Tracking of Particles in Fluorescence Microscopy Images Using a Spatial Distance Model for Brownian Motion

R. Spilger; J. Hellgoth; J.-Y. Lee; S. Hanselmann; D.-P. Herten; R. Bartenschlager; K. Rohr

doi:10.1109/ISBI45749.2020.9098729

Tracking of Particles in Fluorescence Microscopy Images Using a Spatial Distance Model for Brownian Motion

R. Spilger, J. Hellgoth, J.-Y. Lee, S. Hanselmann, D.-P. Herten, R. Bartenschlager, K. Rohr

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Automatic tracking of particles in fluorescence microscopy images is an important task to quantify the dynamic behavior of subcellular and virus structures. We present a novel iterative approach for tracking multiple particles in microscopy data based on a spatial distance model derived under Brownian motion. Our approach exploits the information that the most likely object position at the next time point is at a certain distance from the current position. Information from all particles in a temporal image sequence are combined and all motion-specific parameters are automatically estimated. Experiments using data of the Particle Tracking Challenge as well as real live cell microscopy data displaying hepatocyte growth factor receptors and virus structures show that our approach outperforms previous methods.

Original language	English
Title of host publication	Proceedings - International Symposium on Biomedical Imaging
Pages	969-972
Number of pages	4
ISBN (Electronic)	9781538693308
DOIs	https://doi.org/10.1109/ISBI45749.2020.9098729
Publication status	Published - 2020

Publication series

Name	Proceedings - International Symposium on Biomedical Imaging
Volume	2020-April
ISSN (Print)	1945-7928
ISSN (Electronic)	1945-8452

Bibliographical note

Funding Information:
Acknowledgments: This work is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Projektnummer 240245660 - SFB 1129 (projects Z4, P11). JYL and RB acknowledge the microscopy support from the Infectious Diseases Imaging Platform at the CIID, Heidelberg. We thank Leonid Kostrykin for fruitful discussions.

Publisher Copyright:
© 2020 IEEE.

Keywords

Biomedical imaging
Brownian motion
chi distribution
microscopy images
particle tracking

ASJC Scopus subject areas

Biomedical Engineering
Radiology Nuclear Medicine and imaging

Access to Document

10.1109/ISBI45749.2020.9098729

Cite this

Spilger, R., Hellgoth, J., Lee, J-Y., Hanselmann, S., Herten, D-P., Bartenschlager, R., & Rohr, K. (2020). Tracking of Particles in Fluorescence Microscopy Images Using a Spatial Distance Model for Brownian Motion. In Proceedings - International Symposium on Biomedical Imaging (pp. 969-972). Article 9098729 (Proceedings - International Symposium on Biomedical Imaging; Vol. 2020-April). https://doi.org/10.1109/ISBI45749.2020.9098729

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title = "Tracking of Particles in Fluorescence Microscopy Images Using a Spatial Distance Model for Brownian Motion",

abstract = "Automatic tracking of particles in fluorescence microscopy images is an important task to quantify the dynamic behavior of subcellular and virus structures. We present a novel iterative approach for tracking multiple particles in microscopy data based on a spatial distance model derived under Brownian motion. Our approach exploits the information that the most likely object position at the next time point is at a certain distance from the current position. Information from all particles in a temporal image sequence are combined and all motion-specific parameters are automatically estimated. Experiments using data of the Particle Tracking Challenge as well as real live cell microscopy data displaying hepatocyte growth factor receptors and virus structures show that our approach outperforms previous methods.",

keywords = "Biomedical imaging, Brownian motion, chi distribution, microscopy images, particle tracking",

author = "R. Spilger and J. Hellgoth and J.-Y. Lee and S. Hanselmann and D.-P. Herten and R. Bartenschlager and K. Rohr",

note = "Funding Information: Acknowledgments: This work is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Projektnummer 240245660 - SFB 1129 (projects Z4, P11). JYL and RB acknowledge the microscopy support from the Infectious Diseases Imaging Platform at the CIID, Heidelberg. We thank Leonid Kostrykin for fruitful discussions. Publisher Copyright: {\textcopyright} 2020 IEEE.",

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doi = "10.1109/ISBI45749.2020.9098729",

language = "English",

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series = "Proceedings - International Symposium on Biomedical Imaging",

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Spilger, R, Hellgoth, J, Lee, J-Y, Hanselmann, S, Herten, D-P, Bartenschlager, R & Rohr, K 2020, Tracking of Particles in Fluorescence Microscopy Images Using a Spatial Distance Model for Brownian Motion. in Proceedings - International Symposium on Biomedical Imaging., 9098729, Proceedings - International Symposium on Biomedical Imaging, vol. 2020-April, pp. 969-972. https://doi.org/10.1109/ISBI45749.2020.9098729

Tracking of Particles in Fluorescence Microscopy Images Using a Spatial Distance Model for Brownian Motion. / Spilger, R.; Hellgoth, J.; Lee, J.-Y. et al.
Proceedings - International Symposium on Biomedical Imaging. 2020. p. 969-972 9098729 (Proceedings - International Symposium on Biomedical Imaging; Vol. 2020-April).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Herten, D.-P.

AU - Bartenschlager, R.

AU - Rohr, K.

N1 - Funding Information: Acknowledgments: This work is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Projektnummer 240245660 - SFB 1129 (projects Z4, P11). JYL and RB acknowledge the microscopy support from the Infectious Diseases Imaging Platform at the CIID, Heidelberg. We thank Leonid Kostrykin for fruitful discussions. Publisher Copyright: © 2020 IEEE.

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AB - Automatic tracking of particles in fluorescence microscopy images is an important task to quantify the dynamic behavior of subcellular and virus structures. We present a novel iterative approach for tracking multiple particles in microscopy data based on a spatial distance model derived under Brownian motion. Our approach exploits the information that the most likely object position at the next time point is at a certain distance from the current position. Information from all particles in a temporal image sequence are combined and all motion-specific parameters are automatically estimated. Experiments using data of the Particle Tracking Challenge as well as real live cell microscopy data displaying hepatocyte growth factor receptors and virus structures show that our approach outperforms previous methods.

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Spilger R, Hellgoth J, Lee J-Y, Hanselmann S, Herten D-P, Bartenschlager R et al. Tracking of Particles in Fluorescence Microscopy Images Using a Spatial Distance Model for Brownian Motion. In Proceedings - International Symposium on Biomedical Imaging. 2020. p. 969-972. 9098729. (Proceedings - International Symposium on Biomedical Imaging). doi: 10.1109/ISBI45749.2020.9098729

Tracking of Particles in Fluorescence Microscopy Images Using a Spatial Distance Model for Brownian Motion

Abstract

Publication series

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this