Measuring image resolution in optical nanoscopy

Nieuwenhuizen, Robert P. J.; Lidke, Keith A.; Bates, Mark; Puig, Daniela Leyton; Grünwald, David; Stallinga, Sjoerd; Rieger, Bernd

doi:10.1038/nmeth.2448

Cited by 686 publications

(683 citation statements)

References 47 publications

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“…Fourier-ring correlation (FRC) was recently introduced as a method for measuring the image resolution in the SMLM context 21,65 . In the formalism of FRC, the set of positions is partitioned in two halves to determine the resolution.…”

Section: Computation Of the Image Resolution Using The Fourier Ring Cmentioning

confidence: 99%

Quantitative evaluation of software packages for single-molecule localization microscopy

et al. 2015

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the quality of super-resolution images obtained by singlemolecule localization microscopy (smlm) depends largely on the software used to detect and accurately localize point sources. in this work, we focus on the computational aspects of super-resolution microscopy and present a comprehensive evaluation of localization software packages. our philosophy is to evaluate each package as a whole, thus maintaining the integrity of the software. We prepared synthetic data that represent three-dimensional structures modeled after biological components, taking excitation parameters, noise sources, point-spread functions and pixelation into account. We then asked developers to run their software on our data; most responded favorably, allowing us to present a broad picture of the methods available. We evaluated their results using quantitative and user-interpretable criteria: detection rate, accuracy, quality of image reconstruction, resolution, software usability and computational resources. these metrics reflect the various tradeoffs of smlm software packages and help users to choose the software that fits their needs.We have conducted a large-scale comparative study of software packages developed in the context of SMLM, including recently developed algorithms. We designed realistic data that are generic and cover a broad range of experimental conditions and compared the software packages using a multiple-criterion quantitative assessment that is based on a known ground truth.Our study is based on the active participation of developers of SMLM software. More than 30 groups have participated so far, and the study is still under way. We provide participants access to our benchmark data as an ongoing public challenge. Participants run their own software on our data and report their list of localized particles for evaluation. The results of the challenge are accessible online and updated regularly.SMLM was demonstrated in 2006, independently by three research groups 1-3 , and has enabled subsequent breakthroughs in diverse fields 4,5 . SMLM can resolve biological structures at the nanometer scale (typically 20 nm lateral resolution), circumventing Abbe's diffraction limit. At the cost of a relatively simple setup 6,7 , it has opened exciting new opportunities in life science research 8,9 .The underlying principle of SMLM is the sequential imaging of sparse subsets of fluorophores distributed over thousands of frames, to populate a high-density map of fluorophore positions. Such large data sets require automated image-analysis algorithms to detect and precisely infer the position of individual fluorophore, taking advantage of their separation in space and time.The acquired data cannot be visualized directly; further computerized image-reconstruction methods are required. These typically comprise four steps: preprocessing, detection, localization and rendering. Preprocessing reduces the effects of the background and noise; detection identifies potential molecule candidates in each frame; localization performs a subpixel refine...

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Section: Computation Of the Image Resolution Using The Fourier Ring Cmentioning

confidence: 99%

Quantitative evaluation of software packages for single-molecule localization microscopy

et al. 2015

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“…In addition, translating the SMLM localization precision, typically between 10 and 25 nm, into spatial resolution is still very challenging due to a number of complicating factors. 15 Therefore, early on, the validation of SMLM has been carried out with correlative imaging using transmission electron microscopy (TEM). 6 Yet, in the case when SMLM is correlated either with TEM 6,16 or scanning electron microscopy (SEM), 17,18 sample preparation conditions are far from physiological, prohibiting the observation of live processes.…”

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confidence: 99%

High-Resolution Correlative Microscopy: Bridging the Gap between Single Molecule Localization Microscopy and Atomic Force Microscopy

Odermatt¹,

Shivanandan²,

Deschout³

et al. 2015

Nano Lett.

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Nanoscale characterization of living samples has become essential for modern biology. Atomic force microscopy (AFM) creates topological images of fragile biological structures from biomolecules to living cells in aqueous environments. However, correlating nanoscale structure to biological function of specific proteins can be challenging. To this end we have built and characterized a correlated single molecule localization microscope (SMLM)/AFM that allows localizing specific, labeled proteins within high-resolution AFM images in a biologically relevant context. Using direct stochastic optical reconstruction microscopy (dSTORM)/AFM, we directly correlate and quantify the density of localizations with the 3D topography using both imaging modalities along (F-)actin cytoskeletal filaments. In addition, using photo activated light microscopy (PALM)/AFM, we provide correlative images of bacterial cells in aqueous conditions. Moreover, we report the first correlated AFM/PALM imaging of live mammalian cells. The complementary information provided by the two techniques opens a new dimension for structural and functional nanoscale biology.

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“…FRC has also recently been used in optical microscopy [31,32]. A set of 76 phase images was split into two statistically independent sets of 38 phase images and two independent XL-SIM images were processed, which are shown in Supplementary Figure S12.…”

Section: Quantitative Resolution Measurementmentioning

confidence: 99%

“…Subsequently, the FRC was calculated from the two XL-SIM images of the nanoruler sample as described, e.g., in [31]. We used the value of 1/7 ≈ 0.143 as the threshold criterion, which has also been used, e.g., in [32]. A graphical illustration of the FRC is shown in Figure 4c.…”

Section: Quantitative Resolution Measurementmentioning

confidence: 99%

XL-SIM: Extending Superresolution into Deeper Layers

2017

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Of all 3D-super resolution techniques, structured illumination microscopy (SIM) provides the best compromise with respect to resolution, signal-to-noise ratio (S/N), speed and cell viability. Its ability to achieve double resolution in all three dimensions enables resolving 3D-volumes almost 10× smaller than with a normal light microscope. Its major drawback is noise contained in the out-of-focus-signal, which-unlike the out-of-focus signal itself-cannot be removed mathematically. The resulting "noise-pollution" grows bigger the more light is removed, thus rendering thicker biological samples unsuitable for SIM. By using a slit confocal pattern, we employ optical means to suppress out-of-focus light before its noise can spoil SIM mathematics. This not only increases tissue penetration considerably, but also provides a better S/N performance and an improved confocality. The SIM pattern we employ is no line grid, but a two-dimensional hexagonal structure, which makes pattern rotation between image acquisitions obsolete and thus simplifies image acquisition and yields more robust fit parameters for SIM.

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Measuring image resolution in optical nanoscopy

Cited by 686 publications

References 47 publications

Quantitative evaluation of software packages for single-molecule localization microscopy

Quantitative evaluation of software packages for single-molecule localization microscopy

High-Resolution Correlative Microscopy: Bridging the Gap between Single Molecule Localization Microscopy and Atomic Force Microscopy

XL-SIM: Extending Superresolution into Deeper Layers

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