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Current Directions in Biomedical Engineering

Joint Journal of the German Society for Biomedical Engineering in VDE and the Austrian and Swiss Societies for Biomedical Engineering

Editor-in-Chief: Dössel, Olaf

Editorial Board: Augat, Peter / Buzug, Thorsten M. / Haueisen, Jens / Jockenhoevel, Stefan / Knaup-Gregori, Petra / Kraft, Marc / Lenarz, Thomas / Leonhardt, Steffen / Malberg, Hagen / Penzel, Thomas / Plank, Gernot / Radermacher, Klaus M. / Schkommodau, Erik / Stieglitz, Thomas / Urban, Gerald A.


CiteScore 2018: 0.47

Source Normalized Impact per Paper (SNIP) 2018: 0.377

Open Access
Online
ISSN
2364-5504
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Comparing human and algorithmic tracking of subviral particles in fluorescence microscopic image sequences

Dennis Müller
  • Corresponding author
  • Technische Hochschule Mittelhessen, Dept. Life Science Engineering, Wiesenstraße 14, 35390 Giessen, Germany
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/ Andreas Rausch
  • Technische Hochschule Mittelhessen, Dept. Life Science Engineering, Wiesenstraße 14, 35390 Giessen, Germany
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/ Olga Dolnik
  • Philipps-Universität Marburg, Institut für Virologie, Hans-Meerwein-Straße 2, 35043 Marburg, Germany
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/ Thomas Schanze
  • Technische Hochschule Mittelhessen, Dept. Life Science Engineering, Wiesenstraße 14, 35390 Giessen, Germany
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Published Online: 2017-09-07 | DOI: https://doi.org/10.1515/cdbme-2017-0114

Abstract

Tracking of subviral particles with automated methods enables the analysis of intracellular processes exhibited by viruses. A linear assignment problem solver and a Kalman-filter have been added to an existing particle tracking algorithm. First results produced with simulated image sequences showed that the improved algorithm is able to improve tracking results by closing gaps in the particle’s trajectories. Here we report on the evaluation of the LAP-Kalman algorithm using real fluorescence-microscopic images. The results from the original and improved algorithm have been compared to the results of manual tracking. Evaluation results indicate that the improved algorithm is capable to reconstruct missing parts of particle tracks in difficult conditions. However, the evaluation of the algorithms and the manual tracking is a complex task because of the low image contrast and high object density with intersecting tracks in the live-cell images.

Keywords: Fluorescence microscopy; Subviral particles; Tracking; Detection; Evaluation

About the article

Published Online: 2017-09-07


Citation Information: Current Directions in Biomedical Engineering, Volume 3, Issue 2, Pages 543–547, ISSN (Online) 2364-5504, DOI: https://doi.org/10.1515/cdbme-2017-0114.

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©2017 Dennis Müller et al., published by De Gruyter. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

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