Comparison between SOFI and STORM

Geissbuehler, Stefan; Dellagiacoma, Claudio; Lasser, Theo

doi:10.1364/boe.2.000408

Cited by 134 publications

(192 citation statements)

References 28 publications

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“…The peak signal-to-noise ratio (pSNR; noise measured on the background) in a single frame was 20-23dB for the brightest molecules, which is rather low for performing localization microscopy, but more than sufficient for SOFI (Geissbuehler et al 2011). Additionally, we observed significant read-out noise at this acquisition speed (fixed-pattern noise in the average image, Figure (f-h) Profiles along the cuts 1-1', 2-2' and 3-3'.…”

Section: Resultsmentioning

confidence: 99%

“…I( r i , t) is the intensity distribution measured over time on a detector pixel r i . We used the cross-cumulant approach without repetitions to increase the pixel grid density and eliminate any bias arising from noise contributions in auto-cumulants (Geissbuehler et al 2011). A 4x4 neighborhood around every pixel was considered to compute all possible n-pixel combinations excluding pixel repetitions.…”

Section: Theory and Algorithmmentioning

confidence: 99%

“…Uncorrelated noise, stationary background, as well as out-of-focus light are greatly reduced by the cumulants analysis. While PALM and STORM are commonly based on a frame-byframe analysis of images of individual fluorophores, SOFI processes the entire image sequence at once and therefore presents significant advantages in terms of the number of required photons per fluorophore and image, as well as in acquisition time (Geissbuehler et al 2011). Localization microscopy requires a meta-stable dark state for imaging individual fluorophores (van de Linde et al 2010).…”

Section: Introductionmentioning

confidence: 99%

“…Localization microscopy requires a meta-stable dark state for imaging individual fluorophores (van de Linde et al 2010). In contrast, SOFI relies solely on stochastic, reversible and temporally resolvable fluorescence fluctuations almost regardless of the on-off duty cycle (Geissbuehler et al 2011). The main drawback of SOFI is the amplification of heterogeneities in molecular brightness and blinking statistics which limits the use of higher-order cumulants and therefore resolution.…”

Section: Introductionmentioning

confidence: 99%

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Mapping molecular statistics with balanced super-resolution optical fluctuation imaging (bSOFI)

et al. 2012

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Background: Super-resolution optical fluctuation imaging (SOFI) achieves 3D super-resolution by computing temporal cumulants or spatio-temporal cross-cumulants of stochastically blinking fluorophores. In contrast to localization microscopy, SOFI is compatible with weakly emitting fluorophores and a wide range of blinking conditions. The main drawback of SOFI is the nonlinear response to brightness and blinking heterogeneities in the sample, which limits the use of higher cumulant orders for improving the resolution. Balanced super-resolution optical fluctuation imaging (bSOFI) analyses several cumulant orders for extracting molecular parameter maps, such as molecular state lifetimes, concentration and brightness distributions of fluorophores within biological samples. Moreover, the estimated blinking statistics are used to balance the image contrast, i.e. linearize the brightness and blinking response and to obtain a resolution improving linearly with the cumulant order. Results: Using a widefield total-internal-reflection (TIR) fluorescence microscope, we acquired image sequences of fluorescently labelled microtubules in fixed HeLa cells. We demonstrate an up to five-fold resolution improvement as compared to the diffraction-limited image, despite low single-frame signal-to-noise ratios. Due to the TIR illumination, the intensity profile in the sample decreases exponentially along the optical axis, which is reported by the estimated spatial distributions of the molecular brightness as well as the blinking on-ratio. Therefore, TIR-bSOFI also encodes depth information through these parameter maps. Conclusions: bSOFI is an extended version of SOFI that cancels the nonlinear response to brightness and blinking heterogeneities. The obtained balanced image contrast significantly enhances the visual perception of super-resolution based on higher-order cumulants and thereby facilitates the access to higher resolutions. Furthermore, bSOFI provides microenvironment-related molecular parameter maps and paves the way for functional super-resolution microscopy based on stochastic switching.

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Section: Resultsmentioning

confidence: 99%

Section: Theory and Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Mapping molecular statistics with balanced super-resolution optical fluctuation imaging (bSOFI)

et al. 2012

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“…SOFI does not require specialized equipment and can produce subdiffraction images over a broad range of imaging conditions, including low signal-tonoise and high background (11,12). In SOFI, a dataset of tens or hundreds of images is acquired at high speed, using fluorophores that can switch between a fluorescent and nonfluorescent state repeatedly.…”

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Widely accessible method for superresolution fluorescence imaging of living systems

Dedecker

Dertinger³

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

196

182

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Superresolution fluorescence microscopy overcomes the diffraction resolution barrier and allows the molecular intricacies of life to be revealed with greatly enhanced detail. However, many current superresolution techniques still face limitations and their implementation is typically associated with a steep learning curve. Patterned illumination-based superresolution techniques [e.g., stimulated emission depletion (STED), reversible optically-linear fluorescence transitions (RESOLFT), and saturated structured illumination microscopy (SSIM)] require specialized equipment, whereas single-molecule-based approaches [e.g., stochastic optical reconstruction microscopy (STORM), photo-activation localization microscopy (PALM), and fluorescence-PALM (F-PALM)] involve repetitive single-molecule localization, which requires its own set of expertise and is also temporally demanding. Here we present a superresolution fluorescence imaging method, photochromic stochastic optical fluctuation imaging (pcSOFI). In this method, irradiating a reversibly photoswitching fluorescent protein at an appropriate wavelength produces robust single-molecule intensity fluctuations, from which a superresolution picture can be extracted by a statistical analysis of the fluctuations in each pixel as a function of time, as previously demonstrated in SOFI. This method, which uses off-the-shelf equipment, genetically encodable labels, and simple and rapid data acquisition, is capable of providing two-to threefold-enhanced spatial resolution, significant background rejection, markedly improved contrast, and favorable temporal resolution in living cells. Furthermore, both 3D and multicolor imaging are readily achievable. Because of its ease of use and high performance, we anticipate that pcSOFI will prove an attractive approach for superresolution imaging.subdiffraction-limit | two-color imaging | membrane rafts F luorescence imaging has become one of the major avenues for analyzing various molecular events underlying cellular processes. Even though many fluorophores can be used as molecular labels, direct observation at the molecular length scale is hampered by the diffraction of light. To provide a more detailed image of molecular events in cells, a number of techniques have been recently developed that bestow far-field fluorescence microscopy with fundamentally unlimited spatial resolution (1, 2). These techniques, either based on patterned illumination [such as stimulated emission depletion (STED) microscopy (3, 4), reversible optically linear fluorescence transitions (RESOLFT) microscopy (5), and saturated structured illumination microscopy (SSIM) (6)] or repeated single-molecule localization [such as photo-activation localization microscopy (PALM), stochastic optical reconstruction microscopy (STORM), fluorescence-PALM (F-PALM), ground-state depletion microscopy (GSDIM) microscopy (7-10)], are capable of improving spatial resolution by over an order of magnitude. However, these methods still face limitations. STED, RESOLFT, and SSIM microscopy ...

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Diffraction‐Unlimited Fluorescence Microscopy of Living Biological Samples Using pcSOFI

Duwé

Moeyaert

Dedecker

2015

CP Chemical Biology

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The complex microscopic nature of many live biological processes is often obscured by the diffraction limit of light, requiring diffraction‐unlimited fluorescence microscopy to resolve them. Because of the vast range of different processes that can be studied, sub‐diffraction imaging should work efficiently under many different conditions. Photochromic stochastic optical fluctuation imaging (pcSOFI) is a recent addition to the field of diffraction‐unlimited fluorescence microscopy. This robust and versatile method employs a statistical analysis of random fluctuations in the emission of single labels, in this case reversibly switchable fluorescent proteins (RSFPs), to retrieve super‐resolution information. Added to the resolution enhancement, pcSOFI also offers contrast enhancement and background reduction in a practical and convenient way. Here, we describe the necessary steps to obtain diffraction‐unlimited images, including multicolor and three‐dimensional imaging, and highlight the advantages of pcSOFI together with the circumstances under which pcSOFI can be favorably applied. © 2015 by John Wiley & Sons, Inc.

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Comparison between SOFI and STORM

Cited by 134 publications

References 28 publications

Mapping molecular statistics with balanced super-resolution optical fluctuation imaging (bSOFI)

Mapping molecular statistics with balanced super-resolution optical fluctuation imaging (bSOFI)

Widely accessible method for superresolution fluorescence imaging of living systems

Diffraction‐Unlimited Fluorescence Microscopy of Living Biological Samples Using pcSOFI

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