Abstract

Multi-emitter localization has great potential for maximizing the imaging speed of super-resolution localization microscopy. However, the slow image analysis speed of reported multi-emitter localization algorithms limits their usage in mostly off-line image processing with small image size. Here we adopt the well-known divide and conquer strategy in computer science and present a fitting-based method called QC-STORM for fast multi-emitter localization. Using simulated and experimental data, we verify that QC-STORM is capable of providing real-time full image processing on raw images with 100 µm × 100 µm field of view and 10 ms exposure time, with comparable spatial resolution as the popular fitting-based ThunderSTORM and the up-to-date non-iterative WindSTORM. This study pushes the development and practical use of super-resolution localization microscopy in high-throughput or high-content imaging of cell-to-cell differences or discovering rare events in a large cell population.

© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

Full Article  |  PDF Article
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References

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2019 (3)

M. Shannon and D. M. Owen, “Bridging the Nanoscopy-Immunology Gap,” Front. Phys. 6, 157 (2019).
[Crossref]

H. Ma, J. Xu, and Y. Liu, “WindSTORM: Robust online image processing for high-throughput nanoscopy,” Sci. Adv. 5(4), eaaw0683 (2019).
[Crossref]

D. Sage, T.-A. Pham, H. Babcock, T. Lukes, T. Pengo, J. Chao, R. Velmurugan, A. Herbert, A. Agrawal, S. Colabrese, A. Wheeler, A. Archetti, B. Rieger, R. Ober, G. M. Hagen, J.-B. Sibarita, J. Ries, R. Henriques, M. Unser, and S. Holden, “Super-resolution fight club: assessment of 2D and 3D single-molecule localization microscopy software,” Nat. Methods 16(5), 387–395 (2019).
[Crossref]

2018 (6)

R. Strack, “Deep learning advances super-resolution imaging,” Nat. Methods 15(6), 403 (2018).
[Crossref]

Y. Li, M. Mund, P. Hoess, J. Deschamps, U. Matti, B. Nijmeijer, V. J. Sabinina, J. Ellenberg, I. Schoen, and J. Ries, “Real-time 3D single-molecule localization using experimental point spread functions,” Nat. Methods 15(5), 367–369 (2018).
[Crossref]

Y. M. Sigal, R. Zhou, and X. Zhuang, “Visualizing and discovering cellular structures with super-resolution microscopy,” Science 361(6405), 880–887 (2018).
[Crossref]

W. Ouyang, A. Aristov, M. Lelek, X. Hao, and C. Zimmer, “Deep learning massively accelerates super-resolution localization microscopy,” Nat. Biotechnol. 36(5), 460–468 (2018).
[Crossref]

E. Nehme, L. E. Weiss, T. Michaeli, and Y. Shechtman, “Deep-STORM: super-resolution single-molecule microscopy by deep learning,” Optica 5(4), 458–464 (2018).
[Crossref]

M. Štefko, B. Ottino, K. M. Douglass, and S. Manley, “Autonomous illumination control for localization microscopy,” Opt. Express 26(23), 30882–30900 (2018).
[Crossref]

2017 (3)

Z. Zhao, B. Xin, L. Li, and Z.-L. Huang, “High-power homogeneous illumination for super-resolution localization microscopy with large field-of-view,” Opt. Express 25(12), 13382–13395 (2017).
[Crossref]

H. Ma, R. Fu, J. Xu, and Y. Liu, “A simple and cost-effective setup for super-resolution localization microscopy,” Sci. Rep. 7(1), 1542 (2017).
[Crossref]

A. Beghin, A. Kechkar, C. Butler, F. Levet, M. Cabillic, O. Rossier, G. Giannone, R. Galland, D. Choquet, and J.-B. Sibarita, “Localization-based super-resolution imaging meets high-content screening,” Nat. Methods 14(12), 1184–1190 (2017).
[Crossref]

2016 (1)

M. Mattiazzi Usaj, E. B. Styles, A. J. Verster, H. Friesen, C. Boone, and B. J. Andrews, “High-Content Screening for Quantitative Cell Biology,” Trends Cell Biol. 26(8), 598–611 (2016).
[Crossref]

2015 (4)

J. Min, C. Vonesch, H. Kirshner, L. Carlini, N. Olivier, S. Holden, S. Manley, J. C. Ye, and M. Unser, “FALCON: fast and unbiased reconstruction of high-density super-resolution microscopy data,” Sci. Rep. 4(1), 4577 (2015).
[Crossref]

D. Sage, H. Kirshner, T. Pengo, N. Stuurman, J. Min, S. Manley, and M. Unser, “Quantitative evaluation of software packages for single-molecule localization microscopy,” Nat. Methods 12(8), 717–724 (2015).
[Crossref]

P. Almada, S. Culley, and R. Henriques, “PALM and STORM: Into large fields and high-throughput microscopy with sCMOS detectors,” Methods 88, 109–121 (2015).
[Crossref]

P. Bon, N. Bourg, S. Lécart, S. Monneret, E. Fort, J. Wenger, and S. Lévêque-Fort, “Three-dimensional nanometre localization of nanoparticles to enhance super-resolution microscopy,” Nat. Commun. 6(1), 7764 (2015).
[Crossref]

2014 (3)

M. Ovesný, P. Křížek, J. Borkovec, Z. Švindrych, and G. M. Hagen, “ThunderSTORM: a comprehensive ImageJ plug-in for PALM and STORM data analysis and super-resolution imaging,” Bioinformatics 30(16), 2389–2390 (2014).
[Crossref]

T. Holm, T. Klein, A. Löschberger, T. Klamp, G. Wiebusch, S. van de Linde, and M. Sauer, “A Blueprint for Cost-Efficient Localization Microscopy,” ChemPhysChem 15(4), 651–654 (2014).
[Crossref]

A. Small and S. Stahlheber, “Fluorophore localization algorithms for super-resolution microscopy,” Nat. Methods 11(3), 267–279 (2014).
[Crossref]

2013 (4)

R. P. J. Nieuwenhuizen, K. A. Lidke, M. Bates, D. L. Puig, D. Grünwald, S. Stallinga, and B. Rieger, “Measuring image resolution in optical nanoscopy,” Nat. Methods 10(6), 557–562 (2013).
[Crossref]

A. Kechkar, D. Nair, M. Heilemann, D. Choquet, and J.-B. Sibarita, “Real-Time Analysis and Visualization for Single-Molecule Based Super-Resolution Microscopy,” PLoS One 8(4), e62918 (2013).
[Crossref]

R. McGorty, D. Kamiyama, and B. Huang, “Active microscope stabilization in three dimensions using image correlation,” Biomed. Opt. Phase Microsc. Nanosc. 2(1), 3 (2013).
[Crossref]

F. Huang, T. M. P. Hartwich, F. E. Rivera-Molina, Y. Lin, W. C. Duim, J. J. Long, P. D. Uchil, J. R. Myers, M. A. Baird, W. Mothes, M. W. Davidson, D. Toomre, and J. Bewersdorf, “Video-rate nanoscopy using sCMOS camera-specific single-molecule localization algorithms,” Nat. Methods 10(7), 653–658 (2013).
[Crossref]

2012 (3)

H. Babcock, Y. M. Sigal, and X. Zhuang, “A high-density 3D localization algorithm for stochastic optical reconstruction microscopy,” Biomed. Opt. Phase Microsc. Nanosc. 1(1), 6 (2012).
[Crossref]

S. H. Lee, M. Baday, M. Tjioe, P. D. Simonson, R. Zhang, E. Cai, and P. R. Selvin, “Using fixed fiduciary markers for stage drift correction,” Opt. Express 20(11), 12177–12183 (2012).
[Crossref]

I. Mukherjee and S. Routroy, “Comparing the performance of neural networks developed by using Levenberg–Marquardt and Quasi-Newton with the gradient descent algorithm for modelling a multiple response grinding process,” Expert Syst. Appl. 39(3), 2397–2407 (2012).
[Crossref]

2011 (4)

S. van de Linde, A. Löschberger, T. Klein, M. Heidbreder, S. Wolter, M. Heilemann, and M. Sauer, “Direct stochastic optical reconstruction microscopy with standard fluorescent probes,” Nat. Protoc. 6(7), 991–1009 (2011).
[Crossref]

F. Huang, S. L. Schwartz, J. M. Byars, and K. A. Lidke, “Simultaneous multiple-emitter fitting for single molecule super-resolution imaging,” Biomed. Opt. Express 2(5), 1377–1393 (2011).
[Crossref]

S. J. Holden, S. Uphoff, and A. N. Kapanidis, “DAOSTORM: an algorithm for high-density super-resolution microscopy,” Nat. Methods 8(4), 279–280 (2011).
[Crossref]

S. A. Jones, S.-H. Shim, J. He, and X. Zhuang, “Fast, three-dimensional super-resolution imaging of live cells,” Nat. Methods 8(6), 499–505 (2011).
[Crossref]

2010 (2)

T. Quan, P. Li, F. Long, S. Zeng, Q. Luo, P. N. Hedde, G. U. Nienhaus, and Z.-L. Huang, “Ultra-fast, high-precision image analysis for localization-based super resolution microscopy,” Opt. Express 18(11), 11867–11876 (2010).
[Crossref]

C. S. Smith, N. Joseph, B. Rieger, and K. A. Lidke, “Fast, single-molecule localization that achieves theoretically minimum uncertainty,” Nat. Methods 7(5), 373–375 (2010).
[Crossref]

2008 (1)

B. Huang, W. Wang, M. Bates, and X. Zhuang, “Three-dimensional super-resolution imaging by stochastic optical reconstruction microscopy,” Science 319(5864), 810–813 (2008).
[Crossref]

2006 (3)

E. Betzig, G. H. Patterson, R. Sougrat, O. W. Lindwasser, S. Olenych, J. S. Bonifacino, M. W. Davidson, J. Lippincott-Schwartz, and H. F. Hess, “Imaging intracellular fluorescent proteins at nanometer resolution,” Science 313(5793), 1642–1645 (2006).
[Crossref]

S. T. Hess, T. P. K. Girirajan, and M. D. Mason, “Ultra-high resolution imaging by fluorescence photoactivation localization microscopy,” Biophys. J. 91(11), 4258–4272 (2006).
[Crossref]

M. J. Rust, M. Bates, and X. Zhuang, “Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM),” Nat. Methods 3(10), 793–796 (2006).
[Crossref]

2005 (1)

E. S. Ahmed, A. I. Volodin, and A. A. Hussein, “Robust weighted likelihood estimation of exponential parameters,” IEEE Trans. Reliab. 54(3), 389–395 (2005).
[Crossref]

1994 (1)

C. Field and B. Smith, “Robust Estimation: A Weighted Maximum Likelihood Approach,” Int. Stat. Rev. 62(3), 405–424 (1994).
[Crossref]

Agrawal, A.

D. Sage, T.-A. Pham, H. Babcock, T. Lukes, T. Pengo, J. Chao, R. Velmurugan, A. Herbert, A. Agrawal, S. Colabrese, A. Wheeler, A. Archetti, B. Rieger, R. Ober, G. M. Hagen, J.-B. Sibarita, J. Ries, R. Henriques, M. Unser, and S. Holden, “Super-resolution fight club: assessment of 2D and 3D single-molecule localization microscopy software,” Nat. Methods 16(5), 387–395 (2019).
[Crossref]

Ahmed, E. S.

E. S. Ahmed, A. I. Volodin, and A. A. Hussein, “Robust weighted likelihood estimation of exponential parameters,” IEEE Trans. Reliab. 54(3), 389–395 (2005).
[Crossref]

Almada, P.

P. Almada, S. Culley, and R. Henriques, “PALM and STORM: Into large fields and high-throughput microscopy with sCMOS detectors,” Methods 88, 109–121 (2015).
[Crossref]

Andrews, B. J.

M. Mattiazzi Usaj, E. B. Styles, A. J. Verster, H. Friesen, C. Boone, and B. J. Andrews, “High-Content Screening for Quantitative Cell Biology,” Trends Cell Biol. 26(8), 598–611 (2016).
[Crossref]

Archetti, A.

D. Sage, T.-A. Pham, H. Babcock, T. Lukes, T. Pengo, J. Chao, R. Velmurugan, A. Herbert, A. Agrawal, S. Colabrese, A. Wheeler, A. Archetti, B. Rieger, R. Ober, G. M. Hagen, J.-B. Sibarita, J. Ries, R. Henriques, M. Unser, and S. Holden, “Super-resolution fight club: assessment of 2D and 3D single-molecule localization microscopy software,” Nat. Methods 16(5), 387–395 (2019).
[Crossref]

Aristov, A.

W. Ouyang, A. Aristov, M. Lelek, X. Hao, and C. Zimmer, “Deep learning massively accelerates super-resolution localization microscopy,” Nat. Biotechnol. 36(5), 460–468 (2018).
[Crossref]

Babcock, H.

D. Sage, T.-A. Pham, H. Babcock, T. Lukes, T. Pengo, J. Chao, R. Velmurugan, A. Herbert, A. Agrawal, S. Colabrese, A. Wheeler, A. Archetti, B. Rieger, R. Ober, G. M. Hagen, J.-B. Sibarita, J. Ries, R. Henriques, M. Unser, and S. Holden, “Super-resolution fight club: assessment of 2D and 3D single-molecule localization microscopy software,” Nat. Methods 16(5), 387–395 (2019).
[Crossref]

H. Babcock, Y. M. Sigal, and X. Zhuang, “A high-density 3D localization algorithm for stochastic optical reconstruction microscopy,” Biomed. Opt. Phase Microsc. Nanosc. 1(1), 6 (2012).
[Crossref]

Baday, M.

Baddeley, D.

A. E. S. Barentine, Y. Lin, M. Liu, P. Kidd, L. Balduf, M. R. Grace, S. Wang, J. Bewersdorf, and D. Baddeley, “3D Multicolor Nanoscopy at 10,000 Cells a Day,” bioRxiv, 606954 (2019).

Baird, M. A.

F. Huang, T. M. P. Hartwich, F. E. Rivera-Molina, Y. Lin, W. C. Duim, J. J. Long, P. D. Uchil, J. R. Myers, M. A. Baird, W. Mothes, M. W. Davidson, D. Toomre, and J. Bewersdorf, “Video-rate nanoscopy using sCMOS camera-specific single-molecule localization algorithms,” Nat. Methods 10(7), 653–658 (2013).
[Crossref]

Balduf, L.

A. E. S. Barentine, Y. Lin, M. Liu, P. Kidd, L. Balduf, M. R. Grace, S. Wang, J. Bewersdorf, and D. Baddeley, “3D Multicolor Nanoscopy at 10,000 Cells a Day,” bioRxiv, 606954 (2019).

Barentine, A. E. S.

A. E. S. Barentine, Y. Lin, M. Liu, P. Kidd, L. Balduf, M. R. Grace, S. Wang, J. Bewersdorf, and D. Baddeley, “3D Multicolor Nanoscopy at 10,000 Cells a Day,” bioRxiv, 606954 (2019).

Bates, M.

R. P. J. Nieuwenhuizen, K. A. Lidke, M. Bates, D. L. Puig, D. Grünwald, S. Stallinga, and B. Rieger, “Measuring image resolution in optical nanoscopy,” Nat. Methods 10(6), 557–562 (2013).
[Crossref]

B. Huang, W. Wang, M. Bates, and X. Zhuang, “Three-dimensional super-resolution imaging by stochastic optical reconstruction microscopy,” Science 319(5864), 810–813 (2008).
[Crossref]

M. J. Rust, M. Bates, and X. Zhuang, “Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM),” Nat. Methods 3(10), 793–796 (2006).
[Crossref]

Beghin, A.

A. Beghin, A. Kechkar, C. Butler, F. Levet, M. Cabillic, O. Rossier, G. Giannone, R. Galland, D. Choquet, and J.-B. Sibarita, “Localization-based super-resolution imaging meets high-content screening,” Nat. Methods 14(12), 1184–1190 (2017).
[Crossref]

Betzig, E.

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Bewersdorf, J.

F. Huang, T. M. P. Hartwich, F. E. Rivera-Molina, Y. Lin, W. C. Duim, J. J. Long, P. D. Uchil, J. R. Myers, M. A. Baird, W. Mothes, M. W. Davidson, D. Toomre, and J. Bewersdorf, “Video-rate nanoscopy using sCMOS camera-specific single-molecule localization algorithms,” Nat. Methods 10(7), 653–658 (2013).
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A. E. S. Barentine, Y. Lin, M. Liu, P. Kidd, L. Balduf, M. R. Grace, S. Wang, J. Bewersdorf, and D. Baddeley, “3D Multicolor Nanoscopy at 10,000 Cells a Day,” bioRxiv, 606954 (2019).

Bohrer, C. H.

C. H. Bohrer, X. Yang, Z. Lyu, S.-C. Wang, and J. Xiao, “Improved single-molecule localization precision in astigmatism-based 3D superresolution imaging using weighted likelihood estimation,” bioRxiv, 304816 (2018).

Bon, P.

P. Bon, N. Bourg, S. Lécart, S. Monneret, E. Fort, J. Wenger, and S. Lévêque-Fort, “Three-dimensional nanometre localization of nanoparticles to enhance super-resolution microscopy,” Nat. Commun. 6(1), 7764 (2015).
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Bonifacino, J. S.

E. Betzig, G. H. Patterson, R. Sougrat, O. W. Lindwasser, S. Olenych, J. S. Bonifacino, M. W. Davidson, J. Lippincott-Schwartz, and H. F. Hess, “Imaging intracellular fluorescent proteins at nanometer resolution,” Science 313(5793), 1642–1645 (2006).
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Boone, C.

M. Mattiazzi Usaj, E. B. Styles, A. J. Verster, H. Friesen, C. Boone, and B. J. Andrews, “High-Content Screening for Quantitative Cell Biology,” Trends Cell Biol. 26(8), 598–611 (2016).
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Borkovec, J.

M. Ovesný, P. Křížek, J. Borkovec, Z. Švindrych, and G. M. Hagen, “ThunderSTORM: a comprehensive ImageJ plug-in for PALM and STORM data analysis and super-resolution imaging,” Bioinformatics 30(16), 2389–2390 (2014).
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Bourg, N.

P. Bon, N. Bourg, S. Lécart, S. Monneret, E. Fort, J. Wenger, and S. Lévêque-Fort, “Three-dimensional nanometre localization of nanoparticles to enhance super-resolution microscopy,” Nat. Commun. 6(1), 7764 (2015).
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A. Beghin, A. Kechkar, C. Butler, F. Levet, M. Cabillic, O. Rossier, G. Giannone, R. Galland, D. Choquet, and J.-B. Sibarita, “Localization-based super-resolution imaging meets high-content screening,” Nat. Methods 14(12), 1184–1190 (2017).
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Byars, J. M.

Cabillic, M.

A. Beghin, A. Kechkar, C. Butler, F. Levet, M. Cabillic, O. Rossier, G. Giannone, R. Galland, D. Choquet, and J.-B. Sibarita, “Localization-based super-resolution imaging meets high-content screening,” Nat. Methods 14(12), 1184–1190 (2017).
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Cai, E.

Carlini, L.

J. Min, C. Vonesch, H. Kirshner, L. Carlini, N. Olivier, S. Holden, S. Manley, J. C. Ye, and M. Unser, “FALCON: fast and unbiased reconstruction of high-density super-resolution microscopy data,” Sci. Rep. 4(1), 4577 (2015).
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D. Sage, T.-A. Pham, H. Babcock, T. Lukes, T. Pengo, J. Chao, R. Velmurugan, A. Herbert, A. Agrawal, S. Colabrese, A. Wheeler, A. Archetti, B. Rieger, R. Ober, G. M. Hagen, J.-B. Sibarita, J. Ries, R. Henriques, M. Unser, and S. Holden, “Super-resolution fight club: assessment of 2D and 3D single-molecule localization microscopy software,” Nat. Methods 16(5), 387–395 (2019).
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Choquet, D.

A. Beghin, A. Kechkar, C. Butler, F. Levet, M. Cabillic, O. Rossier, G. Giannone, R. Galland, D. Choquet, and J.-B. Sibarita, “Localization-based super-resolution imaging meets high-content screening,” Nat. Methods 14(12), 1184–1190 (2017).
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A. Kechkar, D. Nair, M. Heilemann, D. Choquet, and J.-B. Sibarita, “Real-Time Analysis and Visualization for Single-Molecule Based Super-Resolution Microscopy,” PLoS One 8(4), e62918 (2013).
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D. Sage, T.-A. Pham, H. Babcock, T. Lukes, T. Pengo, J. Chao, R. Velmurugan, A. Herbert, A. Agrawal, S. Colabrese, A. Wheeler, A. Archetti, B. Rieger, R. Ober, G. M. Hagen, J.-B. Sibarita, J. Ries, R. Henriques, M. Unser, and S. Holden, “Super-resolution fight club: assessment of 2D and 3D single-molecule localization microscopy software,” Nat. Methods 16(5), 387–395 (2019).
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Collier, J.

S. J. Holden, T. Pengo, K. L. Meibom, C. F. Fernandez, J. Collier, and S. Manley, “High throughput 3D super-resolution microscopy reveals Caulobacter crescentus in vivo Z-ring organization,” Proc. Natl. Acad. Sci. USA111(12), 4566–4571 (2014).
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P. Almada, S. Culley, and R. Henriques, “PALM and STORM: Into large fields and high-throughput microscopy with sCMOS detectors,” Methods 88, 109–121 (2015).
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Davidson, M. W.

F. Huang, T. M. P. Hartwich, F. E. Rivera-Molina, Y. Lin, W. C. Duim, J. J. Long, P. D. Uchil, J. R. Myers, M. A. Baird, W. Mothes, M. W. Davidson, D. Toomre, and J. Bewersdorf, “Video-rate nanoscopy using sCMOS camera-specific single-molecule localization algorithms,” Nat. Methods 10(7), 653–658 (2013).
[Crossref]

E. Betzig, G. H. Patterson, R. Sougrat, O. W. Lindwasser, S. Olenych, J. S. Bonifacino, M. W. Davidson, J. Lippincott-Schwartz, and H. F. Hess, “Imaging intracellular fluorescent proteins at nanometer resolution,” Science 313(5793), 1642–1645 (2006).
[Crossref]

Deschamps, J.

Y. Li, M. Mund, P. Hoess, J. Deschamps, U. Matti, B. Nijmeijer, V. J. Sabinina, J. Ellenberg, I. Schoen, and J. Ries, “Real-time 3D single-molecule localization using experimental point spread functions,” Nat. Methods 15(5), 367–369 (2018).
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Douglass, K. M.

Duim, W. C.

F. Huang, T. M. P. Hartwich, F. E. Rivera-Molina, Y. Lin, W. C. Duim, J. J. Long, P. D. Uchil, J. R. Myers, M. A. Baird, W. Mothes, M. W. Davidson, D. Toomre, and J. Bewersdorf, “Video-rate nanoscopy using sCMOS camera-specific single-molecule localization algorithms,” Nat. Methods 10(7), 653–658 (2013).
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Ellenberg, J.

Y. Li, M. Mund, P. Hoess, J. Deschamps, U. Matti, B. Nijmeijer, V. J. Sabinina, J. Ellenberg, I. Schoen, and J. Ries, “Real-time 3D single-molecule localization using experimental point spread functions,” Nat. Methods 15(5), 367–369 (2018).
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Fernandez, C. F.

S. J. Holden, T. Pengo, K. L. Meibom, C. F. Fernandez, J. Collier, and S. Manley, “High throughput 3D super-resolution microscopy reveals Caulobacter crescentus in vivo Z-ring organization,” Proc. Natl. Acad. Sci. USA111(12), 4566–4571 (2014).
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C. Field and B. Smith, “Robust Estimation: A Weighted Maximum Likelihood Approach,” Int. Stat. Rev. 62(3), 405–424 (1994).
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Fort, E.

P. Bon, N. Bourg, S. Lécart, S. Monneret, E. Fort, J. Wenger, and S. Lévêque-Fort, “Three-dimensional nanometre localization of nanoparticles to enhance super-resolution microscopy,” Nat. Commun. 6(1), 7764 (2015).
[Crossref]

Friesen, H.

M. Mattiazzi Usaj, E. B. Styles, A. J. Verster, H. Friesen, C. Boone, and B. J. Andrews, “High-Content Screening for Quantitative Cell Biology,” Trends Cell Biol. 26(8), 598–611 (2016).
[Crossref]

Fu, R.

H. Ma, R. Fu, J. Xu, and Y. Liu, “A simple and cost-effective setup for super-resolution localization microscopy,” Sci. Rep. 7(1), 1542 (2017).
[Crossref]

Galland, R.

A. Beghin, A. Kechkar, C. Butler, F. Levet, M. Cabillic, O. Rossier, G. Giannone, R. Galland, D. Choquet, and J.-B. Sibarita, “Localization-based super-resolution imaging meets high-content screening,” Nat. Methods 14(12), 1184–1190 (2017).
[Crossref]

Giannone, G.

A. Beghin, A. Kechkar, C. Butler, F. Levet, M. Cabillic, O. Rossier, G. Giannone, R. Galland, D. Choquet, and J.-B. Sibarita, “Localization-based super-resolution imaging meets high-content screening,” Nat. Methods 14(12), 1184–1190 (2017).
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Girirajan, T. P. K.

S. T. Hess, T. P. K. Girirajan, and M. D. Mason, “Ultra-high resolution imaging by fluorescence photoactivation localization microscopy,” Biophys. J. 91(11), 4258–4272 (2006).
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Grace, M. R.

A. E. S. Barentine, Y. Lin, M. Liu, P. Kidd, L. Balduf, M. R. Grace, S. Wang, J. Bewersdorf, and D. Baddeley, “3D Multicolor Nanoscopy at 10,000 Cells a Day,” bioRxiv, 606954 (2019).

Grünwald, D.

R. P. J. Nieuwenhuizen, K. A. Lidke, M. Bates, D. L. Puig, D. Grünwald, S. Stallinga, and B. Rieger, “Measuring image resolution in optical nanoscopy,” Nat. Methods 10(6), 557–562 (2013).
[Crossref]

Hagen, G. M.

D. Sage, T.-A. Pham, H. Babcock, T. Lukes, T. Pengo, J. Chao, R. Velmurugan, A. Herbert, A. Agrawal, S. Colabrese, A. Wheeler, A. Archetti, B. Rieger, R. Ober, G. M. Hagen, J.-B. Sibarita, J. Ries, R. Henriques, M. Unser, and S. Holden, “Super-resolution fight club: assessment of 2D and 3D single-molecule localization microscopy software,” Nat. Methods 16(5), 387–395 (2019).
[Crossref]

M. Ovesný, P. Křížek, J. Borkovec, Z. Švindrych, and G. M. Hagen, “ThunderSTORM: a comprehensive ImageJ plug-in for PALM and STORM data analysis and super-resolution imaging,” Bioinformatics 30(16), 2389–2390 (2014).
[Crossref]

Hao, X.

W. Ouyang, A. Aristov, M. Lelek, X. Hao, and C. Zimmer, “Deep learning massively accelerates super-resolution localization microscopy,” Nat. Biotechnol. 36(5), 460–468 (2018).
[Crossref]

Hartwich, T. M. P.

F. Huang, T. M. P. Hartwich, F. E. Rivera-Molina, Y. Lin, W. C. Duim, J. J. Long, P. D. Uchil, J. R. Myers, M. A. Baird, W. Mothes, M. W. Davidson, D. Toomre, and J. Bewersdorf, “Video-rate nanoscopy using sCMOS camera-specific single-molecule localization algorithms,” Nat. Methods 10(7), 653–658 (2013).
[Crossref]

He, J.

S. A. Jones, S.-H. Shim, J. He, and X. Zhuang, “Fast, three-dimensional super-resolution imaging of live cells,” Nat. Methods 8(6), 499–505 (2011).
[Crossref]

Hedde, P. N.

Heidbreder, M.

S. van de Linde, A. Löschberger, T. Klein, M. Heidbreder, S. Wolter, M. Heilemann, and M. Sauer, “Direct stochastic optical reconstruction microscopy with standard fluorescent probes,” Nat. Protoc. 6(7), 991–1009 (2011).
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Heilemann, M.

A. Kechkar, D. Nair, M. Heilemann, D. Choquet, and J.-B. Sibarita, “Real-Time Analysis and Visualization for Single-Molecule Based Super-Resolution Microscopy,” PLoS One 8(4), e62918 (2013).
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S. van de Linde, A. Löschberger, T. Klein, M. Heidbreder, S. Wolter, M. Heilemann, and M. Sauer, “Direct stochastic optical reconstruction microscopy with standard fluorescent probes,” Nat. Protoc. 6(7), 991–1009 (2011).
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Henriques, R.

D. Sage, T.-A. Pham, H. Babcock, T. Lukes, T. Pengo, J. Chao, R. Velmurugan, A. Herbert, A. Agrawal, S. Colabrese, A. Wheeler, A. Archetti, B. Rieger, R. Ober, G. M. Hagen, J.-B. Sibarita, J. Ries, R. Henriques, M. Unser, and S. Holden, “Super-resolution fight club: assessment of 2D and 3D single-molecule localization microscopy software,” Nat. Methods 16(5), 387–395 (2019).
[Crossref]

P. Almada, S. Culley, and R. Henriques, “PALM and STORM: Into large fields and high-throughput microscopy with sCMOS detectors,” Methods 88, 109–121 (2015).
[Crossref]

Herbert, A.

D. Sage, T.-A. Pham, H. Babcock, T. Lukes, T. Pengo, J. Chao, R. Velmurugan, A. Herbert, A. Agrawal, S. Colabrese, A. Wheeler, A. Archetti, B. Rieger, R. Ober, G. M. Hagen, J.-B. Sibarita, J. Ries, R. Henriques, M. Unser, and S. Holden, “Super-resolution fight club: assessment of 2D and 3D single-molecule localization microscopy software,” Nat. Methods 16(5), 387–395 (2019).
[Crossref]

Hess, H. F.

E. Betzig, G. H. Patterson, R. Sougrat, O. W. Lindwasser, S. Olenych, J. S. Bonifacino, M. W. Davidson, J. Lippincott-Schwartz, and H. F. Hess, “Imaging intracellular fluorescent proteins at nanometer resolution,” Science 313(5793), 1642–1645 (2006).
[Crossref]

Hess, S. T.

S. T. Hess, T. P. K. Girirajan, and M. D. Mason, “Ultra-high resolution imaging by fluorescence photoactivation localization microscopy,” Biophys. J. 91(11), 4258–4272 (2006).
[Crossref]

Hoess, P.

Y. Li, M. Mund, P. Hoess, J. Deschamps, U. Matti, B. Nijmeijer, V. J. Sabinina, J. Ellenberg, I. Schoen, and J. Ries, “Real-time 3D single-molecule localization using experimental point spread functions,” Nat. Methods 15(5), 367–369 (2018).
[Crossref]

Holden, S.

D. Sage, T.-A. Pham, H. Babcock, T. Lukes, T. Pengo, J. Chao, R. Velmurugan, A. Herbert, A. Agrawal, S. Colabrese, A. Wheeler, A. Archetti, B. Rieger, R. Ober, G. M. Hagen, J.-B. Sibarita, J. Ries, R. Henriques, M. Unser, and S. Holden, “Super-resolution fight club: assessment of 2D and 3D single-molecule localization microscopy software,” Nat. Methods 16(5), 387–395 (2019).
[Crossref]

J. Min, C. Vonesch, H. Kirshner, L. Carlini, N. Olivier, S. Holden, S. Manley, J. C. Ye, and M. Unser, “FALCON: fast and unbiased reconstruction of high-density super-resolution microscopy data,” Sci. Rep. 4(1), 4577 (2015).
[Crossref]

Holden, S. J.

S. J. Holden, S. Uphoff, and A. N. Kapanidis, “DAOSTORM: an algorithm for high-density super-resolution microscopy,” Nat. Methods 8(4), 279–280 (2011).
[Crossref]

S. J. Holden, T. Pengo, K. L. Meibom, C. F. Fernandez, J. Collier, and S. Manley, “High throughput 3D super-resolution microscopy reveals Caulobacter crescentus in vivo Z-ring organization,” Proc. Natl. Acad. Sci. USA111(12), 4566–4571 (2014).
[Crossref]

Holm, T.

T. Holm, T. Klein, A. Löschberger, T. Klamp, G. Wiebusch, S. van de Linde, and M. Sauer, “A Blueprint for Cost-Efficient Localization Microscopy,” ChemPhysChem 15(4), 651–654 (2014).
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Huang, B.

R. McGorty, D. Kamiyama, and B. Huang, “Active microscope stabilization in three dimensions using image correlation,” Biomed. Opt. Phase Microsc. Nanosc. 2(1), 3 (2013).
[Crossref]

B. Huang, W. Wang, M. Bates, and X. Zhuang, “Three-dimensional super-resolution imaging by stochastic optical reconstruction microscopy,” Science 319(5864), 810–813 (2008).
[Crossref]

Huang, F.

F. Huang, T. M. P. Hartwich, F. E. Rivera-Molina, Y. Lin, W. C. Duim, J. J. Long, P. D. Uchil, J. R. Myers, M. A. Baird, W. Mothes, M. W. Davidson, D. Toomre, and J. Bewersdorf, “Video-rate nanoscopy using sCMOS camera-specific single-molecule localization algorithms,” Nat. Methods 10(7), 653–658 (2013).
[Crossref]

F. Huang, S. L. Schwartz, J. M. Byars, and K. A. Lidke, “Simultaneous multiple-emitter fitting for single molecule super-resolution imaging,” Biomed. Opt. Express 2(5), 1377–1393 (2011).
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Huang, Z.-L.

Hussein, A. A.

E. S. Ahmed, A. I. Volodin, and A. A. Hussein, “Robust weighted likelihood estimation of exponential parameters,” IEEE Trans. Reliab. 54(3), 389–395 (2005).
[Crossref]

Jones, S. A.

S. A. Jones, S.-H. Shim, J. He, and X. Zhuang, “Fast, three-dimensional super-resolution imaging of live cells,” Nat. Methods 8(6), 499–505 (2011).
[Crossref]

Joseph, N.

C. S. Smith, N. Joseph, B. Rieger, and K. A. Lidke, “Fast, single-molecule localization that achieves theoretically minimum uncertainty,” Nat. Methods 7(5), 373–375 (2010).
[Crossref]

Kamiyama, D.

R. McGorty, D. Kamiyama, and B. Huang, “Active microscope stabilization in three dimensions using image correlation,” Biomed. Opt. Phase Microsc. Nanosc. 2(1), 3 (2013).
[Crossref]

Kapanidis, A. N.

S. J. Holden, S. Uphoff, and A. N. Kapanidis, “DAOSTORM: an algorithm for high-density super-resolution microscopy,” Nat. Methods 8(4), 279–280 (2011).
[Crossref]

Kechkar, A.

A. Beghin, A. Kechkar, C. Butler, F. Levet, M. Cabillic, O. Rossier, G. Giannone, R. Galland, D. Choquet, and J.-B. Sibarita, “Localization-based super-resolution imaging meets high-content screening,” Nat. Methods 14(12), 1184–1190 (2017).
[Crossref]

A. Kechkar, D. Nair, M. Heilemann, D. Choquet, and J.-B. Sibarita, “Real-Time Analysis and Visualization for Single-Molecule Based Super-Resolution Microscopy,” PLoS One 8(4), e62918 (2013).
[Crossref]

Kidd, P.

A. E. S. Barentine, Y. Lin, M. Liu, P. Kidd, L. Balduf, M. R. Grace, S. Wang, J. Bewersdorf, and D. Baddeley, “3D Multicolor Nanoscopy at 10,000 Cells a Day,” bioRxiv, 606954 (2019).

Kirshner, H.

D. Sage, H. Kirshner, T. Pengo, N. Stuurman, J. Min, S. Manley, and M. Unser, “Quantitative evaluation of software packages for single-molecule localization microscopy,” Nat. Methods 12(8), 717–724 (2015).
[Crossref]

J. Min, C. Vonesch, H. Kirshner, L. Carlini, N. Olivier, S. Holden, S. Manley, J. C. Ye, and M. Unser, “FALCON: fast and unbiased reconstruction of high-density super-resolution microscopy data,” Sci. Rep. 4(1), 4577 (2015).
[Crossref]

Klamp, T.

T. Holm, T. Klein, A. Löschberger, T. Klamp, G. Wiebusch, S. van de Linde, and M. Sauer, “A Blueprint for Cost-Efficient Localization Microscopy,” ChemPhysChem 15(4), 651–654 (2014).
[Crossref]

Klein, T.

T. Holm, T. Klein, A. Löschberger, T. Klamp, G. Wiebusch, S. van de Linde, and M. Sauer, “A Blueprint for Cost-Efficient Localization Microscopy,” ChemPhysChem 15(4), 651–654 (2014).
[Crossref]

S. van de Linde, A. Löschberger, T. Klein, M. Heidbreder, S. Wolter, M. Heilemann, and M. Sauer, “Direct stochastic optical reconstruction microscopy with standard fluorescent probes,” Nat. Protoc. 6(7), 991–1009 (2011).
[Crossref]

Krížek, P.

M. Ovesný, P. Křížek, J. Borkovec, Z. Švindrych, and G. M. Hagen, “ThunderSTORM: a comprehensive ImageJ plug-in for PALM and STORM data analysis and super-resolution imaging,” Bioinformatics 30(16), 2389–2390 (2014).
[Crossref]

Lécart, S.

P. Bon, N. Bourg, S. Lécart, S. Monneret, E. Fort, J. Wenger, and S. Lévêque-Fort, “Three-dimensional nanometre localization of nanoparticles to enhance super-resolution microscopy,” Nat. Commun. 6(1), 7764 (2015).
[Crossref]

Lee, S. H.

Lelek, M.

W. Ouyang, A. Aristov, M. Lelek, X. Hao, and C. Zimmer, “Deep learning massively accelerates super-resolution localization microscopy,” Nat. Biotechnol. 36(5), 460–468 (2018).
[Crossref]

Lévêque-Fort, S.

P. Bon, N. Bourg, S. Lécart, S. Monneret, E. Fort, J. Wenger, and S. Lévêque-Fort, “Three-dimensional nanometre localization of nanoparticles to enhance super-resolution microscopy,” Nat. Commun. 6(1), 7764 (2015).
[Crossref]

Levet, F.

A. Beghin, A. Kechkar, C. Butler, F. Levet, M. Cabillic, O. Rossier, G. Giannone, R. Galland, D. Choquet, and J.-B. Sibarita, “Localization-based super-resolution imaging meets high-content screening,” Nat. Methods 14(12), 1184–1190 (2017).
[Crossref]

Li, L.

Li, P.

Li, Y.

Y. Li, M. Mund, P. Hoess, J. Deschamps, U. Matti, B. Nijmeijer, V. J. Sabinina, J. Ellenberg, I. Schoen, and J. Ries, “Real-time 3D single-molecule localization using experimental point spread functions,” Nat. Methods 15(5), 367–369 (2018).
[Crossref]

Lidke, K. A.

R. P. J. Nieuwenhuizen, K. A. Lidke, M. Bates, D. L. Puig, D. Grünwald, S. Stallinga, and B. Rieger, “Measuring image resolution in optical nanoscopy,” Nat. Methods 10(6), 557–562 (2013).
[Crossref]

F. Huang, S. L. Schwartz, J. M. Byars, and K. A. Lidke, “Simultaneous multiple-emitter fitting for single molecule super-resolution imaging,” Biomed. Opt. Express 2(5), 1377–1393 (2011).
[Crossref]

C. S. Smith, N. Joseph, B. Rieger, and K. A. Lidke, “Fast, single-molecule localization that achieves theoretically minimum uncertainty,” Nat. Methods 7(5), 373–375 (2010).
[Crossref]

Lin, Y.

F. Huang, T. M. P. Hartwich, F. E. Rivera-Molina, Y. Lin, W. C. Duim, J. J. Long, P. D. Uchil, J. R. Myers, M. A. Baird, W. Mothes, M. W. Davidson, D. Toomre, and J. Bewersdorf, “Video-rate nanoscopy using sCMOS camera-specific single-molecule localization algorithms,” Nat. Methods 10(7), 653–658 (2013).
[Crossref]

A. E. S. Barentine, Y. Lin, M. Liu, P. Kidd, L. Balduf, M. R. Grace, S. Wang, J. Bewersdorf, and D. Baddeley, “3D Multicolor Nanoscopy at 10,000 Cells a Day,” bioRxiv, 606954 (2019).

Lindwasser, O. W.

E. Betzig, G. H. Patterson, R. Sougrat, O. W. Lindwasser, S. Olenych, J. S. Bonifacino, M. W. Davidson, J. Lippincott-Schwartz, and H. F. Hess, “Imaging intracellular fluorescent proteins at nanometer resolution,” Science 313(5793), 1642–1645 (2006).
[Crossref]

Lippincott-Schwartz, J.

E. Betzig, G. H. Patterson, R. Sougrat, O. W. Lindwasser, S. Olenych, J. S. Bonifacino, M. W. Davidson, J. Lippincott-Schwartz, and H. F. Hess, “Imaging intracellular fluorescent proteins at nanometer resolution,” Science 313(5793), 1642–1645 (2006).
[Crossref]

Liu, M.

A. E. S. Barentine, Y. Lin, M. Liu, P. Kidd, L. Balduf, M. R. Grace, S. Wang, J. Bewersdorf, and D. Baddeley, “3D Multicolor Nanoscopy at 10,000 Cells a Day,” bioRxiv, 606954 (2019).

Liu, Y.

H. Ma, J. Xu, and Y. Liu, “WindSTORM: Robust online image processing for high-throughput nanoscopy,” Sci. Adv. 5(4), eaaw0683 (2019).
[Crossref]

H. Ma, R. Fu, J. Xu, and Y. Liu, “A simple and cost-effective setup for super-resolution localization microscopy,” Sci. Rep. 7(1), 1542 (2017).
[Crossref]

Long, F.

Long, J. J.

F. Huang, T. M. P. Hartwich, F. E. Rivera-Molina, Y. Lin, W. C. Duim, J. J. Long, P. D. Uchil, J. R. Myers, M. A. Baird, W. Mothes, M. W. Davidson, D. Toomre, and J. Bewersdorf, “Video-rate nanoscopy using sCMOS camera-specific single-molecule localization algorithms,” Nat. Methods 10(7), 653–658 (2013).
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Figures (12)

Fig. 1.
Fig. 1. Principle of MLEwt for sparse emitter localization with signal contamination. (a) Comparison on the recovered signal from conventional MLE (MLEbfgs, upper) and weighted MLE (MLEwt, lower). A contaminated ROI (11 × 11 pixels) is extracted from a raw image taken from astigmatism 3D imaging, and is processed using either MLEbfgs or MLEwt. The signal is recovered using the fitted parameters. Note that this ROI can be also fitted using a multi-emitter model at the expense of a slow data processing speed. (b) MLE loss maps from an ROI with signal contamination. In both maps, the fitting parameters other than x and y positions were fixed and adopted from the fitted result of MLEwt. (c) Averaged horizontal intensity profile of the extracted ROI in (a). The σleft and σright denote the estimated standard deviation width (in pixel) for the Gaussian weight function in the left and right sides, respectively.
Fig. 2.
Fig. 2. The workflow for ROI identification and extraction.
Fig. 3.
Fig. 3. MLE fitting using the divide and conquer strategy. (a) The workflow. (b-c) The percentage of ROIs containing different number of emitters under different activation density. Here (b) is for 2D, and (c) is for astigmatism 3D raw images.
Fig. 4.
Fig. 4. Comparison on the localization performance among MLEbfgs, MLEwt and ThunderSTORM for simulated 2D raw images. (a) The dependence of RMSE on activation density. (b) The dependence of Jaccard index on activation density. (c) The dependence of run time on activation density. Here the run time accounts for all data processing routine, including ROI extraction, molecule localization, and super-resolution image rendering, to process a single raw image. The simulated images contains 1024 × 1024 pixels with a pixel size of 100 nm. Both the QC-STORM and the ThunderSTORM were set to work at the sparse emitter mode when the run time was evaluated. Both the MLEbfgs and the MLEwt algorhthms were used when the QC-STORM is working in the sparse emitter mode. The letter S denotes sparse emitter mode.
Fig. 5.
Fig. 5. Comparison on the localization performance among MLEbfgs, MLEwt and ThunderSTORM for simulated astigmatism 3D raw images. (a) The dependence of lateral RMSE on activation density. (b) The dependence of axial RMSE on activation density. (c) The dependence of Jaccard index on activation density. (d) The dependence of run time on activation density. Here the run time accounts for all data processing routine in a single raw image. Other settings are similar to those in Fig. 4.
Fig. 6.
Fig. 6. Comparison on the localization performance of three software for 2D raw images. (a) The dependence of RMSE on activation density. (b) The dependence of Jaccard index on activation density. (c) The dependence of run time on activation density. Here the run time accounts for all data processing routine in a single raw image. Other settings are similar to those in Fig. 4. The letter M denotes multi-emitter mode, and WindSTORM has only a multi-emitter mode. We don’t show the run time of WindSTORM, since the GPU version of WindSTORM is not running correctly under our hardware configurations.
Fig. 7.
Fig. 7. Comparison on the localization performance of ThunderSTORM and QC-STORM for astigmatism 3D raw images. (a-b) The dependence of lateral and axial RMSE on activation density. (c) The dependence of Jaccard index on activation density. (d) The dependence of run time on activation density. Here the run time accounts for all data processing time in a single image of 1024 × 1024 pixels. The letter M denotes multi-emitter mode.
Fig. 8.
Fig. 8. Comparison on the localization performance of three software using open datasets. (a) Evaluation of RMSE and Jaccard index on four 2D imaging datasets. (b) Evaluation of lateral and axial RMSE, and Jaccard index on four astigmatism 3D imaging datasets. The acronym LD and HD denote low density and high density, respectively. MT1 and MT2 are high SNR datasets. MT3, MT4, ER1 and ER2 are low SNR datasets.
Fig. 9.
Fig. 9. Evaluation of the localization performance among QC-STORM, ThunderSTORM and WindSTORM using experimental 2D images. (a) A super-resolution image reconstructed from a total of 1000 raw images with 1024 × 1024 pixels. The images were processed by QC-STORM. The estimated full data processing times for different software are shown in the top-right corner. (b) Enlarged super-resolution images of the boxed region in (a). A representative raw image shows a non-uniform fluorescence background. Three software were used to process the raw images independently. The FRC resolution and the total number of localizations are shown in the lower-right corners. (c) Enlarged super-resolution images of the two ROIs indicated in (b). The upper row shows an area with high fluorescence background, and the lower row is for an area with low fluorescence background. The localization number and the FRC resolution of these ROIs are also shown in these images. (d) Spatial resolution characterized by the intensity profiles of the marked positions in (c).
Fig. 10.
Fig. 10. Evaluation of the localization performance between QC-STORM and ThunderSTORM using an experimental 3D open dataset. (a) A super-resolution image reconstructed from QC-STORM. (b) Enlarged super-resolution images reconstructed from the two software. The images correspond to the marked area in (a). The upper images were processed from the original open dataset with low activation density, while the lower images were processed from a modified open dataset with high activation density. The FRC resolution and the total localization number are shown in the upper-left corners. (c) Spatial resolution characterized by the intensity profiles of two microtubules at the marked positions in (b).
Fig. 11.
Fig. 11. Real-time feedback control on image SNR and activation density. (a-b) The dependence of normalized SNR and total signal photon on the number of raw image frames. The axial drift correction is turned ON (with correction) or OFF (no correction). (c-d) The dependence of the number of localized molecules and the percentage of sparse emitter localization on the number of raw image frames. The activation density control is turned ON (with feedback) or OFF (no feedback).
Fig. 12.
Fig. 12. The improvement of imaging speed after combining ANNA-PALM with QC-STORM. (a) A super-resolution image reconstructed from QC-STORM. Here a total of 800 raw images was used, and the FOV equals to 80 µm × 86 µm. (b) Super-resolution images reconstructed from different number of raw images. These images were originated from the rectangular area marked in (a). QC-STORM or a combination of QC-STORM and ANNA-PALM was used to process the raw images. (c) Line profiles of the marked areas in (b).

Equations (8)

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I i , j = A e ( ( i x 0 ) 2 2 σ x 2 + ( j y 0 ) 2 2 σ y 2 ) + B
min L = 1 i , j N ( I i , j q i , j ln I i , j )
min L = 1 i , j N F i , j = 1 i , j N ( I i , j q i , j q i , j ( ln I i , j ln q i , j ) )
I i , j = 128 × A e 0.1 × σ ( ( i x 0 ) 2 + ( j y 0 ) 2 ) + 64 × B
min L = 1 i , j N W i , j F i , j
W i , j = e ( ( i x w ) 2 2 σ w x 2 + ( j y w ) 2 2 σ w y 2 )
0   +   A e x 2 2 σ 2 d x = A σ π 2
I i , j = k = 1 M A k e ( ( i x 0 k ) 2 2 σ x k 2 + ( j y 0 k ) 2 2 σ y k 2 ) + B

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