An active particle-based tracking framework for 2D and 3D time-lapse microscopy images
An active particle-based tracking framework for 2D and 3D time-lapse microscopy images
The process required to track cellular structures is a key task in the study of cell migration. This allows the accurate estimation of motility indicators that help in the understanding of mechanisms behind various biological processes. This paper reports a particle-based fully automatic tracking framework that is able to quantify the motility of living cells in time-lapse images. Contrary to the standard tracking methods based on predefined motion models, in this paper we reformulate the tracking mechanism as a data driven optimization process to remove its reliance on a priory motion models. The proposed method has been evaluated using 2D and 3D deconvolved epifluorescent in-vivo image sequences that describe the development of the quail embryo.
Algorithms, Animals, Cell Movement, Electronic Data Processing, Fluorescent Dyes/pharmacology, Green Fluorescent Proteins/metabolism, Image Processing, Computer-Assisted, Imaging, Three-Dimensional/methods, Microscopy/methods, Microscopy, Fluorescence/methods, Models, Statistical, Models, Theoretical, Motion, Quail, Signal Processing, Computer-Assisted
6613-6618
Hossain, M Julius
bba1b875-7604-462b-a55b-ba0b54f728e8
Whelan, Paul F
8f491dab-3987-4dcb-886f-343fd227fc3c
Czirok, Andras
d14053da-371a-4a71-bf44-fa3d79cf5bd2
Ghita, Ovidiu
48aa245e-63b2-445d-bda0-d1cfeca9d7ab
2011
Hossain, M Julius
bba1b875-7604-462b-a55b-ba0b54f728e8
Whelan, Paul F
8f491dab-3987-4dcb-886f-343fd227fc3c
Czirok, Andras
d14053da-371a-4a71-bf44-fa3d79cf5bd2
Ghita, Ovidiu
48aa245e-63b2-445d-bda0-d1cfeca9d7ab
Hossain, M Julius, Whelan, Paul F, Czirok, Andras and Ghita, Ovidiu
(2011)
An active particle-based tracking framework for 2D and 3D time-lapse microscopy images.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2011, .
(doi:10.1109/IEMBS.2011.6091631).
Abstract
The process required to track cellular structures is a key task in the study of cell migration. This allows the accurate estimation of motility indicators that help in the understanding of mechanisms behind various biological processes. This paper reports a particle-based fully automatic tracking framework that is able to quantify the motility of living cells in time-lapse images. Contrary to the standard tracking methods based on predefined motion models, in this paper we reformulate the tracking mechanism as a data driven optimization process to remove its reliance on a priory motion models. The proposed method has been evaluated using 2D and 3D deconvolved epifluorescent in-vivo image sequences that describe the development of the quail embryo.
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More information
Published date: 2011
Keywords:
Algorithms, Animals, Cell Movement, Electronic Data Processing, Fluorescent Dyes/pharmacology, Green Fluorescent Proteins/metabolism, Image Processing, Computer-Assisted, Imaging, Three-Dimensional/methods, Microscopy/methods, Microscopy, Fluorescence/methods, Models, Statistical, Models, Theoretical, Motion, Quail, Signal Processing, Computer-Assisted
Identifiers
Local EPrints ID: 467288
URI: http://eprints.soton.ac.uk/id/eprint/467288
ISSN: 2375-7477
PURE UUID: 81178dc7-2f6a-4a17-b455-64b5fbfb52bc
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Date deposited: 05 Jul 2022 16:44
Last modified: 17 Mar 2024 04:12
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Contributors
Author:
M Julius Hossain
Author:
Paul F Whelan
Author:
Andras Czirok
Author:
Ovidiu Ghita
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