scholarly journals GPU-accelerated real-time reconstruction in Python of three-dimensional datasets from structured illumination microscopy with hexagonal patterns

2021 ◽  
Vol 379 (2199) ◽  
Author(s):  
Hai Gong ◽  
Wenjun Guo ◽  
Mark A. A. Neil
Keyword(s):  
Moving Objects ◽  
Three Dimensional ◽  
Simulated Data ◽  
Super Resolution ◽  
Light Sheet ◽  
Processing Unit ◽  
Structured Illumination ◽  
Reconstruction Algorithms ◽  
Structured Illumination Microscopy ◽  
Axially Moving

We present a structured illumination microscopy system that projects a hexagonal pattern by the interference among three coherent beams, suitable for implementation in a light-sheet geometry. Seven images acquired as the illumination pattern is shifted laterally can be processed to produce a super-resolved image that surpasses the diffraction-limited resolution by a factor of over 2 in an exemplar light-sheet arrangement. Three methods of processing data are discussed depending on whether the raw images are available in groups of seven, individually in a stream or as a larger batch representing a three-dimensional stack. We show that imaging axially moving samples can introduce artefacts, visible as fine structures in the processed images. However, these artefacts are easily removed by a filtering operation carried out as part of the batch processing algorithm for three-dimensional stacks. The reconstruction algorithms implemented in Python include specific optimizations for calculation on a graphics processing unit and we demonstrate its operation on experimental data of static objects and on simulated data of moving objects. We show that the software can process over 239 input raw frames per second at 512 × 512 pixels, generating over 34 super-resolved frames per second at 1024 × 1024 pixels. This article is part of the Theo Murphy meeting issue ‘Super-resolution structured illumination microscopy (part 1)’.

scholarly journals Super-Resolution Imaging by Dual Iterative Structured Illumination Microscopy

2021 ◽  
Author(s):  
Anna Loeschberger ◽  
Yauheni Novikau ◽  
Ralf Netz ◽  
Marie-Christin Spindler ◽  
Ricardo Benavente ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Brain Slices ◽  
Super Resolution ◽  
Reconstruction Algorithm ◽  
Living Cells ◽  
Structured Illumination ◽  
Structured Illumination Microscopy ◽  
Spatiotemporal Resolution ◽  
Coated Pits ◽  
Resolution Imaging

Three-dimensional (3D) multicolor super-resolution imaging in the 50-100 nm range in fixed and living cells remains challenging. We extend the resolution of structured illumination microscopy (SIM) by an improved nonlinear iterative reconstruction algorithm that enables 3D multicolor imaging with improved spatiotemporal resolution at low illumination intensities. We demonstrate the performance of dual iterative SIM (diSIM) imaging cellular structures in fixed cells including synaptonemal complexes, clathrin coated pits and the actin cytoskeleton with lateral resolutions of 60-100 nm with standard fluorophores. Furthermore, we visualize dendritic spines in 70 micrometer thick brain slices with an axial resolution < 200 nm. Finally, we image dynamics of the endoplasmatic reticulum and microtubules in living cells with up to 255 frames/s.

scholarly journals High-speed multiplane structured illumination microscopy of living cells using an image-splitting prism

Nanophotonics ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 143-148
Author(s):  
Adrien Descloux ◽  
Marcel Müller ◽  
Vytautas Navikas ◽  
Andreas Markwirth ◽  
Robin van den Eynde ◽  
...  
Keyword(s):  
High Speed ◽  
Three Dimensional ◽  
Super Resolution ◽  
Optical Element ◽  
Spatial Light Modulators ◽  
Structured Illumination ◽  
Structured Illumination Microscopy ◽  
Image Stack ◽  
Light Modulators ◽  
3D Information

AbstractSuper-resolution structured illumination microscopy (SR-SIM) can be conducted at video-rate acquisition speeds when combined with high-speed spatial light modulators and sCMOS cameras, rendering it particularly suitable for live-cell imaging. If, however, three-dimensional (3D) information is desired, the sequential acquisition of vertical image stacks employed by current setups significantly slows down the acquisition process. In this work, we present a multiplane approach to SR-SIM that overcomes this slowdown via the simultaneous acquisition of multiple object planes, employing a recently introduced multiplane image splitting prism combined with high-speed SIM illumination. This strategy requires only the introduction of a single optical element and the addition of a second camera to acquire a laterally highly resolved 3D image stack. We demonstrate the performance of multiplane SIM by applying this instrument to imaging the dynamics of mitochondria in living COS-7 cells.

scholarly journals Extending resolution of structured illumination microscopy with sparse deconvolution

2021 ◽  
Author(s):  
Weisong Zhao ◽  
Shiqun Zhao ◽  
Liuju Li ◽  
Xiaoshuai Huang ◽  
Shijia Xing ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Three Dimensional ◽  
Super Resolution ◽  
Live Cell ◽  
Frame Rate ◽  
Live Cells ◽  
Photon Flux ◽  
Structured Illumination ◽  
Structured Illumination Microscopy ◽  
Spatiotemporal Resolution

Abstract The spatial resolutions of live-cell super-resolution microscopes are limited by the maximum collected photon flux. Taking advantage of a priori knowledge of the sparsity and continuity of biological structures, we develop a deconvolution algorithm that further extends the resolution of super-resolution microscopes under the same photon budgets by nearly twofold. As a result, sparse structured illumination microscopy (Sparse-SIM) achieves ~60 nm resolution at a 564 Hz frame rate, allowing it to resolve intricate structural intermediates, including small vesicular fusion pores, ring-shaped nuclear pores formed by different nucleoporins, and relative movements between the inner and outer membranes of mitochondria in live cells. Likewise, sparse deconvolution can be used to increase the three-dimensional resolution and contrast of spinning-disc confocal-based SIM (SD-SIM), and operates under conditions with the insufficient signal-to-noise-ratio, all of which allows routine four-color, three-dimensional, ~90 nm resolution live-cell super-resolution imaging. Overall, sparse deconvolution may be a general tool to push the spatiotemporal resolution limits of live-cell fluorescence microscopy.

scholarly journals A polymer gel index-matched to water enables diverse applications in fluorescence microscopy

2020 ◽  
Author(s):  
Xiaofei Han ◽  
Yijun Su ◽  
Hamilton White ◽  
Kate M. O’Neill ◽  
Nicole Y. Morgan ◽  
...  
Keyword(s):  
Surface Passivation ◽  
Super Resolution ◽  
Light Sheet ◽  
Polymer Gel ◽  
Structured Illumination ◽  
Structured Illumination Microscopy ◽  
Neural Structure ◽  
Uv Curable ◽  
Isotropic Resolution ◽  
Light Sheet Microscopy

AbstractWe demonstrate diffraction-limited and super-resolution imaging through thick layers (tens-hundreds of microns) of BIO-133, a biocompatible, UV-curable, commercially available polymer with a refractive index (RI) matched to water. We show that cells can be directly grown on BIO-133 substrates without the need for surface passivation and use this capability to perform extended time-lapse volumetric imaging of cellular dynamics 1) at isotropic resolution using dual-view light-sheet microscopy, and 2) at super-resolution using instant structured illumination microscopy. BIO-133 also enables immobilization of 1) Drosophila tissue, allowing us to track membrane puncta in pioneer neurons, and 2) Caenorhabditis elegans, which allows us to image and inspect fine neural structure and to track pan-neuronal calcium activity over hundreds of volumes. Finally, BIO-133 is compatible with other microfluidic materials, enabling optical and chemical perturbation of immobilized samples, as we demonstrate by performing drug and optogenetic stimulation on cells and C. elegans.

scholarly journals A quantitative super-resolution imaging toolbox for diagnosis of motile ciliopathies

2020 ◽  
Vol 12 (535) ◽  
pp. eaay0071 ◽  
Author(s):  
Zhen Liu ◽  
Quynh P. H. Nguyen ◽  
Qingxu Guan ◽  
Alexandra Albulescu ◽  
Lauren Erdman ◽  
...  
Keyword(s):  
Lung Function ◽  
A Priori ◽  
Three Dimensional ◽  
Super Resolution ◽  
Structural Defects ◽  
Structured Illumination ◽  
Structured Illumination Microscopy ◽  
Stochastic Optical Reconstruction Microscopy ◽  
Motile Cilia ◽  
Optical Reconstruction

Airway clearance of pathogens and particulates relies on motile cilia. Impaired cilia motility can lead to reduction in lung function, lung transplant, or death in some cases. More than 50 proteins regulating cilia motility are linked to primary ciliary dyskinesia (PCD), a heterogeneous, mainly recessive genetic lung disease. Accurate PCD molecular diagnosis is essential for identifying therapeutic targets and for initiating therapies that can stabilize lung function, thereby reducing socioeconomic impact of the disease. To date, PCD diagnosis has mainly relied on nonquantitative methods that have limited sensitivity or require a priori knowledge of the genes involved. Here, we developed a quantitative super-resolution microscopy workflow: (i) to increase sensitivity and throughput, (ii) to detect structural defects in PCD patients’ cells, and (iii) to quantify motility defects caused by yet to be found PCD genes. Toward these goals, we built a localization map of PCD proteins by three-dimensional structured illumination microscopy and implemented quantitative image analysis and machine learning to detect protein mislocalization, we analyzed axonemal structure by stochastic optical reconstruction microscopy, and we developed a high-throughput method for detecting motile cilia uncoordination by rotational polarity. Together, our data show that super-resolution methods are powerful tools for improving diagnosis of motile ciliopathies.

scholarly journals Extended mechanical force measurements using structured illumination microscopy

2021 ◽  
Vol 379 (2199) ◽  
Author(s):  
Kseniya Korobchevskaya ◽  
Huw Colin-York ◽  
Liliana Barbieri ◽  
Marco Fritzsche
Keyword(s):  
Imaging System ◽  
Three Dimensional ◽  
Traction Force ◽  
Super Resolution ◽  
Mechanical Force ◽  
Structured Illumination ◽  
Structured Illumination Microscopy ◽  
Biological Studies ◽  
Wide Range ◽  
Spatio Temporal

Quantifying cell generated mechanical forces is key to furthering our understanding of mechanobiology. Traction force microscopy (TFM) is one of the most broadly applied force probing technologies, but its sensitivity is strictly dependent on the spatio-temporal resolution of the underlying imaging system. In previous works, it was demonstrated that increased sampling densities of cell derived forces permitted by super-resolution fluorescence imaging enhanced the sensitivity of the TFM method. However, these recent advances to TFM based on super-resolution techniques were limited to slow acquisition speeds and high illumination powers. Here, we present three novel TFM approaches that, in combination with total internal reflection, structured illumination microscopy and astigmatism, improve the spatial and temporal performance in either two-dimensional or three-dimensional mechanical force quantification, while maintaining low illumination powers. These three techniques can be straightforwardly implemented on a single optical set-up offering a powerful platform to provide new insights into the physiological force generation in a wide range of biological studies. This article is part of the Theo Murphy meeting issue ‘Super-resolution structured illumination microscopy (part 1)'.

Live, Video-Rate Super-Resolution Microscopy Using Structured Illumination and Rapid GPU-Based Parallel Processing

2011 ◽  
Vol 17 (2) ◽  
pp. 191-196 ◽  
Author(s):  
Jonathan Lefman ◽  
Keana Scott ◽  
Stephan Stranick
Keyword(s):  
Parallel Processing ◽  
Real Time ◽  
Super Resolution ◽  
Fold Increase ◽  
Frame Rate ◽  
Processing Unit ◽  
Structured Illumination ◽  
Structured Illumination Microscopy ◽  
Multiprocessor Computer ◽  
Computational Overhead

AbstractStructured illumination fluorescence microscopy is a powerful super-resolution method that is capable of achieving a resolution below 100 nm. Each super-resolution image is computationally constructed from a set of differentially illuminated images. However, real-time application of structured illumination microscopy (SIM) has generally been limited due to the computational overhead needed to generate super-resolution images. Here, we have developed a real-time SIM system that incorporates graphic processing unit (GPU) based in-line parallel processing of raw/differentially illuminated images. By using GPU processing, the system has achieved a 90-fold increase in processing speed compared to performing equivalent operations on a multiprocessor computer—the total throughput of the system is limited by data acquisition speed, but not by image processing. Overall, more than 350 raw images (16-bit depth, 512 × 512 pixels) can be processed per second, resulting in a maximum frame rate of 39 super-resolution images per second. This ultrafast processing capability is used to provide immediate feedback of super-resolution images for real-time display. These developments are increasing the potential for sophisticated super-resolution imaging applications.

scholarly journals SIMcheck: a Toolbox for Successful Super-resolution Structured Illumination Microscopy

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Graeme Ball ◽  
Justin Demmerle ◽  
Rainer Kaufmann ◽  
Ilan Davis ◽  
Ian M. Dobbie ◽  
...  
Keyword(s):  
Cell Biology ◽  
Three Dimensional ◽  
Super Resolution ◽  
Quality Data ◽  
Structured Illumination ◽  
Structured Illumination Microscopy ◽  
High Quality Data ◽  
Accessible Method ◽  
Objective Control ◽  
Common Problems

Abstract Three-dimensional structured illumination microscopy (3D-SIM) is a versatile and accessible method for super-resolution fluorescence imaging, but generating high-quality data is challenging, particularly for non-specialist users. We present SIMcheck, a suite of ImageJ plugins enabling users to identify and avoid common problems with 3D-SIM data and assess resolution and data quality through objective control parameters. Additionally, SIMcheck provides advanced calibration tools and utilities for common image processing tasks. This open-source software is applicable to all commercial and custom platforms and will promote routine application of super-resolution SIM imaging in cell biology.

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