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    On-line Tracking of Cells and Their Lineage from Time Lapse Video Data

    Access Status
    Fulltext not available
    Authors
    Dat Nguyen, T.
    Kim, Du Yong
    Date
    2018
    Type
    Conference Paper
    
    Metadata
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    Citation
    Dat Nguyen, T. and Kim, D.Y. 2018. On-line Tracking of Cells and Their Lineage from Time Lapse Video Data, 7th International Conference on Control Automation and Information Sciences (ICCAIS), pp. 291-296: IEEE.
    Source Title
    ICCAIS 2018 - 7th International Conference on Control, Automation and Information Sciences
    Source Conference
    7th International Conference on Control Automation and Information Sciences (ICCAIS)
    DOI
    10.1109/ICCAIS.2018.8570546
    ISBN
    9781538660201
    School
    School of Electrical Engineering, Computing and Mathematical Science (EECMS)
    Funding and Sponsorship
    http://purl.org/au-research/grants/arc/DP160104662
    URI
    http://hdl.handle.net/20.500.11937/73834
    Collection
    • Curtin Research Publications
    Abstract

    © 2018 IEEE. In this paper, we propose an algorithm for tracking cells that also provides lineage information. Our approach incorporates cell spawning into the random finite set dynamic model of the cell population, which allows the Bayes multi-object filter to capture information on the cells ancestries. A generalized Labeled Multi-Bernoulli (GLMB) filter (with cell spawning model) is applied to track the cells using detections extracted from time lapse video data. Numerical results on a set of stems cells demonstrate the capability of the proposed solution to track the time-varying number of cells as well as their ancestries.

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