in vivo neural imaging. We modified OS-SIM reconstruction algorithms to improve signal-to-noise ratio and correct motion-induced artifacts in live samples. Incorporating an adaptive optics (AO) module to OS-SIM, we found that correcting sample-induced optical aberrations was essential for achieving accurate structural and functional characterizations in vivo. With AO OS-SIM, we demonstrated fast, high-resolution in vivo imaging with optical sectioning for structural imaging of mouse cortical neurons and zebrafish larval motor neurons, and functional imaging of quantal synaptic transmission at Drosophila larval neuromuscular junctions.

Extended field-of-view adaptive optics in microscopy via numerical field segmentation

Sample-induced optical aberrations in microscopy are, in general, field dependent, limiting their correction via pupil adaptive optics (AO) to the center of the available field-of-view (FoV). This is a major hindrance, particularly for deep tissue imaging, where AO has a significant impact. We present a new wide-field AO microscopy scheme, in which the deformable element is located at the pupil plane of the objective. To maintain high-quality correction across its entirety, the FoV is partitioned into small segments, and a separate aberration estimation is performed for each via a modal-decomposition-based indirect wavefront sensing algorithm. A final full-field image is synthesized by stitching of the partitions corrected consecutively and independently via their respective measured aberrations. The performance and limitations of the method are experimentally explored on synthetic samples imaged via a custom-developed AO fluorescence microscope featuring an optofluidic refractive wavefront modulator.

Four-dimensional visualization of zebrafish cardiovascular and vessel dynamics by a structured illumination microscope with electrically tunable lens

We established a four-dimensional (4D) microscopy method using structured illumination for optical axial imaging with an electrically tunable lens. With its fast imaging capability, the dynamics of the cardiovascular system of the zebrafish and cerebral vessels were imaged based on the coverage of two stacks (25 layers) per second with lateral /axial resolutions of 0.6 µm and 1.8 µm, respectively. Time lapse imaging clearly shows the contractile-relaxation response of the beating heart at different cardiac phases and with different mobilities of blood vessels in different regions. This new 4D technique will facilitate in vivo imaging of organ function, generation, as well as drug responses in small-sized animals.

Adaptive wavefront correction structured illumination holographic tomography

In this study, a novel adaptive wavefront correction (AWC) technique is implemented on a compactly developed structured illumination holographic tomography (SI-HT) system. We propose a mechanical movement-free compact scanning architecture for SI-HT systems with AWC, implemented by designing and displaying a series of computer-generated holograms (CGH) composed of blazed grating with phase Fresnel lens on a phase-only spatial light modulator (SLM). In the proposed SI-HT, the aberrations of the optical system are sensed by digital holography and are used to design the CGH-based AWC to compensate the phase aberrations of the tomographic imaging system. The proposed method was validated using a standard Siemens star target, its potential application was demonstrated using a live candida rugosa sample, and its label-free three-dimensional refractive index profile was generated at its subcellular level. The experimental results obtained reveal the ability of the proposed method to enhance the imaging performance in both lateral and axial directions.

Accurate aberration correction in confocal microscopy based on modal sensorless method

Confocal microscopy has the advantages of high resolution and optical sectioning ability over conventional microscopy. However, aberration induced by the optical system can compromise these advantages and considerably reduce the energy reaching the pointlike detector. We propose an accurate aberration correction method with a liquid-crystal spatial light modulator (LCSLM) in the confocal system. Each coefficient of Zernike aberration modes is calculated by directly measuring the variance of the images with different bias aberration modes. Large-coefficient (>0.7 rad) aberration is compensated first by LCSLM, following which aberrations with small coefficients are measured precisely, minimizing the cross talk between different kinds of aberrations. With this predistortion strategy, the aberration correction is much more accurate, and maximum image intensity in the normal and nonconjugated systems is improved by 2.5 times and 4 times compared to the normal correction method, respectively, demonstrating the effectiveness of our method.

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.

Optical transfer function engineering for a tunable 3D structured illumination microscope

Two important features of three-dimensional structured illumination microscopy (3D-SIM) are its optical sectioning (OS) and super-resolution (SR) capabilities. Previous works on 3D-SIM systems show that these features are coupled. We demonstrate that a 3D-SIM system using a Fresnel biprism illuminated by multiple linear incoherent sources provides a structured illumination pattern whose lateral and axial modulation frequencies can be tuned separately. Therefore, the compact support of the synthetic optical transfer function (OTF) can be engineered to achieve the highest OS and SR capabilities for a particular imaging application. Theoretical performance of our engineered system based on the OTF support is compared to that achieved by other well-known SIM systems.

IsoSense: frequency enhanced sensorless adaptive optics through structured illumination

We present IsoSense, a wavefront sensing method that mitigates sample dependency in image-based sensorless adaptive optics applications in microscopy. Our method employs structured illumination to create additional high spatial frequencies in the image through custom illumination patterns. This improves the reliability of image quality metric calculations and enables sensorless wavefront measurement even in samples with sparse spatial frequency content. We demonstrate the feasibility of IsoSense for aberration correction in a deformable-mirror-based structured illumination super-resolution fluorescence microscope.

Adaptive optics microspectrometer for cross-correlation measurement of microfluidic flows

Mapping flows in vivo is essential for the investigation of cardiovascular pathologies in animal models. The limitation of optical-based methods, such as space-time cross correlation, is the scattering of light by the connective and fat components and the direct wave front distortion by large inhomogeneities in the tissue. Nonlinear excitation of the sample fluorescence helps us by reducing light scattering in excitation. However, there is still a limitation on the signal-background due to the wave front distortion. We develop a diffractive optical microscope based on a single spatial light modulator (SLM) with no movable parts. We combine the correction of wave front distortions to the cross-correlation analysis of the flow dynamics. We use the SLM to shine arbitrary patterns of spots on the sample, to correct their optical aberrations, to shift the aberration corrected spot array on the sample for the collection of fluorescence images, and to measure flow velocities from the cross-correlation functions computed between couples of spots. The setup and the algorithms are tested on various microfluidic devices. By applying the adaptive optics correction algorithm, it is possible to increase up to 5 times the signal-to-background ratio and to reduce approximately of the same ratio the uncertainty of the flow speed measurement. By working on grids of spots, we can correct different aberrations in different portions of the field of view, a feature that allows for anisoplanatic aberrations correction. Finally, being more efficient in the excitation, we increase the accuracy of the speed measurement by employing a larger number of spots in the grid despite the fact that the two-photon excitation efficiency scales as the fourth power of this number: we achieve a twofold decrease of the uncertainty and a threefold increase of the accuracy in the evaluation of the flow speed.

Structured illumination approaches for super-resolution in plant cells

The advent of super-resolution techniques in biological microscopy has opened new frontiers for exploring the molecular distribution of proteins and small molecules in cells. Improvements in optical design and innovations in the approaches for the collection of fluorescence emission have produced substantial gains in signal from chemical labels and fluorescent proteins. Structuring the illumination to elicit fluorescence from specific or even random patterns allows the extraction of higher order spatial frequencies from specimens labeled with conventional probes. Application of this approach to plant systems for super-resolution imaging has been relatively slow owing in large part to aberrations incurred when imaging through the plant cell wall. In this brief review, we address the use of two prominent methods for generating super-resolution images in living plant specimens and discuss future directions for gaining better access to these techniques.

Handheld Adaptive Optics Scanning Laser Ophthalmoscope

Adaptive optics scanning laser ophthalmoscopy (AOSLO) has enabled in vivo visualization and enhanced understanding of retinal structure and function. Current generation AOSLOs have a large footprint and are mainly limited to imaging cooperative adult subjects. To extend the application of AOSLO to new patient populations, we have designed the first portable handheld AOSLO (HAOSLO) system. By incorporating a novel computational wavefront sensorless AO algorithm and custom optics, we have miniaturized our HAOSLO to weigh less than 200 grams. HAOSLO imaged the cones closest to the fovea with a handheld probe in adults and captured the first AO-enhanced image of cones in infants.

Aqueous mounting media increasing tissue translucence improve image quality in Structured Illumination Microscopy of thick biological specimen

Structured Illumination Microscopy (SIM) is a super-resolution microscopy method that has significantly advanced studies of cellular structures. It relies on projection of illumination patterns onto a fluorescently labelled biological sample. The information derived from the sample is then shifted to a detectable band, and in the process of image calculation in Fourier space the resolution is doubled. Refractive index homogeneity along the optical path is crucial to maintain a highly modulated illumination pattern necessary for high-quality SIM. This applies in particular to thick samples consisting of large cells and tissues. Surprisingly, sample mounting media for SIM have not undergone a significant evolution for almost a decade. Through identification and systematic evaluation of a number of non-hazardous, water-soluble chemical components of mounting media, we demonstrate an unprecedented improvement in SIM-image quality. Mounting solutions presented in this research are capable of reducing abundant light scattering which constitutes the limiting factor in 3D-SIM imaging of large Hodgkin's lymphoma and embryonic stem cells as well as 10 µm tissue sections. Moreover, we demonstrate usefulness of some of the media in single molecule localisation microscopy. The results presented here are of importance for standardisation of 3D-SIM data acquisition pipelines for an expanding community of users.

Aberration correction method based on double-helix point spread function

Point spread function (PSF) engineering has met with lots of interest in various optical imaging techniques, including super-resolution microscopy, microparticle tracking, and extended depth-of-field microscopy. The intensity distributions of the modified PSFs often suffer from deteriorations caused by system aberrations, which greatly degrade the image contrast, resolution, or localization precision. We present an aberration correction method using a spiral-phase-based double-helix PSF as an aberration indicator, which is sensitive and quantitatively correlated to the spherical aberration, coma, and astigmatism. Superior to the routine iteration-based correction methods, the presented approach is iteration-free and the aberration coefficients can be directly calculated with the measured parameters, relieving the computing burden. The validity of the method is verified by both examining the intensity distribution of the conventional Gaussian PSF in three dimensions and observing muntjac skin fibroblast cells. This iteration-free correction method has a potential application in PSF engineering systems equipped with a spatial light modulator.

Image restoration approach to address reduced modulation contrast in structured illumination microscopy

The performance of structured illumination microscopy (SIM) is hampered in many biological applications due to the inability to modulate the light when imaging deep into the sample. This is in part because sample-induced aberration reduces the modulation contrast of the structured pattern. In this paper, we present an image restoration approach suitable for processing raw incoherent-grid-projection SIM data with a low fringe contrast. Restoration results from simulated and experimental ApoTome SIM data show results with improved signal-to-noise ratio (SNR) and optical sectioning compared to the results obtained from existing methods, such as 2D demodulation and 3D SIM deconvolution. Our proposed method provides satisfactory results (quantified by the achieved SNR and normalized mean square error) even when the modulation contrast of the illumination pattern is as low as 7%.

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.

Imaging neuronal structure dynamics using 2-photon super-resolution patterned excitation reconstruction microscopy

Visualizing fine neuronal structures deep inside strongly light-scattering brain tissue remains a challenge in neuroscience. Recent nanoscopy techniques have reached the necessary resolution but often suffer from limited imaging depth, long imaging time or high light fluence requirements. Here, we present two-photon super-resolution patterned excitation reconstruction (2P-SuPER) microscopy for 3-dimensional imaging of dendritic spine dynamics at a maximum demonstrated imaging depth of 130 μm in living brain tissue with approximately 100 nm spatial resolution. We confirmed 2P-SuPER resolution using fluorescence nanoparticle and quantum dot phantoms and imaged spiny neurons in acute brain slices. We induced hippocampal plasticity and showed that 2P-SuPER can resolve increases in dendritic spine head sizes on CA1 pyramidal neurons following theta-burst stimulation of Schaffer collateral axons. 2P-SuPER further revealed nanoscopic increases in dendritic spine neck widths, a feature of synaptic plasticity that has not been thoroughly investigated due to the combined limit of resolution and penetration depth in existing imaging technologies.

Adaptive optical microscopy for neurobiology

With the ability to correct for the aberrations introduced by biological specimens, adaptive optics-a method originally developed for astronomical telescopes-has been applied to optical microscopy to recover diffraction-limited imaging performance deep within living tissue. In particular, this technology has been used to improve image quality and provide a more accurate characterization of both structure and function of neurons in a variety of living organisms. Among its many highlights, adaptive optical microscopy has made it possible to image large volumes with diffraction-limited resolution in zebrafish larval brains, to resolve dendritic spines over 600μm deep in the mouse brain, and to more accurately characterize the orientation tuning properties of thalamic boutons in the primary visual cortex of awake mice.

Adaptive optics stochastic optical reconstruction microscopy (AO-STORM) by particle swarm optimization

Stochastic optical reconstruction microscopy (STORM) can achieve resolutions of better than 20nm imaging single fluorescently labeled cells. However, when optical aberrations induced by larger biological samples degrade the point spread function (PSF), the localization accuracy and number of localizations are both reduced, destroying the resolution of STORM. Adaptive optics (AO) can be used to correct the wavefront, restoring the high resolution of STORM. A challenge for AO-STORM microscopy is the development of robust optimization algorithms which can efficiently correct the wavefront from stochastic raw STORM images. Here we present the implementation of a particle swarm optimization (PSO) approach with a Fourier metric for real-time correction of wavefront aberrations during STORM acquisition. We apply our approach to imaging boutons 100 μm deep inside the central nervous system (CNS) of Drosophila melanogaster larvae achieving a resolution of 146 nm.

Image scanning microscopy: an overview

For almost a century, the resolution of optical microscopy was thought to be limited by Abbé's law describing the diffraction limit of light. At the turn of the millennium, aided by new technologies and fluorophores, the field of optical microscopy finally surpassed the diffraction barrier: a milestone achievement that has been recognized by the 2014 Nobel Prize in Chemistry. Many super-resolution methods rely on the unique photophysical properties of the fluorophores to improve resolution, posing significant limitations on biological imaging, such as multicoloured staining, live-cell imaging and imaging thick specimens. Structured Illumination Microscopy (SIM) is one branch of super-resolution microscopy that requires no such special properties of the applied fluorophores, making it more versatile than other techniques. Since its introduction in biological imaging, SIM has proven to be a popular tool in the biologist's arsenal for following biological interaction and probing structures of nanometre scale. SIM continues to see much advancement in design and implementation, including the development of Image Scanning Microscopy (ISM), which uses patterned excitation via either predefined arrays or raster-scanned single point-spread functions (PSF). This review aims to give a brief overview of the SIM and ISM processes and subsequent developments in the image reconstruction process. Drawing from this, and incorporating more recent achievements in light shaping (i.e. pattern scanning and super-resolution beam shaping), this study also intends to suggest potential future directions for this ever-expanding field.

Characterization of wavefront errors in mouse cranial bone using second-harmonic generation

Optical aberrations significantly affect the resolution and signal-to-noise ratio of deep tissue microscopy. As multiphoton microscopy is applied deeper into tissue, the loss of resolution and signal due to propagation of light in a medium with heterogeneous refractive index becomes more serious. Efforts in imaging through the intact skull of mice cannot typically reach past the bone marrow ( ? 150 ?? ? m of depth) and have limited resolution and penetration depth. Mechanical bone thinning or optical ablation of bone enables deeper imaging, but these methods are highly invasive and may impact tissue biology. Adaptive optics is a promising noninvasive alternative for restoring optical resolution. We characterize the aberrations present in bone using second-harmonic generation imaging of collagen. We simulate light propagation through highly scattering bone and evaluate the effect of aberrations on the point spread function. We then calculate the wavefront and expand it in Zernike orthogonal polynomials to determine the strength of different optical aberrations. We further compare the corrected wavefront and the residual wavefront error, and suggest a correction element with high number of elements or multiconjugate wavefront correction for this highly scattering environment.

Image-based adaptive optics for in vivo imaging in the hippocampus

Adaptive optics is a promising technique for the improvement of microscopy in tissues. A large palette of indirect and direct wavefront sensing methods has been proposed for in vivo imaging in experimental animal models. Application of most of these methods to complex samples suffers from either intrinsic and/or practical difficulties. Here we show a theoretically optimized wavefront correction method for inhomogeneously labeled biological samples. We demonstrate its performance at a depth of 200 μm in brain tissue within a sparsely labeled region such as the pyramidal cell layer of the hippocampus, with cells expressing GCamP6. This method is designed to be sample-independent thanks to an automatic axial locking on objects of interest through the use of an image-based metric that we designed. Using this method, we show an increase of in vivo imaging quality in the hippocampus.

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.

In vivo super-resolution retinal imaging through virtually structured detection

High resolution is important for sensitive detection of subtle distortions of retinal morphology at an early stage of eye diseases. We demonstrate virtually structured detection (VSD) as a feasible method to achieve in vivo super-resolution ophthalmoscopy. A line-scanning strategy was employed to achieve a super-resolution imaging speed up to 127 ?? frames / s with a frame size of 512 × 512 ?? pixels . The proof-of-concept experiment was performed on anesthetized frogs. VSD-based super-resolution images reveal individual photoreceptors and nerve fiber bundles unambiguously. Both image contrast and signal-to-noise ratio are significantly improved due to the VSD implementation.

Coherence-Gated Sensorless Adaptive Optics Multiphoton Retinal Imaging

Multiphoton microscopy enables imaging deep into scattering tissues. The efficient generation of non-linear optical effects is related to both the pulse duration (typically on the order of femtoseconds) and the size of the focused spot. Aberrations introduced by refractive index inhomogeneity in the sample distort the wavefront and enlarge the focal spot, which reduces the multiphoton signal. Traditional approaches to adaptive optics wavefront correction are not effective in thick or multi-layered scattering media. In this report, we present sensorless adaptive optics (SAO) using low-coherence interferometric detection of the excitation light for depth-resolved aberration correction of two-photon excited fluorescence (TPEF) in biological tissue. We demonstrate coherence-gated SAO TPEF using a transmissive multi-actuator adaptive lens for in vivo imaging in a mouse retina. This configuration has significant potential for reducing the laser power required for adaptive optics multiphoton imaging, and for facilitating integration with existing systems.

Sensorless adaptive optics implementation in widefield optical sectioning microscopy inside in vivo Drosophila brain

We present an implementation of a sensorless adaptive optics loop in a widefield fluorescence microscope. This setup is designed to compensate for aberrations induced by the sample on both excitation and emission pathways. It allows fast optical sectioning inside a living Drosophila brain. We present a detailed characterization of the system performances. We prove that the gain brought to optical sectioning by realizing structured illumination microscopy with adaptive optics down to 50 μm deep inside living Drosophila brain.

Aberrations and adaptive optics in super-resolution microscopy

As one of the most powerful tools in the biological investigation of cellular structures and dynamic processes, fluorescence microscopy has undergone extraordinary developments in the past decades. The advent of super-resolution techniques has enabled fluorescence microscopy - or rather nanoscopy - to achieve nanoscale resolution in living specimens and unravelled the interior of cells with unprecedented detail. The methods employed in this expanding field of microscopy, however, are especially prone to the detrimental effects of optical aberrations. In this review, we discuss how super-resolution microscopy techniques based upon single-molecule switching, stimulated emission depletion and structured illumination each suffer from aberrations in different ways that are dependent upon intrinsic technical aspects. We discuss the use of adaptive optics as an effective means to overcome this problem.

Adaptive optics stochastic optical reconstruction microscopy (AO-STORM) using a genetic algorithm

The resolution of Single Molecule Localization Microscopy (SML) is dependent on the width of the Point Spread Function (PSF) and the number of photons collected. However, biological samples tend to degrade the shape of the PSF due to the heterogeneity of the index of refraction. In addition, there are aberrations caused by imperfections in the optical components and alignment, and the refractive index mismatch between the coverslip and the sample, all of which directly reduce the accuracy of SML. Adaptive Optics (AO) can play a critical role in compensating for aberrations in order to increase the resolution. However the stochastic nature of single molecule emission presents a challenge for wavefront optimization because the large fluctuations in photon emission do not permit many traditional optimization techniques to be used. Here we present an approach that optimizes the wavefront during SML acquisition by combining an intensity independent merit function with a Genetic algorithm (GA) to optimize the PSF despite the fluctuating intensity. We demonstrate the use of AO with GA in tissue culture cells and through ~50µm of tissue in the Drosophila Central Nervous System (CNS) to achieve a 4-fold increase in the localization precision.

Enhanced resolution through thick tissue with structured illumination and adaptive optics

Structured illumination microscopy provides twice the linear resolution of conventional fluorescence microscopy, but in thick samples, aberrations degrade the performance and limit the resolution. Here, we demonstrate structured illumination microscopy through 35 μm of tissue using adaptive optics (AO) to correct aberrations resulting in images with a resolution of 140 nm. We report a 60% minimum improvement in the signal-to-noise ratio of the structured illumination reconstruction through thick tissue by correction with AO.

In vivo imaging of human photoreceptor mosaic with wavefront sensorless adaptive optics optical coherence tomography

Wavefront sensorless adaptive optics optical coherence tomography (WSAO-OCT) is a novel imaging technique for in vivo high-resolution depth-resolved imaging that mitigates some of the challenges encountered with the use of sensor-based adaptive optics designs. This technique replaces the Hartmann Shack wavefront sensor used to measure aberrations with a depth-resolved image-driven optimization algorithm, with the metric based on the OCT volumes acquired in real-time. The custom-built ultrahigh-speed GPU processing platform and fast modal optimization algorithm presented in this paper was essential in enabling real-time, in vivo imaging of human retinas with wavefront sensorless AO correction. WSAO-OCT is especially advantageous for developing a clinical high-resolution retinal imaging system as it enables the use of a compact, low-cost and robust lens-based adaptive optics design. In this report, we describe our WSAO-OCT system for imaging the human photoreceptor mosaic in vivo. We validated our system performance by imaging the retina at several eccentricities, and demonstrated the improvement in photoreceptor visibility with WSAO compensation.

Super-resolution imaging in live cells

Over the last twenty years super-resolution fluorescence microscopy has gone from proof-of-concept experiments to commercial systems being available in many labs, improving the resolution achievable by up to a factor of 10 or more. There are three major approaches to super-resolution, stimulated emission depletion microscopy, structured illumination microscopy, and localisation microscopy, which have all produced stunning images of cellular structures. A major current challenge is optimising performance of each technique so that the same sort of data can be routinely taken in live cells. There are several major challenges, particularly phototoxicity and the speed with which images of whole cells, or groups of cells, can be acquired. In this review we discuss the various approaches which can be successfully used in live cells, the tradeoffs in resolution, speed, and ease of implementation which one must make for each approach, and the quality of results that one might expect from each technique.

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Super-resolution imaging of cell structures can achieve a resolution of tens of nm.

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There are three major techniques: STED, SIM, and localisation microscopy.

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Live cell super-resolution requires trading off resolution, speed, and light dose.