K-factor image deshadowing for three-dimensional fluorescence microscopy

Tali Ilovitsh; Aryeh Weiss; Amihai Meiri; Carl G. Ebeling; Aliza Amiel; Hila Katz; Batya Mannasse-Green; Zeev Zalevsky

doi:10.1038/srep13724

K-factor image deshadowing for three-dimensional fluorescence microscopy

Tali Ilovitsh^*
, Aryeh Weiss
, Amihai Meiri
, Carl G. Ebeling
, Aliza Amiel
, Hila Katz
, Batya Mannasse-Green
, Zeev Zalevsky

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

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.

Original language	English
Article number	13724
Journal	Scientific Reports
Volume	5
DOIs	https://doi.org/10.1038/srep13724
State	Published - 3 Sep 2015
Externally published	Yes

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10.1038/srep13724

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abstract = "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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AU - Ilovitsh, Tali

AU - Weiss, Aryeh

AU - Meiri, Amihai

AU - Ebeling, Carl G.

AU - Amiel, Aliza

AU - Katz, Hila

AU - Mannasse-Green, Batya

AU - Zalevsky, Zeev

PY - 2015/9/3

Y1 - 2015/9/3

N2 - 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.

AB - 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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K-factor image deshadowing for three-dimensional fluorescence microscopy

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