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Proceedings Paper

Modified K-factor image decomposition for three-dimensional super resolution microscopy
Author(s): Tali Ilovitsh; Aryeh Weiss; Amihai Meiri; Carl G. Ebeling; Aliza Amiel; Hila Katz; Batya Mannasse-Green; Zeev Zalevsky
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Paper 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.

This work presets a novel use of the nonlinear image decomposition technique called K-factor that reshapes the three dimensional (3D) point spread function (PSF) of an XYZ image stack into a narrow Gaussian profile. The experimentally obtained PSF of a Z-stack raw data that is acquired by a widefield microscope has a more elaborate shape that is given by the Gibson and Lanni model. This shape increases the computational complexity associated with the localization routine, when used in localization microscopy techniques. Furthermore, due to its nature, this PSF spreads over a larger volume, making the problem of overlapping emitters detection more pronounced. The ability to use Gaussian fitting with high accuracy on 3D data can facilitate the computational complexity, hence reduce the processing time required for the generation of the 3D superresolved image. In addition it allows the detection of overlapping PSFs and reduces the effects of the penetration of out of focus PSFs into in focused PSFs, therefore enables the increase in the activated fluorophore density by ~50%. The algorithm was tested both on simulated data and experimentally, where it yielded an increase in the localization accuracy by ~60% with compare to regular Gaussian fitting, and improved the minimal resolvable distance between overlapping PSFs by ~50%, making it extremely applicable to the field of 3D biomedical imaging,

Paper Details

Date Published: 9 March 2016
PDF: 7 pages
Proc. SPIE 9713, Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXIII, 97131R (9 March 2016); doi: 10.1117/12.2205970
Show Author Affiliations
Tali Ilovitsh, Bar-Ilan Univ. (Israel)
Aryeh Weiss, Bar-Ilan Univ. (Israel)
Amihai Meiri, The Univ. of Utah (United States)
Carl G. Ebeling, The Univ. of Utah (United States)
Aliza Amiel, Genetic Institute, Meir Medical Ctr. (Israel)
Bar-Ilan Univ. (Israel)
Hila Katz, Genetic Institute, Meir Medical Ctr. (Israel)
Bar-Ilan Univ. (Israel)
Batya Mannasse-Green, Genetic Institute, Meir Medical Ctr. (Israel)
Bar-Ilan Univ. (Israel)
Zeev Zalevsky, Bar-Ilan Univ. (Israel)


Published in SPIE Proceedings Vol. 9713:
Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXIII
Thomas G. Brown; Carol J. Cogswell; Tony Wilson, Editor(s)

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