Fourier ring correlation as a resolution criterion for super-resolution microscopy

Banterle, Niccolò; Bui, Khanh Huy; Lemke, Edward A.; Beck, Martin

doi:10.1016/j.jsb.2013.05.004

Cited by 307 publications

(245 citation statements)

References 17 publications

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“…Their FWHM values of (49 ± 7) nm and (40 ± 5) nm affirm the resolution below 50 nm. (b) Consistently, we find a Fourier-ring-correlation resolution 33,34 of (41.3 ± 2.3) nm for the dSTORM image of Fig. 2a.…”

Section: Supplementary Figure 1 |supporting

confidence: 83%

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Chip-based wide field-of-view nanoscopy

et al. 2017

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Optical microscopy based on waveguide chips significantly reduces the complexity of the entire optical setup, enabling miniaturization by completely removing the excitation light path from the microscope. Instead, waveguides which tightly confine the guided light by total internal reflection due to a high refractive index contrast (HIC) to the surrounding media such as water and cells are used to deliver the illumination light to the sample. The evanescent field on top of the waveguide can be utilized for total internal reflection fluorescence (TIRF) excitation over an almost arbitrarily wide FOV that is intrinsically independent of the detection objective lens and in principle only limited by the waveguide design. Evanescent field excitation using waveguides was first introduced by Grandin et al. 17 , where a slab waveguide was used to generate an evanescent field over the large stretch of the waveguide chip. Slab waveguides (Fig. 1a) Here, we demonstrate waveguide chip-based super-resolution fluorescence imaging by two complementary approaches using ESI and dSTORM. The high intensity in the evanescent field generated by the HIC waveguide material is used for optical switching of fluorophores as required by dSTORM. In addition, the intrinsically multi-mode interference pattern within the waveguide is used to generate fluctuating intensity patterns for ESI. To demonstrate the applicability of waveguide chip-based super-resolution microscopy we visualize the connection of the actin cytoskeleton and plasma membrane fenestrations in liver sinusoidal endothelial cells (LSECs). RESULTS Chip-based single molecule localization microscopyThe performance of chip-based dSTORM is shown by imaging immunostained microtubules in rat LSECs 26 plated directly on the waveguide (Fig. 2a). Measuring the lateral profile along one straight microtubule filament reveals a hollow structure 27 which has been used earlier in localization microscopy as a benchmark sample [28][29][30] , discussed in detail in 31 . This shows a resolution of better than 50 nm ( Fig. 2b), confirmed by full-width-at-half-maximum (FWHM) values, localization precision 32 , and Fourier ring correlation 33,34 (FRC) calculations ( Supplementary Fig. 1). The resolution capability was further investigated by using DNA origami nanorulers that provide markers at (50 ± 5) nm distance as references. These can be clearly resolved in chip-based dSTORM (Fig. 2c,d, Supplementary Fig. 2) which shows a comparable performance to the widely used architecture of an inverted TIRF dSTORM setup (Fig. 2c,d, Supplementary Fig. 3).As an advantage over conventional setups, waveguide chip-based nanoscopy greatly benefits from the fact that the fluorescence excitation is independent of the detection objective lens. As fluorescence is excited by the evanescent field of the waveguide, the technique provides optical sectioning and excellent signal to background ratios at penetration depths below 200 nm ( Supplementary Fig. 4, Supplementary Fig. 5, Video 1), similar to objective-based TIRF...

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Section: Supplementary Figure 1 |supporting

confidence: 83%

“…This shows a resolution of better than 50 nm (Fig. 2b), confirmed by full-width-at-half-maximum (FWHM) values, localization precision 32 , and Fourier ring correlation 33,34 (FRC) calculations ( Supplementary Fig. 1).…”

Section: Chip-based Single Molecule Localization Microscopysupporting

confidence: 54%

Chip-based wide field-of-view nanoscopy

et al. 2017

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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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“…10(d)). The effective resolution of the reconstructed image was measured using the method of Fourier ring correlation (FRC) [23,39]. FRC evaluates the degree of correlation of two independent reconstructions of the same object in frequency space and determines the resolution threshold (the spatial frequency) at which both reconstructions are consistent and considered to be resolved.…”

Section: Resultsmentioning

confidence: 99%

Improved localization accuracy in stochastic super-resolution fluorescence microscopy by K-factor image deshadowing

Ilovitsh

Meiri

Ebeling

et al. 2013

Biomed. Opt. Express

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Localization of a single fluorescent particle with sub-diffractionlimit accuracy is a key merit in localization microscopy. Existing methods such as photoactivated localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM) achieve localization accuracies of single emitters that can reach an order of magnitude lower than the conventional resolving capabilities of optical microscopy. However, these techniques require a sparse distribution of simultaneously activated fluorophores in the field of view, resulting in larger time needed for the construction of the full image. In this paper we present the use of a nonlinear image decomposition algorithm termed K-factor, which reduces an image into a nonlinear set of contrast-ordered decompositions whose joint product reassembles the original image. The K-factor technique, when implemented on raw data prior to localization, can improve the localization accuracy of standard existing methods, and also enable the localization of overlapping particles, allowing the use of increased fluorophore activation density, and thereby increased data collection speed. Numerical simulations of fluorescence data with random probe positions, and especially at high densities of activated fluorophores, demonstrate an improvement of up to 85% in the localization precision compared to single fitting techniques. Implementing the proposed concept on experimental data of cellular structures yielded a 37% improvement in resolution for the same superresolution image acquisition time, and a decrease of 42% in the collection time of super-resolution data with the same resolution.

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Fourier ring correlation as a resolution criterion for super-resolution microscopy

Cited by 307 publications

References 17 publications

Chip-based wide field-of-view nanoscopy

Chip-based wide field-of-view nanoscopy

Quantitative evaluation of software packages for single-molecule localization microscopy

Improved localization accuracy in stochastic super-resolution fluorescence microscopy by K-factor image deshadowing

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