Cusp-artifacts in high order superresolution optical fluctuation imaging

3D super-resolution optical fluctuation imaging with temporal focusing two-photon excitation

3D super-resolution fluorescence microscopy typically requires sophisticated setups, sample preparation, or long measurements. A notable exception, SOFI, only requires recording a sequence of frames and no hardware modifications whatsoever but being a wide-field method, it faces problems in thick, dense samples. We combine SOFI with temporal focusing two-photon excitation - the wide-field method that is capable of exciting a thin slice in 3D volume. Temporal focusing is simple to implement whenever the excitation path of the microscope can be accessed. The implementation of SOFI is straightforward. By merging these two methods, we obtain super-resolved 3D images of neurons stained with quantum dots. Our approach offers reduced bleaching of out-of-focus fluorescent probes and an improved signal-to-background ratio that can be used when robust resolution improvement is required in thick, dense samples.

Video-rate 3D imaging of living cells using Fourier view-channel-depth light field microscopy

Interrogation of subcellular biological dynamics occurring in a living cell often requires noninvasive imaging of the fragile cell with high spatiotemporal resolution across all three dimensions. It thereby poses big challenges to modern fluorescence microscopy implementations because the limited photon budget in a live-cell imaging task makes the achievable performance of conventional microscopy approaches compromise between their spatial resolution, volumetric imaging speed, and phototoxicity. Here, we incorporate a two-stage view-channel-depth (VCD) deep-learning reconstruction strategy with a Fourier light-field microscope based on diffractive optical element to realize fast 3D super-resolution reconstructions of intracellular dynamics from single diffraction-limited 2D light-filed measurements. This VCD-enabled Fourier light-filed imaging approach (F-VCD), achieves video-rate (50 volumes per second) 3D imaging of intracellular dynamics at a high spatiotemporal resolution of ~180 nm × 180 nm × 400 nm and strong noise-resistant capability, with which light field images with a signal-to-noise ratio (SNR) down to -1.62 dB could be well reconstructed. With this approach, we successfully demonstrate the 4D imaging of intracellular organelle dynamics, e.g., mitochondria fission and fusion, with ~5000 times of observation.

Fluorescence fluctuation based super resolution microscopy, basic concepts for an easy start

Due to the wave nature of light, optical microscopy has a lower-bound lateral resolution limit of approximately half of the wavelength of visible light, i.e., within the range of 200 to 350 nm. Fluorescence Fluctuation based Super Resolution Microscopy (FF-SRM) is a term used to encompass a collection of image analysis techniques which rely on the statistical processing of temporal variations of the fluorescence signal. FF-SRM aims to reduce the uncertainty of the location of fluorophores within an image, often improving spatial resolution to several tens of nanometers. FF-SRM is suitable for live-cell imaging due to its compatibility with most fluorescent probes and relatively simple instrumental and experimental requirements, which are mostly camera-based epifluorescence instruments. Each FF-SRM approach has strengths and weaknesses, which depend directly on the underlying statistical principles through which enhanced spatial resolution is achieved. In this review, the basic concepts and principles behind a range of FF-SRM methods published to date are described. Their operational parameters are explained and guidance for its selection is provided. This article is protected by copyright. All rights reserved.

PySOFI: an open source Python package for SOFI

Super-resolution optical fluctuation imaging (SOFI) is a highly democratizable technique that provides optical super-resolution without requirement of sophisticated imaging instruments. Easy-to-use open-source packages for SOFI are important to support the utilization and community adoption of the SOFI method, they also encourage the participation and further development of SOFI by new investigators. In this work, we developed PySOFI, an open-source Python package for SOFI analysis that offers the flexibility to inspect, test, modify, improve, and extend the algorithm. We provide complete documentation for the package and a collection of Jupyter Notebooks to demonstrate the usage of the package. We discuss the architecture of PySOFI and illustrate how to use each functional module. A demonstration on how to extend the PySOFI package with additional modules is also included in the PySOFI package. We expect PySOFI to facilitate efficient adoption, testing, modification, dissemination, and prototyping of new SOFI-relevant algorithms.

Design of experiments for the optimization of SOFI super-resolution microscopy imaging

Super-resolution optical fluctuation imaging (SOFI) is a well-known super-resolution technique appreciated for its versatility and broad applicability. However, even though an extended theoretical description is available, it is still not fully understood how the interplay between different experimental parameters influences the quality of a SOFI image. We investigated the relationship between five experimental parameters (measurement time, on-time t _on, off-time t _off, probe brightness, and out of focus background) and the quality of the super-resolved images they yielded, expressed as Signal to Noise Ratio (SNR). Empirical relationships were modeled for second- and third-order SOFI using data simulated according to a D-Optimal design of experiments, which is an ad-hoc design built to reduce the experimental load when the total number of trials to be conducted becomes too high for practical applications. This approach proves to be more reliable and efficient for parameter optimization compared to the more classical parameter by parameter approach. Our results indicate that the best image quality is achieved for the fastest emitter blinking (lowest t _on and t _off), lowest background level, and the highest measurement duration, while the brightness variation does not affect the quality in a statistically significant way within the investigated range. However, when the ranges spanned by the parameters are constrained, a different set of optimal conditions may arise. For example, for second-order SOFI, we identified situations in which the increase of t _off can be beneficial to SNR, such as when the measurement duration is long enough. In general, optimal values of t _on and t _off have been found to be highly dependent from each other and from the measurement duration.

Active-modulated, random-illumination, super-resolution optical fluctuation imaging

Super-resolution optical fluctuation imaging (SOFI) provides subdiffraction resolution based on the analysis of temporal stochastic intensity fluctuations. However, conventional SOFI imaging relies on the intrinsic blinking properties of fluorescent markers and suffers from severe artifacts and signal losses owing to the unmatched blinking on-time ratio. Herein, we propose active-modulated, random-illumination, super-resolution optical fluctuation imaging that allows the traditional SOFI to overcome the effect of the intrinsic impertinent blinking characteristic of fluorescent markers. We demonstrate theoretically and experimentally that this method of active-modulated random illumination can generate random illumination patterns with a controllable blinking on-time ratio to match the high-order SOFI reconstruction considerably reducing the generated artifacts and signal losses. High-order, high-quality images can be obtained with increased lateral resolution.

Self-Blinking Dyes Unlock High-Order and Multiplane Super-Resolution Optical Fluctuation Imaging

Most diffraction-unlimited super-resolution imaging critically depends on the switching of fluorophores between at least two states, often induced using intense laser light and specialized buffers or UV radiation. Recently, so-called self-blinking dyes that switch spontaneously between an open, fluorescent "on" state and a closed, colorless "off" state were introduced. Here, we exploit the synergy between super-resolution optical fluctuation imaging (SOFI) and spontaneously switching fluorophores for 2D and 3D imaging. SOFI analyzes higher order statistics of fluctuations in the fluorophore emission instead of localizing individual molecules. It thereby tolerates a broad range of labeling densities, switching behavior, and probe brightness. Thus, even dyes that exhibit spontaneous blinking characteristics that are not suitable or suboptimal for single molecule localization microscopy can be used successfully for SOFI-based super-resolution imaging. We demonstrate 2D imaging of fixed cells with almost uniform resolution up to 50-60 nm in 6th order SOFI and characterize changing experimental conditions. Next, we investigate volumetric imaging using biplane and eight-plane data acquisition. We extend 3D cross-cumulant analysis to 4th order, achieving super-resolution in 3D with up to 29 depth planes. Finally, the low laser excitation intensities needed for single and biplane self-blinking SOFI are well suited for live-cell imaging. We show the perspective for time-resolved imaging by observing slow membrane movements in cells. Self-blinking SOFI thus provides a more robust alternative route for easy-to-use 2D and 3D high-resolution imaging.

25th Anniversary of STED Microscopy and the 20th Anniversary of SIM: feature introduction

This feature issue commemorating 25 years of STED microscopy and 20 years of SIM is intended to highlight the incredible progress and growth in the field of superresolution microscopy since Stefan Hell and Jan Wichmann published the article Breaking the diffraction resolution limit by stimulated emission: stimulated-emission-depletion fluorescence microscopy in Optics Letters in 1994.