Smoothness correction for better SOFI imaging

Abstract Sub-diffraction or super-resolution fluorescence imaging allows the visualization of the cellular morphology and interactions at the nanoscale. Statistical analysis methods such as super-resolution optical fluctuation imaging (SOFI) obtain an improved spatial resolution by analyzing fluorop...

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Main Authors: Siewert Hugelier, Wim Vandenberg, Tomáš Lukeš, Kristin S. Grußmayer, Paul H. C. Eilers, Peter Dedecker, Cyril Ruckebusch
Format: Article
Language:English
Published: Nature Publishing Group 2021-04-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-021-87164-4
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spelling doaj-f9a2e049d318479aae5d45359e047cf92021-04-11T11:30:55ZengNature Publishing GroupScientific Reports2045-23222021-04-011111910.1038/s41598-021-87164-4Smoothness correction for better SOFI imagingSiewert Hugelier0Wim Vandenberg1Tomáš Lukeš2Kristin S. Grußmayer3Paul H. C. Eilers4Peter Dedecker5Cyril Ruckebusch6Laboratory for Nanobiology, KU LeuvenLaboratory for Nanobiology, KU LeuvenLaboratory of Nanoscale Biology, École Polytechnique Fédérale de LausanneLaboratory of Nanoscale Biology, École Polytechnique Fédérale de LausanneErasmus University Medical CentreLaboratory for Nanobiology, KU LeuvenUniversity of Lille, CNRS, UMR 8516, LASIREAbstract Sub-diffraction or super-resolution fluorescence imaging allows the visualization of the cellular morphology and interactions at the nanoscale. Statistical analysis methods such as super-resolution optical fluctuation imaging (SOFI) obtain an improved spatial resolution by analyzing fluorophore blinking but can be perturbed by the presence of non-stationary processes such as photodestruction or fluctuations in the illumination. In this work, we propose to use Whittaker smoothing to remove these smooth signal trends and retain only the information associated to independent blinking of the emitters, thus enhancing the SOFI signals. We find that our method works well to correct photodestruction, especially when it occurs quickly. The resulting images show a much higher contrast, strongly suppressed background and a more detailed visualization of cellular structures. Our method is parameter-free and computationally efficient, and can be readily applied on both two-dimensional and three-dimensional data.https://doi.org/10.1038/s41598-021-87164-4
collection DOAJ
language English
format Article
sources DOAJ
author Siewert Hugelier
Wim Vandenberg
Tomáš Lukeš
Kristin S. Grußmayer
Paul H. C. Eilers
Peter Dedecker
Cyril Ruckebusch
spellingShingle Siewert Hugelier
Wim Vandenberg
Tomáš Lukeš
Kristin S. Grußmayer
Paul H. C. Eilers
Peter Dedecker
Cyril Ruckebusch
Smoothness correction for better SOFI imaging
Scientific Reports
author_facet Siewert Hugelier
Wim Vandenberg
Tomáš Lukeš
Kristin S. Grußmayer
Paul H. C. Eilers
Peter Dedecker
Cyril Ruckebusch
author_sort Siewert Hugelier
title Smoothness correction for better SOFI imaging
title_short Smoothness correction for better SOFI imaging
title_full Smoothness correction for better SOFI imaging
title_fullStr Smoothness correction for better SOFI imaging
title_full_unstemmed Smoothness correction for better SOFI imaging
title_sort smoothness correction for better sofi imaging
publisher Nature Publishing Group
series Scientific Reports
issn 2045-2322
publishDate 2021-04-01
description Abstract Sub-diffraction or super-resolution fluorescence imaging allows the visualization of the cellular morphology and interactions at the nanoscale. Statistical analysis methods such as super-resolution optical fluctuation imaging (SOFI) obtain an improved spatial resolution by analyzing fluorophore blinking but can be perturbed by the presence of non-stationary processes such as photodestruction or fluctuations in the illumination. In this work, we propose to use Whittaker smoothing to remove these smooth signal trends and retain only the information associated to independent blinking of the emitters, thus enhancing the SOFI signals. We find that our method works well to correct photodestruction, especially when it occurs quickly. The resulting images show a much higher contrast, strongly suppressed background and a more detailed visualization of cellular structures. Our method is parameter-free and computationally efficient, and can be readily applied on both two-dimensional and three-dimensional data.
url https://doi.org/10.1038/s41598-021-87164-4
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