Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Structured illumination imaging with quasi-periodic patterns.

ABSTRACT: Structured illumination microscopy (SIM) is a well-established method for optical sectioning and super-resolution. The core of structured illumination is using a periodic pattern to excite image signals. This work reports a method for estimating minor pattern distortions from the raw image data and correcting these distortions during SIM image processing. The method was tested with both simulated and experimental image data from two-photon Bessel light-sheet SIM. The results proves the method is effective in challenging situations, where strong scattering background exists, signal-to-noise ratio (SNR) is low and the sample structure is sparse. Experimental results demonstrate restoring synaptic structures in deep brain tissue, despite the presence of strong light scattering and tissue-induced SIM pattern distortion.

SUBMITTER: Xu D

PROVIDER: S-EPMC9990472 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Structured illumination imaging with quasi-periodic patterns.

Xu Dongli D Ding Jun J Peng Leilei L

Journal of biophotonics 20200318 6

Structured illumination microscopy (SIM) is a well-established method for optical sectioning and super-resolution. The core of structured illumination is using a periodic pattern to excite image signals. This work reports a method for estimating minor pattern distortions from the raw image data and correcting these distortions during SIM image processing. The method was tested with both simulated and experimental image data from two-photon Bessel light-sheet SIM. The results proves the method is ...[more]

PMID: 32101369

Similar Datasets

Acoustical structured illumination for super-resolution ultrasound imaging.

Project description:Structured illumination microscopy is an optical method to increase the spatial resolution of wide-field fluorescence imaging beyond the diffraction limit by applying a spatially structured illumination light. Here, we extend this concept to facilitate super-resolution ultrasound imaging by manipulating the transmitted sound field to encode the high spatial frequencies into the observed image through aliasing. Post processing is applied to precisely shift the spectral components to their proper positions in k-space and effectively double the spatial resolution of the reconstructed image compared to one-way focusing. The method has broad application, including the detection of small lesions for early cancer diagnosis, improving the detection of the borders of organs and tumors, and enhancing visualization of vascular features. The method can be implemented with conventional ultrasound systems, without the need for additional components. The resulting image enhancement is demonstrated with both test objects and ex vivo rat metacarpals and phalanges.

| S-EPMC5988254 | biostudies-literature

Measuring light transport properties using speckle patterns as structured illumination.

Project description:The measurement of light absorption and scattering properties of biological materials has several diagnostic and therapeutic applications. We can measure these properties for skin without contact using structured illumination and imaging. However, building simple handheld devices remains challenging due to motion artefacts and moving targets. To overcome this limitation, we project random speckle patterns instead of discrete spatial frequencies on the target. Since random patterns are spatially broadband, they capture more information per image, enabling frame-by-frame analysis. In this paper, we describe the statistics of objective speckles and demonstrate how the optical system is designed for spatially bandlimited illumination. Next, we use a diverse set of liquid tissue phantom to validate the method. We successfully demonstrate that a calibrated instrument can independently predict the two primary light transport properties of a homogeneous turbid system. This work is a starting point for analysing skin and other heterogeneous biological media in the future.

| S-EPMC6672017 | biostudies-literature

ADVANCED IMAGING. Extended-resolution structured illumination imaging of endocytic and cytoskeletal dynamics.

Project description:Super-resolution fluorescence microscopy is distinct among nanoscale imaging tools in its ability to image protein dynamics in living cells. Structured illumination microscopy (SIM) stands out in this regard because of its high speed and low illumination intensities, but typically offers only a twofold resolution gain. We extended the resolution of live-cell SIM through two approaches: ultrahigh numerical aperture SIM at 84-nanometer lateral resolution for more than 100 multicolor frames, and nonlinear SIM with patterned activation at 45- to 62-nanometer resolution for approximately 20 to 40 frames. We applied these approaches to image dynamics near the plasma membrane of spatially resolved assemblies of clathrin and caveolin, Rab5a in early endosomes, and α-actinin, often in relationship to cortical actin. In addition, we examined mitochondria, actin, and the Golgi apparatus dynamics in three dimensions.

| S-EPMC4659358 | biostudies-literature

Quasi-periodic patterns contribute to functional connectivity in the brain.

Project description:Functional connectivity is widely used to study the coordination of activity between brain regions over time. Functional connectivity in the default mode and task positive networks is particularly important for normal brain function. However, the processes that give rise to functional connectivity in the brain are not fully understood. It has been postulated that low-frequency neural activity plays a key role in establishing the functional architecture of the brain. Quasi-periodic patterns (QPPs) are a reliably observable form of low-frequency neural activity that involve the default mode and task positive networks. Here, QPPs from resting-state and working memory task-performing individuals were acquired. The spatiotemporal pattern, strength, and frequency of the QPPs between the two groups were compared and the contribution of QPPs to functional connectivity in the brain was measured. In task-performing individuals, the spatiotemporal pattern of the QPP changes, particularly in task-relevant regions, and the QPP tends to occur with greater strength and frequency. Differences in the QPPs between the two groups could partially account for the variance in functional connectivity between resting-state and task-performing individuals. The QPPs contribute strongly to connectivity in the default mode and task positive networks and to the strength of anti-correlation seen between the two networks. Many of the connections affected by QPPs are also disrupted during several neurological disorders. These findings contribute to understanding the dynamic neural processes that give rise to functional connectivity in the brain and how they may be disrupted during disease.

| S-EPMC6440826 | biostudies-literature

Multifocus structured illumination microscopy for fast volumetric super-resolution imaging.

Project description:We here report for the first time the synergistic implementation of structured illumination microscopy (SIM) and multifocus microscopy (MFM). This imaging modality is designed to alleviate the problem of insufficient volumetric acquisition speed in super-resolution biological imaging. SIM is a wide-field super-resolution technique that allows imaging with visible light beyond the classical diffraction limit. Employing multifocus diffractive optics we obtain simultaneous wide-field 3D imaging capability in the SIM acquisition sequence, improving volumetric acquisition speed by an order of magnitude. Imaging performance is demonstrated on biological specimens.

| S-EPMC5611928 | biostudies-literature

Dynamic super-resolution structured illumination imaging in the living brain.

Project description:Cells in the brain act as components of extended networks. Therefore, to understand neurobiological processes in a physiological context, it is essential to study them in vivo. Super-resolution microscopy has spatial resolution beyond the diffraction limit, thus promising to provide structural and functional insights that are not accessible with conventional microscopy. However, to apply it to in vivo brain imaging, we must address the challenges of 3D imaging in an optically heterogeneous tissue that is constantly in motion. We optimized image acquisition and reconstruction to combat sample motion and applied adaptive optics to correcting sample-induced optical aberrations in super-resolution structured illumination microscopy (SIM) in vivo. We imaged the brains of live zebrafish larvae and mice and observed the dynamics of dendrites and dendritic spines at nanoscale resolution.

| S-EPMC6511017 | biostudies-literature

Super-Resolution Imaging of Neuronal Structures with Structured Illumination Microscopy.

Project description:Super-resolution structured illumination microscopy (SR-SIM) is an optical fluorescence microscopy method which is suitable for imaging a wide variety of cells and tissues in biological and biomedical research. Typically, SIM methods use high spatial frequency illumination patterns generated by laser interference. This approach provides high resolution but is limited to thin samples such as cultured cells. Using a different strategy for processing raw data and coarser illumination patterns, we imaged through a 150-micrometer-thick coronal section of a mouse brain expressing GFP in a subset of neurons. The resolution reached 144 nm, an improvement of 1.7-fold beyond conventional widefield imaging.

| S-EPMC10525192 | biostudies-literature

Microwave imaging of quasi-periodic pulsations at flare current sheet.

Project description:Quasi-periodic pulsations (QPPs) are frequently detected in solar and stellar flares, but the underlying physical mechanisms are still to be ascertained. Here, we show microwave QPPs during a solar flare originating from quasi-periodic magnetic reconnection at the flare current sheet. They appear as two vertically detached but closely related sources with the brighter ones located at flare loops and the weaker ones along the stretched current sheet. Although the brightness temperatures of the two microwave sources differ greatly, they vary in phase with periods of about 10-20 s and 30-60 s. The gyrosynchrotron-dominated microwave spectra also present a quasi-periodic soft-hard-soft evolution. These results suggest that relevant high-energy electrons are accelerated by quasi-periodic reconnection, likely arising from the modulation of magnetic islands within the current sheet as validated by a 2.5-dimensional magnetohydrodynamic simulation.

| S-EPMC9744830 | biostudies-literature

Multiplexed structured illumination super-resolution imaging with lifetime-engineered upconversion nanoparticles.

Project description:The emerging optical multiplexing within nanoscale shows super-capacity in encoding information by using lifetime fingerprints from luminescent nanoparticles. However, the optical diffraction limit compromises the decoding accuracy and throughput of the nanoparticles during conventional widefield imaging. This, in turn, challenges the quality of nanoparticles to afford the modulated excitation condition and further retain the multiplexed optical fingerprints for super-resolution multiplexing. Here we report a tailor-made multiplexed super-resolution imaging method using the lifetime-engineered upconversion nanoparticles. We demonstrate that the nanoparticles are bright, uniform, and stable under structured illumination, which supports a lateral resolution of 185 nm, less than 1/4th of the excitation wavelength. We further develop a deep learning algorithm to coordinate with super-resolution images for more accurate decoding compared to a numeric algorithm. We demonstrate a three-channel super-resolution imaging based optical multiplexing with decoding accuracies above 93% for each channel and larger than 60% accuracy for potential seven-channel multiplexing. The improved resolution provides high throughput by resolving the particles within the diffraction-limited spots, which enables higher multiplexing capacity in space. This lifetime multiplexing super-resolution method opens a new horizon for handling the growing amount of information content, disease source, and security risk in modern society.

| S-EPMC9419758 | biostudies-literature

Machine learning assisted interferometric structured illumination microscopy for dynamic biological imaging.

Project description:Structured Illumination Microscopy, SIM, is one of the most powerful optical imaging methods available to visualize biological environments at subcellular resolution. Its limitations stem from a difficulty of imaging in multiple color channels at once, which reduces imaging speed. Furthermore, there is substantial experimental complexity in setting up SIM systems, preventing a widespread adoption. Here, we present Machine-learning Assisted, Interferometric Structured Illumination Microscopy, MAI-SIM, as an easy-to-implement method for live cell super-resolution imaging at high speed and in multiple colors. The instrument is based on an interferometer design in which illumination patterns are generated, rotated, and stepped in phase through movement of a single galvanometric mirror element. The design is robust, flexible, and works for all wavelengths. We complement the unique properties of the microscope with an open source machine-learning toolbox that permits real-time reconstructions to be performed, providing instant visualization of super-resolved images from live biological samples.

| S-EPMC9772218 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data