Multifocal Structured Illumination Microscopy Research Articles

Polarization-resolved super-resolution second-harmonic generation imaging based on multifocal structured illumination microscopy.

Polarization-resolved second-harmonic generation (PSHG) microscopy is widely used in investigating the structural and morphological alterations of collagen. However, the resolution of second-harmonic generation (SHG) imaging remains constrained by optical diffraction, resulting in the polarization extraction of collagen characteristics from the average properties of collagen fibers. In this study, multifocal structured illumination microscopy (MSIM) was combined with PSHG to achieve polarization-resolved super-resolution imaging of second-harmonic generation signals. For the first time to our knowledge, periodic structures with an average pitch of 277 nm were observed in mouse tail tendons using optical microscopy, and the orientation angle of fibrils within each period was found to exhibit an alternating arrangement along the axis in a regular pattern.

Deep tissue super-resolution imaging with adaptive optical two-photon multifocal structured illumination microscopy

Visualization of axons and dendritic spines is crucial in neuroscience research. However, traditional microscopy is limited by diffraction-limited resolution and shallow imaging depth, making it difficult to study neuronal dynamics. Two-photon multifocal structured illumination microscopy (2P-MSIM) provides super-resolution imaging along with a reasonably good penetration, but it is vulnerable to optical aberrations in deep tissues. Herein we present a novel non-inertial scanning 2P-MSIM system incorporated with adaptive optics (AO) which allows for super-resolution imaging with effective aberration correction. Our strategy is designed to correct both laser and fluorescence paths simultaneously using a spatial light modulator and a deformable mirror respectively, providing better results than the individual path corrections. The successful implementation of adaptive optical two-photon multifocal structured illumination microscopy (AO 2P-MSIM) has allowed for the super-resolution imaging of neuronal structures in a mouse brain slice at great depths and dynamic morphological characteristics of zebrafish motoneurons in vivo.

Super-Resolution Second-Harmonic Generation Imaging with Multifocal Structured Illumination Microscopy.

Second-harmonic generation (SHG) is a noninvasive imaging technique that enables the exploration of physiological structures without the use of an exogenous label. However, traditional SHG imaging is limited by optical diffraction, which restricts the spatial resolution. To break this limitation, we developed a novel approach called multifocal structured illumination microscopy-SHG (MSIM-SHG). By combination of SHG with MSIM, SHG-based super-resolution imaging of material molecules can be achieved, and this SHG super-resolution imaging has a wide range of applications for biological tissues and cells. MSIM-SHG achieved a lateral full width at half-maximum (fwhm) of 147 ± 13 nm and an axial fwhm of 493 ± 47 nm by imaging zinc oxide (ZnO) particles. Furthermore, MSIM-SHG was utilized to quantify collagen fiber alignment in various tissues such as the ovary, muscle, heart, kidney, and cartilage, demonstrating its feasibility for identifying collagen characteristics. MSIM-SHG has potential as a powerful tool for clinical diagnosis and biological research.

Rapid reconstruction algorithm for multifocal structured illumination microscopy

Multifocal structured illumination microscopy (MSIM) could surpass the diffraction limit by illuminating the sample with multiple-spot grid patterns. Developed as a parallel version of image scanning microscopy (ISM) to enhance data acquisition speed, MSIM can also be viewed as a variation of structured illumination microscopy (SIM) in which the conventional sinusoidal illumination is substituted with a lattice array of spots. This method outperforms regular SIM when imaging samples that are thick or highly scattered. In this study, we present a rapid reconstruction algorithm for MSIM in the spatial domain and demonstrate that the radius of its equivalent optical transfer function (OTF) support is twice that of a general wide-field microscopy in the epi-illumination geometry. Numerical simulations and experimental results have validated the effectiveness of the proposed algorithm.

Deep-MSIM: Fast Image Reconstruction with Deep Learning in Multifocal Structured Illumination Microscopy.

Fast and precise reconstruction algorithm is desired for for multifocal structured illumination microscopy (MSIM) to obtain the super-resolution image. This work proposes a deep convolutional neural network (CNN) to learn a direct mapping from raw MSIM images to super-resolution image, which takes advantage of the computational advances of deep learning to accelerate the reconstruction. The method is validated on diverse biological structures and in vivo imaging of zebrafish at a depth of 100µm. The results show that high-quality, super-resolution images can be reconstructed in one-third of the runtime consumed by conventional MSIM method, without compromising spatial resolution. Last but not least, a fourfold reduction in the number of raw images required for reconstruction is achieved by using the same network architecture, yet with different training data.

Narrowband photoblinking InP/ZnSe/ZnS quantum dots for super-resolution multifocal structured illumination microscopy enhanced by optical fluctuation

Abstract Cadmium-free quantum-dot (QD) fluorophores can bridge the gap between the macroscopic and microscopic domains in fluorescence super-resolution bioimaging. InP/ZnSe/ZnS QD photoblinking fluorescent probes can improve the performance of reactive super-resolution imaging techniques and spontaneously switch fluorophores between at least two states (open and close) without depending on intense laser light and specialized buffers for bioimaging. Multifocal structured illumination microscopy (MSIM) provides a two-fold resolution enhancement in sub-diffraction imaging, but higher resolutions are limited by the pattern frequency and signal-to-noise ratio. We exploit the synergy between MSIM and spontaneously switching InP/ZnSe/ZnS QD fluorophores to further increase the imaging resolution. We demonstrate the experimental combination of optical-fluctuation-enhanced super-resolution MSIM using ultrasonic-oscillation-assisted organic solvothermal synthesis of narrowband photoblinking InP/ZnSe/ZnS QDs. The InP/ZnSe/ZnS QDs show a monodisperse grain size of approximately 9 nm, fluorescence quantum yields close to 100%, and full width at half maximum below 30 nm. The structural, electronic, and optical properties are characterized through experiments and first-principles calculations. The enhanced MSIM imaging achieves an approximate fourfold improvement in resolution for fixed cells compared with widefield imaging. The proposed InP/ZnSe/ZnS QD fluorescent probes seem promising for super-resolution imaging using MSIM.

Nonblinking Core–Multishell InP/ZnSe/ZnS Quantum Dot Bioconjugates for Super-resolution Imaging

Colloidal quantum dots (QDs) are vital fluorescent probes with several optical features superior to those found in organic dyes for microscopy imaging. However, the emission blinking behavior of a single QD is an intrinsic drawback for stimulated emission depletion microscopy (STED) or structured illumination microscopy techniques. Herein, we present a rational strategy for the synthesis of a type of deterministic, environmentally friendly, small nonblinking core–multishell InP/ZnSe/ZnS QD using a hydrofluoric acid (HF) etching passivation. The strategy includes four steps: synthesis of the InP core, synthesis of oil-phase core–multishell InP/ZnSe/ZnS QDs using hydrogen fluoride and trioctylphosphine etching passivation, promotion of the water solubility of QDs modified by 3-mercaptopropionic acid (MPA), and enhanced biotargeting of core–multishell InP/ZnSe/ZnS QDs by surface coupling technology. The suppressed blinking mechanism was primarily attributed to surface wrapping shells and HF etching passivation of surface dangling bonds, which reduced surface nonradiative recombination. Nonblinking QDs exhibit high fluorescence efficiency (∼90%), good photostability (>20 min), a large Stokes shift (>135 nm), biocompatibility of the cell viability (>90%), and high targeting. Furthermore, super-resolution multifocal structured illumination microscopy imaging of subcellular structures labeled using these QDs confirmed a resolution improvement of greater than 2.6-fold compared to wide-field microscopy. The results indicate that the nonblinking QDs can function as excellent probes for use in the long-term super-resolution visualization of subcellular dynamics.

NIR-II multifocal structured illumination microscopy.

Optical microscopy has been widely used as a versatile tool in biological research. However, its penetration depth and spatial resolution are desperately limited by light scattering during deep propagation in turbid medium. Here, we implement near-infrared second window (1000-1700 nm) multifocal structured illumination microscopy (NIR-II MSIM) capable of deep penetration, high contrast, and enhanced spatial resolution. Raster-scanning multifocal illumination patterns ensure homogeneous illumination of the sample. By integrating NIR-II photoemission into multifocal photoexcitation, NIR-II MSIM affords deep imaging with improved lateral resolution (∼1.49 µm) at a depth of 2.5 mm in an Intralipid/agar phantom and outstanding contrast. Additionally, imaging at longer wavelength in the NIR-II region shows superior performance. This NIR-II MSIM system will afford a promising platform for studying physiological phenomena in turbid specimens in the future.

Blind optical sectioning and super-resolution imaging in multifocal structured illumination microscopy

Using sparse multi-spot patterns, multifocal structured illumination microscopy (MSIM) can retrieve the 3D structures of thick samples with improved lateral resolution. In the existing MSIM techniques, the accurate parameters of microscope and positions of the illumination focus in the captured images are essential for suppressing the out-of-focus light and improving the lateral resolution. Tedious calibration procedures thus should be carried out in these MSIM techniques. Hence, a blind optical sectioning and super-resolution (OS-SR) imaging method in MSIM is proposed in this paper. The proposed method combines a deconvolution method with the standard deviation method. It can achieve OS-SR images without calibrating the accurate parameters of microscope and the positions of the foci. The validity of the proposed method is demonstrated by simulation and experimental results.

Flat-field multiplexed multifocal structured illumination super-resolution microscopy

Multifocal structured illumination microscopy (MSIM) can achieve optically sectioned images with twice the diffraction limited resolution at an imaging speed of 1 Hz and an imaging depth of up to 50 μm. Compared with the traditional wide-field SIM, the MSIM has greater imaging depth and optical sectionning ability, and it is more suitable for long-term three-dimensional (3D) super-resolution imaging of living thick samples. However, the MSIM has some problems, such as slow imaging speed and complex image post-processing process. In this work, a fast super-resolution imaging method and system based on the flat-field multiplexed MSIM (FM-MSIM) is proposed. By inserting a beam shaping device into the illumination light path, the Gaussian beam is reshaped into a uniform flat-top profile, thereby improving the intensity uniformity of excitation multi-spot focal array and expanding the field of view. By elongating each diffraction limited excitation focal point four times along the <i>Y</i> direction to form a new multiplexed multifocal array pattern, the number of scanning steps is reduced, the energy utilization is improved, and then the imaging speed and signal-to-noise ratio are improved. Combined with the sparse Bayesian learning image reconstruction algorithm based on multiple measurement vector model, the image reconstruction steps are simplified, the imaging speed can be improved at least 4 times while ensuring the spatial resolution of MSIM. On this basis, the established FM-MSIM system is used to carry out the super-resolution imaging experiments on the BSC cell microtubule samples and mouse kidney slices. The experimental results prove the fast three-dimensional super-resolution imaging ability of the system, which is of great significance in developing the fast MSIM.

Two-photon multifocal structured light microscopy based on high-speed phase-type spatial light modulator

Multifocal structured illumination microscopy (MSIM) can achieve a doubled improvement in the resolution of the diffraction limit within an imaging depth of 50 μm. But when imaging thick samples, scattered light and defocused light limit its optical sectioning capability and image contrast. Two-photon MSIM (2P-MSIM) overcomes the influence of sample tissue scattering and further improves the imaging depth and imaging characteristics. However, the existing 2P-MSIM usually adopts galvanometer based scanning mirrors for precisely scanning imaging, which is a complicated and poor flexibility system. Here we propose a simpler 2P-MSIM. Two-photon multifocal scanning imaging can be realized by a spatial light modulator (SLM) with a high frame rate (< 845 Hz). The phase map of generating multi-focus array and linear phase grating loaded on the SLM simultaneously, high-precision parallel digital random address scanning and excitation imaging on the sample surface can be realized. The mechanical inertia problem of the galvanometer scanner in multifocal imaging can be solved by the proposed method while reducing the complexity of the system and improving flexibility. We finally realize two-photon multifocal imaging of mouse kidney tissue slices and lily of the valley rhizome by this system, which verifies the three-dimensional super-resolution imaging capability of this method. It is of great significance in developing the 2P-MSIM.

Enhanced multifocal structured illumination microscopy with desired optical sectioning capability and lateral resolution improvement.

Multifocal structured illumination microscopy (MSIM) can rapidly retrieve 3D structures of thick samples by using multi-spot excitation and detection. Although numerous super-resolution (SR) and optical sectioning (OS) methods have been introduced in this field, the existing OS-SR method in MSIM still has the difficulty in rejecting deep defocused light, which may lead to strong background signal in the retrieved results. To this end, an enhanced OS-SR method is proposed to simultaneously achieve the desired OS capability and significant resolution improvement in MSIM. The enhanced OS-SR image is obtained by combining the standard deviation image with the conventional OS-SR image in the frequency domain. The validity of the proposed method is demonstrated by simulation and experimental results.

Efficient Multifocal Structured Illumination Microscopy Utilizing a Spatial Light Modulator

We demonstrated an efficient system for multifocal structured illumination microscopy (MSIM) utilizing a spatial light modulator (SLM). Nine phase profiles of chessboard phase plates loaded on the SLM in sequence are used to generate nine multifocal arrays on the focal plane. Subsequently, nine raw multifocal images are acquired. Finally, by extracting the parameters of the illumination patterns from the raw images precisely, a final super-resolved image is reconstructed by performing the standard reconstruction procedure of structured illumination microscopy (SIM). Our MSIM system realized nearly a 1.5-fold enhancement in spatial resolution compared with wide-field (WF) microscopy. The feasibility of the present system is validated on experiments and the results show its great performances along with good compatibility.

Hybrid multifocal structured illumination microscopy with enhanced lateral resolution and axial localization capability.

Super-resolution (SR) fluorescence microscopy that breaks through the diffraction barrier has drawn great interest in biomedical research. However, obtaining a high precision three-dimensional distribution of the specimen in a short time still remains a challenging task for existing techniques. In this paper, we propose a super-resolution fluorescence microscopy with axial localization capability by combining multifocal structured illumination microscopy with a hybrid detection PSF composed of a Gaussian PSF and a double-helix PSF. A modified reconstruction scheme is presented to accommodate the new hybrid PSF. This method can not only recover the lateral super-resolution image of the specimen but also retain the specimen's depth map within a range of 600 nm with an axial localization precision of 20.8 nm. The performance of this approach is verified by testing fluorescent beads and tubulin in 293-cells. The developed microscope is well suited for observing the precise 3D distribution of thin specimens.

Optimized approach for optical sectioning enhancement in multifocal structured illumination microscopy.

Multifocal structured illumination microscopy (MSIM) is the parallelized version of image scanning microscopy (ISM) that is created by using many excitation spots, which provides a two-fold resolution enhancement beyond the diffraction limit with a frequency of 1 Hz per 3D picture, but scattered and out-of-focus light in thick samples degrades MSIM optical sectioning performance. Herein, we introduce a new optical sectioning method in MSIM via illumination fluctuation. The proposed method suppresses the out-of-focus light by taking full advantage of the statistic property of MSIM raw data and has no requirement of changing the system setup or projecting more illumination patterns. Experimental results demonstrate that the method can reduce the out-of-focus light by 7.25 times in optical sectioning image.

Digital line scanning fluorescence microscopy based on digital micromirror device

Laser scanning confocal microscope (LSCM) is one of the most important tools for biological imaging due to its strong optical sectioning capability, high signal-to-noise ratio, and high resolution. On the basis of LSCM, line-scanning fluorescence microscopy (LSFM) uses linear scanning instead of point scanning to improve the speed of image acquisition. It has the advantages of simple system structure, fast imaging speed, and weak phototoxicity, and in addition, it is more suitable for high-resolution and fast imaging of living thick samples. It is of great significance for studying the life science, biomedicine, and others. However, the current LSFM technology still faces many urgent problems in terms of system flexibility, imaging speed, resolution and optical sectioning capabilities. Therefore, based on the existing multifocal structured illumination microscopy (MSIM) in our laboratory, a digital line-scanning fluorescence microscopy (DLSFM) based on digital micromirror device(DMD) is presented in this paper. In the illumination path, a high-speed spatial light modulator DMD is adopted to realize multi-line parallel scanning excitation, which simplies the optical system and improves the flexibility and scanning speed of the system. A DLSFM image reconstruction algorithm based on the standard deviation of fluorescence signal is proposed, which is combined withthree-dimensional (3D) Landweber deconvolution algorithm to achieve 3D high-resolution optical slice image reconstruction. On this basis, the imaging experiments on fluorescent beads and standard samples of mouse kidney section are carried out by using DLSFM. The experimental results show that the resolution of DLSFM in the <i>x</i>, <i>y</i> and <i>z</i> directions is 1.33 times, 1.42 times and 1.19 times that of wide field microscope, respectively, and the fast 3D high-resolution optical sectioning imaging of biological samples is realized, which lays a technical foundation for further developing the rapid high-resolution imaging of the whole cells and tissues in vivo.

A method for the reconstruction of multifocal structured illumination microscopy data with high efficiency

We present and demonstrate an efficient method for the reconstruction of profiles acquired by multifocal structured illumination microscopy (MSIM) utilizing few raw images. Firstly, we propose a method to produce nine raw multifocal images with enhanced modulation depth to accomplish the uniform illumination of the sample. Then, combing with the parameter of the arrays, we perform the standard construct reconstruction procedure of structured illumination microscopy (SIM) row by row and column by column. Finally, we combine these restored images together to obtain the final image with enhanced resolution and good contrast. Based on theoretical analysis and numerical simulations, this method shows great potential in the field of the image reconstruction of MSIM data.

Resolution improvement of multifocal structured illumination microscopy with sparse Bayesian learning algorithm.

Multifocal structured illumination microscopy (MSIM) is the parallelized version of image scanning microscopy (ISM), which uses multiple diffraction limited spots, instead of a single diffraction limited spot, to increase the imaging speed. By adding pinhole, contraction and deconvolution, a twofold resolution enhancement could be achieved in theory. However, this resolution improvement is difficult to be attained in practice. In this work, without any modification of the experimental setup, we propose to use multiple measurement vector (MMV) model sparse Bayesian learning (MSBL) algorithm (MSIMMSBL) as the reconstruction algorithm of MSIM, which does not need to estimate the illumination patterns but treat the reconstruct process as an MMV signal reconstruction problem. We compare the reconstructed super-resolution images of MSIMMSBL and MSIM by using simulation and experimental raw images. The results prove that by using the MSBL algorithm, the MSIM can obtain a higher than twofold resolution enhancement compared with the wide field image. This outstanding imaging resolution combining with the primary advantages of MSIM, such as the high imaging speed, could promote the application of MSIM in super-resolution microscopy imaging technology.

Rapid 3D image scanning microscopy with multi-spot excitation and double-helix point spread function detection.

Refocusing after Scanning using Helical phase engineering (RESCH) microscopy has previously been demonstrated to provide volumetric information from a single 2D scan. However, the practical application of this method is challenging due to its limited image acquisition speed and spatial resolution. Here, we report on a combination of RESCH and multifocal structured illumination microscopy (MSIM) to improve the image acquisition speed and spatial resolution. A phase mask is introduced to modulate the conventional point spread function (PSF) to the double-helix PSF (DH-PSF), which provides volumetric information, and meanwhile, sparse multifocal illumination patterns are generated by a digital micromirror device (DMD) for parallel 3D subdiffractive imaging information acquisition. We also present a strategy for processing the collected raw data with a Richardson-Lucy deconvolution and pixel reassignment algorithm to improve the spatial resolution of the depth estimation and imaging performance. The proposed 3D image scanning microscopy can record 3D specimen information and the corresponding depth information from a single multi-spot 2D planar scan, which ensures faster data acquisition, larger field of view, and higher spatial resolution than RESCH. Finally, we demonstrate the capability of our system with actual experiments.

A joint Richardson—Lucy deconvolution algorithm for the reconstruction of multifocal structured illumination microscopy data

We demonstrate the reconstruction of images obtained by multifocal structured illumination microscopy, MSIM, using a joint Richardson–Lucy, jRL-MSIM, deconvolution algorithm, which is based on an underlying widefield image-formation model. The method is efficient in the suppression of out-of-focus light and greatly improves image contrast and resolution. Furthermore, it is particularly well suited for the processing of noise corrupted data. The principle is verified on simulated as well as experimental data and a comparison of the jRL-MSIM approach with the standard reconstruction procedure, which is based on image scanning microscopy, ISM, is made. Our algorithm is efficient and freely available in a user friendly software package.