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Cellular tracking in time-lapse phase contrast images

Cellular tracking in time-lapse phase contrast images
Cellular tracking in time-lapse phase contrast images

The quantitative analysis of live cells is a key issue in evaluating biological processes. The current clinical practice involves the application of a tedious and time consuming manual tracking procedure on large amount of data. As a result, automatic tracking systems are currently developed and evaluated. However, problems caused by cellular division, agglomeration, Brownian motion and topology changes are difficult issues that have to be accommodated by automatic tracking techniques. In this paper, we detail the development of a fully automated multi-target tracking system that is able to deal with Brownian motion and cellular division. During the tracking process our approach includes the neighbourhood relationship and motion history to enforce the cellular tracking continuity in the spatial and temporal domain. The experimental results reported in this paper indicate that our method is able to accurately track cellular structures in time-lapse data.

77-82
IEEE
Thirusittampalam, K.
923f0260-2c27-4b72-980b-73bea60c73af
Hossain, M. J.
bba1b875-7604-462b-a55b-ba0b54f728e8
Ghita, O.
7f5ca381-bf5f-41e0-9fdb-314ae4185acf
Whelan, P. F.
8f491dab-3987-4dcb-886f-343fd227fc3c
Thirusittampalam, K.
923f0260-2c27-4b72-980b-73bea60c73af
Hossain, M. J.
bba1b875-7604-462b-a55b-ba0b54f728e8
Ghita, O.
7f5ca381-bf5f-41e0-9fdb-314ae4185acf
Whelan, P. F.
8f491dab-3987-4dcb-886f-343fd227fc3c

Thirusittampalam, K., Hossain, M. J., Ghita, O. and Whelan, P. F. (2009) Cellular tracking in time-lapse phase contrast images. In 2009 International Machine Vision and Image Processing Conference: IMVIP. IEEE. pp. 77-82 . (doi:10.1109/IMVIP.2009.21).

Record type: Conference or Workshop Item (Paper)

Abstract

The quantitative analysis of live cells is a key issue in evaluating biological processes. The current clinical practice involves the application of a tedious and time consuming manual tracking procedure on large amount of data. As a result, automatic tracking systems are currently developed and evaluated. However, problems caused by cellular division, agglomeration, Brownian motion and topology changes are difficult issues that have to be accommodated by automatic tracking techniques. In this paper, we detail the development of a fully automated multi-target tracking system that is able to deal with Brownian motion and cellular division. During the tracking process our approach includes the neighbourhood relationship and motion history to enforce the cellular tracking continuity in the spatial and temporal domain. The experimental results reported in this paper indicate that our method is able to accurately track cellular structures in time-lapse data.

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More information

Published date: 4 September 2009
Additional Information: Copyright © 2009, IEEE
Venue - Dates: 2009 13th International Machine Vision and Image Processing Conference, IMVIP 2009, , Dublin, Ireland, 2009-09-02 - 2009-09-04

Identifiers

Local EPrints ID: 469944
URI: http://eprints.soton.ac.uk/id/eprint/469944
PURE UUID: 11a1e7e4-1ed6-4f7a-a67a-e26c55f36bb0
ORCID for M. J. Hossain: ORCID iD orcid.org/0000-0003-3303-5755

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Date deposited: 29 Sep 2022 16:35
Last modified: 17 Mar 2024 04:12

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Contributors

Author: K. Thirusittampalam
Author: M. J. Hossain ORCID iD
Author: O. Ghita
Author: P. F. Whelan

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