Multi-scan structured illumination microscopy for rapid and efficient volumetric super-resolution imaging

Structured illumination microscopy (SIM) is one of the most powerful and versatile super-resolution methods due to its live-cell imaging ability of subcellular structures with high speed. In this paper, we propose an alternative SIM assisted by Bloch surface wave (BSW). Through replacing the conventional laser interference fringes with sub-diffraction BSW counterparts with higher spatial frequency, the imaging resolution of SIM could be enhanced greatly and the super-resolution imaging capability down to 80 nm could be achieved. Compared with traditional wide-field fluorescence microscopy, this BSW SIM demonstrates 2.78 times enhancement in imaging resolution, which surpasses general SIM with only 2 times improvement. Moreover, the structured illumination intensity could be boosted drastically, which is beneficial to nonlinear super-resolution imaging techniques, such as saturated SIM. This BSW SIM would provide a super-resolution, wide field of view approach for surface super-resolution fluorescent imaging while maintaining high imaging speed and good bio-compatibility.

Structured illumination microscopy (SIM) is a popular and powerful super-resolution (SR) technique in biomedical research. However, the conventional reconstruction algorithm for SIM heavily relies on the accurate prior knowledge of illumination patterns and signal-to-noise ratio (SNR) of raw images. To obtain high-quality SR images, several raw images need to be captured under high fluorescence level, which further restricts SIM’s temporal resolution and its applications. Deep learning (DL) is a data-driven technology that has been used to expand the limits of optical microscopy. In this study, we propose a deep neural network based on multi-level wavelet and attention mechanism (MWAM) for SIM. Our results show that the MWAM network can extract high-frequency information contained in SIM raw images and accurately integrate it into the output image, resulting in superior SR images compared to those generated using wide-field images as input data. We also demonstrate that the number of SIM raw images can be reduced to three, with one image in each illumination orientation, to achieve the optimal tradeoff between temporal and spatial resolution. Furthermore, our MWAM network exhibits superior reconstruction ability on low-SNR images compared to conventional SIM algorithms. We have also analyzed the adaptability of this network on other biological samples and successfully applied the pretrained model to other SIM systems.

The objective of optical super-resolution imaging is to acquire reliable sub-diffraction information on bioprocesses to facilitate scientific discovery. Structured illumination microscopy (SIM) is acknowledged as the optimal modality for live-cell super-resolution imaging. Although recent deep learning techniques have substantially advanced SIM, their transparency and reliability remain uncertain and under-explored, often resulting in unreliable results and biological misinterpretation. Here, we develop Bayesian deep learning (BayesDL) for SIM, which enhances the reconstruction of densely labeled structures while enabling the quantification of super-resolution uncertainty. With the uncertainty, BayesDL-SIM achieves high-fidelity distribution-informed SIM imaging, allowing for the communication of credibility estimates to users regarding the model outcomes. We also demonstrate that BayesDL-SIM boosts SIM reliability by identifying and preventing erroneous generalizations in various model misuse scenarios. Moreover, the BayesDL uncertainty shows versatile utilities for daily super-resolution imaging, such as error estimation, data acquisition evaluation, etc. Furthermore, we demonstrate the effectiveness and superiority of BayesDL-SIM in live-cell imaging, which reliably reveals F-actin dynamics and the reorganization of the cell cytoskeleton. This work lays the foundation for the reliable implementation of deep learning-based SIM methods in practical applications.

Structured illumination microscopy (SIM) is one of the most significant widefield super-resolution optical imaging techniques. The conventional SIM utilizes a sinusoidal structured pattern to excite the fluorescent sample; which eventually down-modulates higher spatial frequency sample information within the diffraction-limited passband of the microscopy system and provides around two-fold resolution enhancement over diffraction limit after suitable computational post-processing. Here we provide an overview of the basic principle, image reconstruction, technical development of the SIM technique. Nonetheless, in order to push the SIM resolution further towards the extreme nanoscale dimensions, several different approaches are launched apart from the conventional SIM. Among the various SIM methods, some of the important techniques e.g. TIRF, non-linear, plasmonic, speckle SIM etc are discussed elaborately. Moreover, we highlight different implementations of SIM in various other imaging modalities to enhance their imaging performances with augmented capabilities. Finally, some future outlooks are mentioned which might develop fruitfully and pave the way for new discoveries in near future.

Structured illumination microscopy (SIM) is a fast and gentle super-resolution fluorescence imaging technique, featuring live-cell compatible excitation light levels and high imaging speeds. To achieve SIM, spatial modulation of the fluorescence excitation light is employed. This is typically achieved by interfering coherent laser beams in the sample plane, which are often created by spatial light modulators (SLMs). Digital micromirror devices (DMDs) are a form of SLMs with certain advantages, such as high speed, low cost and wide availability, which present certain hurdles in their implementation, mainly the blazed grating effect caused by the jagged surface structure of the tilted mirrors. Recent works have studied this effect through modelling, simulations and experiments, and laid out possible implementations of multi-color SIM imaging based on DMDs. Here, we present an implementation of a dual-color DMD based SIM microscope using temperature-controlled wavelength matching. By carefully controlling the output wavelength of a diode laser by temperature, we can tune two laser wavelengths in such a way that no opto-mechanical realignment of the SIM setup is necessary when switching between both wavelengths. This reduces system complexity and increases imaging speed. With measurements on nano-bead reference samples, as well as the actin skeleton and membrane of fixed U2OS cells, we demonstrate the capabilities of the setup.

Fluorescence imaging methods that achieve spatial resolution beyond the diffraction limit (super-resolution) are of great interest in biology. We describe a super-resolution method that combines two-photon excitation with structured illumination microscopy (SIM), enabling three-dimensional interrogation of live organisms with ~150 nm lateral and ~400 nm axial resolution, at frame rates of ~1 Hz. By performing optical rather than digital processing operations to improve resolution, our microscope permits super-resolution imaging with no additional cost in acquisition time or phototoxicity relative to the point-scanning two-photon microscope upon which it is based. Our method provides better depth penetration and inherent optical sectioning than all previously reported super-resolution SIM implementations, enabling super-resolution imaging at depths exceeding 100 μm from the coverslip surface. The capability of our system for interrogating thick live specimens at high resolution is demonstrated by imaging whole nematode embryos and larvae, and tissues and organs inside zebrafish embryos.

We present a volumetric imaging method for biological tissue that is free of mechanically scanning components. The optical sectioning in the system is obtained by structured illumination microscopy (SIM) with the depth of focus being varied by the use of an electronic tunable-focus lens (ETL). The performance of the axial scanning mechanism was evaluated and characterized in conjunction with SIM to ensure volumetric images could be recorded and reconstructed without significant losses in optical section thickness and lateral resolution over the full desired scan range. It was demonstrated that sub-cellular image resolutions were obtainable in both microsphere films and in ex vivo oral mucosa, spanning multiple cell layers, without significant losses in image quality. The mechanism proposed here has the ability to be integrated into any wide-field microscopy system to convert it into a three-dimensional imaging platform without the need for axial scanning of the sample or imaging optics. The ability to axially scan independent of mechanical movement also provides the opportunity for the development of endoscopic systems which can create volumetric images of tissue in vivo.

Because structured illumination microscopy (SIM) has the advantages of wide-field, rapid imaging, and biocompatibility, it is widely used for super-resolution imaging of living cells. Here, we demonstrate a new super-resolution imaging method—bulk plasmon polariton based SIM (BPPSIM), which combines the SIM with the hyperbolic metamaterials (HMMs). By utilizing an HMM composed of a multilayer metal/dielectric film, a deep subwavelength bulk plasmon polariton is obtained. The imaging resolution of BPPSIM can be improved by the uniform and wide-field structured illumination pattern with high spatial frequency, benefiting from the filtering effect of HMM for the spatial frequency spectrum. The resolution of the recovered images by BPPSIM has been increased to 1/8 of the fluorescence wavelength, which is 2.7-fold enhancement in resolution compared with traditional fluorescence microscopy. This proposed approach demonstrates the operability and flexibility of the structured illumination pattern and can be used in a simple, wide-field and super-resolution fluorescence microscope.

Structured illumination microscopy (SIM) is a widely used super resolution imaging technique that can down-modulate a sample's high-frequency information into objective recordable frequencies to enhance the resolution below the diffraction limit. However, classical SIM image reconstruction methods often generate poor results under low illumination conditions, which are required for reducing photobleaching and phototoxicity in cell imaging experiments. Although denoising methods or auxiliary items improved SIM image reconstruction in low signal level situations, they still suffer from decreased reconstruction quality and significant background artifacts, inevitably limiting their practical applications. In order to improve the reconstruction quality, second-order optimized regularized SIM (sorSIM) is designed specifically for image reconstruction in low signal level situations. In sorSIM, a second-order regularization term is introduced to suppress noise effect, and the penalty factor in this term is selected to optimize the resolution enhancement and noise resistance. Compared to classical SIM image reconstruction algorithms as well as to those previously used in low illumination cases, the proposed sorSIM provides images with enhanced resolution and fewer background artifacts. Therefore, sorSIM can be a potential tool for high-quality and rapid super resolution imaging, especially for low signal images.

Structured illumination microscopy (SIM) is an attractive choice for fast super-resolution imaging. The generation of structured illumination patterns made by interference of laser beams is broadly employed to obtain high modulation depth of patterns, while the polarizations of the laser beams must be elaborately controlled to guarantee the high contrast of interference intensity, which brings a more complex configuration for the polarization control. The emerging pattern projection strategy is much more compact, but the modulation depth of patterns is deteriorated by the optical transfer function (OTF) of the optical system, especially in high spatial frequency near diffraction limit. Therefore, the traditional super-resolution reconstruction algorithm for interference-based SIM will suffer from much artifact in the case of projection-based SIM that possesses a low modulation depth. Here, we propose an alternative reconstruction algorithm based on image recombination transform (IRT), which provides an alternative solution to address this problem even in a weak modulation depth. We demonstrated the effectiveness of this algorithm in the multicolor super-resolution imaging of BPAE cells in our developed projection-based SIM system, which applies a computer controlled digital micro-mirror device (DMD) for fast fringe generation and multicolor LEDs for illumination. The merit of the system incorporated with the proposed algorithm allows for a low excitation intensity fluorescence imaging even less than 1W/cm2, which is beneficial for the long-term, in vivo super-resolved imaging of live cells and tissues.

Structured illumination microscopy (SIM) has emerged as a promising super-resolution fluorescence imaging technique, offering diverse configurations and computational strategies to mitigate phototoxicity during real-time imaging of biological specimens. Traditional efforts to enhance system frame rates have concentrated on processing algorithms, like rolling reconstruction or reduced frame reconstruction, or on investments in costly sCMOS cameras with accelerated row readout rates. In this article, we introduce an approach to elevate SIM frame rates and region of interest (ROI) coverage at the hardware level, without necessitating an upsurge in camera expenses or intricate algorithms. Here, parallel acquisition-readout SIM (PAR-SIM) achieves the highest imaging speed for fluorescence imaging at currently available detector sensitivity. By using the full frame-width of the detector through synchronizing the pattern generation and image exposure-readout process, we have achieved a fundamentally stupendous information spatial-temporal flux of 132.9 MPixels · s−1, 9.6-fold that of the latest techniques, with the lowest SNR of −2.11 dB and 100 nm resolution. PAR-SIM demonstrates its proficiency in successfully reconstructing diverse cellular organelles in dual excitations, even under conditions of low signal due to ultra-short exposure times. Notably, mitochondrial dynamic tubulation and ongoing membrane fusion processes have been captured in live COS-7 cell, recorded with PAR-SIM at an impressive 408 Hz. We posit that this novel parallel exposure-readout mode not only augments SIM pattern modulation for superior frame rates but also holds the potential to benefit other complex imaging systems with a strategic controlling approach.

The super-resolution imaging technique of structured illumination microscopy (SIM) enables the mixing of high-frequency information into the optical transmission domain via light-source modulation, thus breaking the optical diffraction limit. Correlative SIM, which combines other techniques with SIM, offers more versatility or higher imaging resolution than traditional SIM. In this review, we first briefly introduce the imaging mechanism and development trends of conventional SIM. Then, the principles and recent developments of correlative SIM techniques are reviewed. Finally, the future development directions of SIM and its correlative microscopies are presented.

The varied functions of lipid droplets, which encompass the regulation of lipid and energy homeostasis, as well as their association with the occurrence of various metabolic diseases, are intricately linked to their dynamic properties. Super-resolution imaging techniques have emerged to decipher physiological processes and molecular mechanisms on the nanoscale. However, achieving long-term dynamic super-resolution imaging faces challenges due to the need for fluorescent probes with high photostability. This paper introduces LD-CF, a "buffering probe" for imaging lipid droplet dynamics using structured illumination microscopy (SIM). The polarity-sensitive LD-CF eliminates background fluorescence with a "cyan filter" strategy, enabling wash-free imaging of lipid droplets. In the fluorescent "off" state outside droplets, the probes act as a "buffering pool", replacing photobleached probes inside droplets and enabling photostable long-term SIM imaging. With this probe, three modes of lipid droplet fusion were observed, including the discovery of fusion from large to small lipid droplets. Fluorescence intensity tracking also revealed the direction of lipid transport during the lipid droplet fusion.

In traditional optical microscopy imaging system, the resolution of time mainly depends on the detector’s detection speed, usually in millisecond or microsecond magnitude. While the spatial resolution is limited by the optical diffraction limit, the lateral resolution of ordinary microscopies generally only reaches 200nm.Just as biological structure has a wide spatial scale, biological living processes also have a broad time scale. When observing biological subcellular organelles, resolution and the speed of life activities should be considered. For the dynamic process, it’s meaningless to simply improve the spatial resolution without correspondingly increasing the imaging speed which should be no less than the movement speed of the observed object. Existing super-resolution or high-speed optical imaging is limited by the mutual constraints of spatial and time resolution, making it difficult to obtain both super-resolution and high-speed optical imaging. In order to break the constraints of this game and gain high-speed super-resolution images, the CS-SIM system combines SIM (structured illumination microscopy) and CSP (compressed sensing photography). Since they both are wide filed imaging and CSP is a passive receiving imaging technology, SIM and CSP have potential to combine closely and achieve super-resolution and highspeed imaging.

Abstract: As an early component of modern super-resolution (SR) imaging technology, structured illumination microscopy (SIM) has been developed for nearly twenty years. With up to ~60 nm and 564 Hz frame rate, it has achieved an optimal combination of spatiotemporal resolution in live cells recently. Despite these advantages, SIM also suffers disadvantages, some of which originated from the intrinsic reconstruction process. Here we review recent technical advances in SIM, including SR reconstruction, performance evaluation, and its integration with other technologies to provide a practical guide for biologists.