Browse
Submit Data
Databases
API
Help

Dataset Information

10 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Characterization of an industry-grade CMOS camera well suited for single molecule localization microscopy - high performance super-resolution at low cost.

ABSTRACT: Many commercial as well as custom-built fluorescence microscopes use scientific-grade cameras that represent a substantial share of the instrument's cost. This holds particularly true for super-resolution localization microscopy where high demands are placed especially on the detector with respect to sensitivity, noise, and also image acquisition speed. Here, we present and carefully characterize an industry-grade CMOS camera as a cost-efficient alternative to commonly used scientific cameras. Direct experimental comparison of these two detector types shows widely similar performance for imaging by single molecule localization microscopy (SMLM). Furthermore, high image acquisition speeds are demonstrated for the CMOS detector by ultra-fast SMLM imaging.

SUBMITTER: Diekmann R

PROVIDER: S-EPMC5663701 | biostudies-other | 2017 Oct

REPOSITORIES: biostudies-other

ACCESS DATA

Json Xml

Publications

Characterization of an industry-grade CMOS camera well suited for single molecule localization microscopy - high performance super-resolution at low cost.

Diekmann Robin R Till Katharina K Müller Marcel M Simonis Matthias M Schüttpelz Mark M Huser Thomas T

Scientific reports 20171031 1

Many commercial as well as custom-built fluorescence microscopes use scientific-grade cameras that represent a substantial share of the instrument's cost. This holds particularly true for super-resolution localization microscopy where high demands are placed especially on the detector with respect to sensitivity, noise, and also image acquisition speed. Here, we present and carefully characterize an industry-grade CMOS camera as a cost-efficient alternative to commonly used scientific cameras. D ...[more]

PMID: 29089524

Similar Datasets

Multiplane and Spectrally-Resolved Single Molecule Localization Microscopy with Industrial Grade CMOS cameras.

Project description:This work explores the use of industrial grade CMOS cameras for single molecule localization microscopy (SMLM). We show that industrial grade CMOS cameras approach the performance of scientific grade CMOS cameras at a fraction of the cost. This makes it more economically feasible to construct high-performance imaging systems with multiple cameras that are capable of a diversity of applications. In particular we demonstrate the use of industrial CMOS cameras for biplane, multiplane and spectrally resolved SMLM. We also provide open-source software for simultaneous control of multiple CMOS cameras and for the reduction of the movies that are acquired to super-resolution images.

| S-EPMC5789017 | biostudies-literature

Color-Coded Super-Resolution Small-Molecule Imaging.

Project description:Although the development of super-resolution microscopy dates back to 1994, its applications have been primarily focused on visualizing cellular structures and targets, including proteins, DNA and sugars. We now report on a system that allows both monitoring of the localization of exogenous small molecules in live cells at low resolution and subsequent super-resolution imaging by using stochastic optical reconstruction microscopy (STORM) on fixed cells. This represents a powerful new tool to understand the dynamics of subcellular trafficking associated with the mode and mechanism of action of exogenous small molecules.

| S-EPMC5291120 | biostudies-literature

Quantum correlation enhanced super-resolution localization microscopy enabled by a fibre bundle camera.

Project description:Despite advances in low-light-level detection, single-photon methods such as photon correlation have rarely been used in the context of imaging. The few demonstrations, for example of subdiffraction-limited imaging utilizing quantum statistics of photons, have remained in the realm of proof-of-principle demonstrations. This is primarily due to a combination of low values of fill factors, quantum efficiencies, frame rates and signal-to-noise characteristic of most available single-photon sensitive imaging detectors. Here we describe an imaging device based on a fibre bundle coupled to single-photon avalanche detectors that combines a large fill factor, a high quantum efficiency, a low noise and scalable architecture. Our device enables localization-based super-resolution microscopy in a non-sparse non-stationary scene, utilizing information on the number of active emitters, as gathered from non-classical photon statistics.

| S-EPMC5355801 | biostudies-literature

Minimizing Structural Bias in Single-Molecule Super-Resolution Microscopy.

Project description:Single-molecule localization microscopy (SMLM) depends on sequential detection and localization of individual molecular blinking events. Due to the stochasticity of single-molecule blinking and the desire to improve SMLM's temporal resolution, algorithms capable of analyzing frames with a high density (HD) of active molecules, or molecules whose images overlap, are a prerequisite for accurate location measurements. Thus far, HD algorithms are evaluated using scalar metrics, such as root-mean-square error, that fail to quantify the structure of errors caused by the structure of the sample. Here, we show that the spatial distribution of localization errors within super-resolved images of biological structures are vectorial in nature, leading to systematic structural biases that severely degrade image resolution. We further demonstrate that the shape of the microscope's point-spread function (PSF) fundamentally affects the characteristics of imaging artifacts. We built a Robust Statistical Estimation algorithm (RoSE) to minimize these biases for arbitrary structures and PSFs. RoSE accomplishes this minimization by estimating the likelihood of blinking events to localize molecules more accurately and eliminate false localizations. Using RoSE, we measure the distance between crossing microtubules, quantify the morphology of and separation between vesicles, and obtain robust recovery using diverse 3D PSFs with unmatched accuracy compared to state-of-the-art algorithms.

| S-EPMC6120949 | biostudies-literature

Quantifying accuracy and heterogeneity in single-molecule super-resolution microscopy.

Project description:The resolution and accuracy of single-molecule localization microscopes (SMLMs) are routinely benchmarked using simulated data, calibration rulers, or comparisons to secondary imaging modalities. However, these methods cannot quantify the nanoscale accuracy of an arbitrary SMLM dataset. Here, we show that by computing localization stability under a well-chosen perturbation with accurate knowledge of the imaging system, we can robustly measure the confidence of individual localizations without ground-truth knowledge of the sample. We demonstrate that our method, termed Wasserstein-induced flux (WIF), measures the accuracy of various reconstruction algorithms directly on experimental 2D and 3D data of microtubules and amyloid fibrils. We further show that WIF confidences can be used to evaluate the mismatch between computational models and imaging data, enhance the accuracy and resolution of reconstructed structures, and discover hidden molecular heterogeneities. As a computational methodology, WIF is broadly applicable to any SMLM dataset, imaging system, and localization algorithm.

| S-EPMC7732856 | biostudies-literature

A simple and cost-effective setup for super-resolution localization microscopy.

Project description:Single molecule localization microscopy (SMLM) has become a powerful imaging tool for biomedical research, but it is mostly available in imaging facilities and a small number of laboratories due to its high cost. Here, we evaluate the possibility of replacing high-cost components on standard SMLM with appropriate low-cost alternatives and build a simple but high-performance super-resolution SMLM setup. Through numerical simulation and biological experiments, we demonstrate that our low-cost SMLM setup can yield similar localization precision and spatial resolution compared to the standard SMLM equipped with state-of-the-art components, but at a small fraction of their cost. Our low-cost SMLM setup can potentially serve as a routine laboratory microscope with high-performance super-resolution imaging capability.

| S-EPMC5431525 | biostudies-literature

Optimized localization analysis for single-molecule tracking and super-resolution microscopy.

Project description:We optimally localized isolated fluorescent beads and molecules imaged as diffraction-limited spots, determined the orientation of molecules and present reliable formulas for the precision of various localization methods. Both theory and experimental data showed that unweighted least-squares fitting of a Gaussian squanders one-third of the available information, a popular formula for its precision exaggerates beyond Fisher's information limit, and weighted least-squares may do worse, whereas maximum-likelihood fitting is practically optimal.

| S-EPMC3127582 | biostudies-literature

Evaluation of super-resolution performance of the K2 electron-counting camera using 2D crystals of aquaporin-0.

Project description:The K2 Summit camera was initially the only commercially available direct electron detection camera that was optimized for high-speed counting of primary electrons and was also the only one that implemented centroiding so that the resolution of the camera can be extended beyond the Nyquist limit set by the physical pixel size. In this study, we used well-characterized two-dimensional crystals of the membrane protein aquaporin-0 to characterize the performance of the camera below and beyond the physical Nyquist limit and to measure the influence of electron dose rate on image amplitudes and phases.

| S-EPMC4633381 | biostudies-literature

Single-molecule-based super-resolution images in the presence of multiple fluorophores.

Project description:Several super-resolution techniques exist, yet most require multiple lasers, use either large or weakly emitting fluorophores, or involve chemical manipulation. Here we show a simple technique that exceeds the standard diffraction limit by 5-15× on fixed samples, yet allows the user to localize individual fluorophores from among groups of crowded fluorophores. It relies only on bright, organic fluorophores and a sensitive camera, both of which are commercially available. Super-resolution is achieved by subtracting sequential images to find the fluorophores that photobleach (temporarily or permanently), photoactivate, or bind to the structure of interest in transitioning from one frame to the next. These fluorophores can then be localized via Gaussian fitting with selective frame averaging to achieve accuracies much better than the diffraction limit. The signal-to-noise ratio decreases with the square root of the number of nearby fluorophores, producing average single-molecule localization errors that are typically <30 nm. Surprisingly, one can often extract signal when there are approximately 20 fluorophores surrounding the fluorophore of interest. Examples shown include microtubules (in vitro and in fixed cells) and chromosomal DNA.

| S-EPMC3212641 | biostudies-literature

Inferring biological structures from super-resolution single molecule images using generative models.

Project description:Localization-based super resolution imaging is presently limited by sampling requirements for dynamic measurements of biological structures. Generating an image requires serial acquisition of individual molecular positions at sufficient density to define a biological structure, increasing the acquisition time. Efficient analysis of biological structures from sparse localization data could substantially improve the dynamic imaging capabilities of these methods. Using a feature extraction technique called the Hough Transform simple biological structures are identified from both simulated and real localization data. We demonstrate that these generative models can efficiently infer biological structures in the data from far fewer localizations than are required for complete spatial sampling. Analysis at partial data densities revealed efficient recovery of clathrin vesicle size distributions and microtubule orientation angles with as little as 10% of the localization data. This approach significantly increases the temporal resolution for dynamic imaging and provides quantitatively useful biological information.

| S-EPMC3358321 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

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