K-factor image deshadowing for three-dimensional fluorescence microscopy

The ability to track single fluorescent particles within a three dimensional (3D) cellular environment can provide valuable insights into cellular processes. In this paper, we present a modified nonlinear image decomposition technique called K-factor that reshapes the 3D point spread function (PSF)...

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Detalles Bibliográficos
Autores principales: Ilovitsh, Tali, Weiss, Aryeh, Meiri, Amihai, Ebeling, Carl G., Amiel, Aliza, Katz, Hila, Mannasse-Green, Batya, Zalevsky, Zeev
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2015
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4558540/
https://www.ncbi.nlm.nih.gov/pubmed/26333693
http://dx.doi.org/10.1038/srep13724
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author Ilovitsh, Tali
Weiss, Aryeh
Meiri, Amihai
Ebeling, Carl G.
Amiel, Aliza
Katz, Hila
Mannasse-Green, Batya
Zalevsky, Zeev
author_facet Ilovitsh, Tali
Weiss, Aryeh
Meiri, Amihai
Ebeling, Carl G.
Amiel, Aliza
Katz, Hila
Mannasse-Green, Batya
Zalevsky, Zeev
author_sort Ilovitsh, Tali
collection PubMed
description The ability to track single fluorescent particles within a three dimensional (3D) cellular environment can provide valuable insights into cellular processes. In this paper, we present a modified nonlinear image decomposition technique called K-factor that reshapes the 3D point spread function (PSF) of an XYZ image stack into a narrow Gaussian profile. The method increases localization accuracy by ~60% with compare to regular Gaussian fitting, and improves minimal resolvable distance between overlapping PSFs by ~50%. The algorithm was tested both on simulated data and experimentally.
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spelling pubmed-45585402015-09-11 K-factor image deshadowing for three-dimensional fluorescence microscopy Ilovitsh, Tali Weiss, Aryeh Meiri, Amihai Ebeling, Carl G. Amiel, Aliza Katz, Hila Mannasse-Green, Batya Zalevsky, Zeev Sci Rep Article The ability to track single fluorescent particles within a three dimensional (3D) cellular environment can provide valuable insights into cellular processes. In this paper, we present a modified nonlinear image decomposition technique called K-factor that reshapes the 3D point spread function (PSF) of an XYZ image stack into a narrow Gaussian profile. The method increases localization accuracy by ~60% with compare to regular Gaussian fitting, and improves minimal resolvable distance between overlapping PSFs by ~50%. The algorithm was tested both on simulated data and experimentally. Nature Publishing Group 2015-09-03 /pmc/articles/PMC4558540/ /pubmed/26333693 http://dx.doi.org/10.1038/srep13724 Text en Copyright © 2015, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Ilovitsh, Tali
Weiss, Aryeh
Meiri, Amihai
Ebeling, Carl G.
Amiel, Aliza
Katz, Hila
Mannasse-Green, Batya
Zalevsky, Zeev
K-factor image deshadowing for three-dimensional fluorescence microscopy
title K-factor image deshadowing for three-dimensional fluorescence microscopy
title_full K-factor image deshadowing for three-dimensional fluorescence microscopy
title_fullStr K-factor image deshadowing for three-dimensional fluorescence microscopy
title_full_unstemmed K-factor image deshadowing for three-dimensional fluorescence microscopy
title_short K-factor image deshadowing for three-dimensional fluorescence microscopy
title_sort k-factor image deshadowing for three-dimensional fluorescence microscopy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4558540/
https://www.ncbi.nlm.nih.gov/pubmed/26333693
http://dx.doi.org/10.1038/srep13724
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