Wavelet-based tracking of bacteria in unreconstructed off-axis holograms

Wavelet-based tracking of bacteria in unreconstructed off-axis holograms Methods 136 (2018) 60–65 Contents lists available at ScienceDirect Methods journal homepage: www.elsevier.com/locate/ymeth Wavelet-based tracking of bacteria in unreconstructed off-axis holograms a b,c b a,⇑ Zach Marin , J. Kent Wallace , Jay Nadeau , Andre Khalil CompuMAINE Laboratory, Department of Mathematics & Statistics, University of Maine, Orono, ME 04469, USA The Motility Group, Division of Aerospace Engineering, California Institute of Technology, 1200 E. California Blvd., Pasadena, CA 91125, USA Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr., Pasadena, CA 91109, USA ar ti c l e i nf o ab stra ct Article history: We propose an automated wavelet-based method of tracking particles in unreconstructed off-axis holo- Received 13 July 2017 grams to provide rough estimates of the presence of motion and particle trajectories in digital holo- Received in revised form 2 September 2017 graphic microscopy (DHM) time series. The wavelet transform modulus maxima segmentation method Accepted 5 September 2017 is adapted and tailored to extract Airy-like diffraction disks, which represent bacteria, from DHM time Available online 13 September 2017 series. In this exploratory analysis, the method shows potential for estimating bacterial tracks in low- particle-density time series, based on a preliminary analysis of both http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Methods Elsevier

Wavelet-based tracking of bacteria in unreconstructed off-axis holograms

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Publisher
Elsevier
Copyright
Copyright © 2017 Elsevier Inc.
ISSN
1046-2023
eISSN
1095-9130
D.O.I.
10.1016/j.ymeth.2017.09.003
Publisher site
See Article on Publisher Site

Abstract

Methods 136 (2018) 60–65 Contents lists available at ScienceDirect Methods journal homepage: www.elsevier.com/locate/ymeth Wavelet-based tracking of bacteria in unreconstructed off-axis holograms a b,c b a,⇑ Zach Marin , J. Kent Wallace , Jay Nadeau , Andre Khalil CompuMAINE Laboratory, Department of Mathematics & Statistics, University of Maine, Orono, ME 04469, USA The Motility Group, Division of Aerospace Engineering, California Institute of Technology, 1200 E. California Blvd., Pasadena, CA 91125, USA Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr., Pasadena, CA 91109, USA ar ti c l e i nf o ab stra ct Article history: We propose an automated wavelet-based method of tracking particles in unreconstructed off-axis holo- Received 13 July 2017 grams to provide rough estimates of the presence of motion and particle trajectories in digital holo- Received in revised form 2 September 2017 graphic microscopy (DHM) time series. The wavelet transform modulus maxima segmentation method Accepted 5 September 2017 is adapted and tailored to extract Airy-like diffraction disks, which represent bacteria, from DHM time Available online 13 September 2017 series. In this exploratory analysis, the method shows potential for estimating bacterial tracks in low- particle-density time series, based on a preliminary analysis of both

Journal

MethodsElsevier

Published: Mar 1, 2018

References

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