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Coupling cell detection and tracking by temporal feedback

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F20%3A00341865" target="_blank" >RIV/68407700:21230/20:00341865 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1007/s00138-020-01072-7" target="_blank" >https://doi.org/10.1007/s00138-020-01072-7</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/s00138-020-01072-7" target="_blank" >10.1007/s00138-020-01072-7</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Coupling cell detection and tracking by temporal feedback

  • Original language description

    The tracking-by-detection strategy is the backbone of many methods for tracking living cells in time-lapse microscopy. An object detector is first applied to the input images, and the resulting detection candidates are then linked by a data association module. The performance of such methods strongly depends on the quality of the detector because detection errors propagate to the linking step. To tackle this issue, we propose a joint model for segmentation, detection and tracking. The model is defined implicitly as limiting distribution of a Markov chain Monte Carlo algorithm and contains a temporal feedback, which allows to dynamically alter detector parameters using hints given by neighboring frames and, in this way, correct detection errors. The proposed method can integrate any detector and is therefore not restricted to a specific domain. The parameters of the model are learned using an objective based on empirical risk minimization. We use our method to conduct large-scale experiments for confluent cultures of endothelial cells and evaluate its performance in the ISBI Cell Tracking Challenge, where it consistently scored among the best three methods.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2020

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Machine Vision and Applications

  • ISSN

    0932-8092

  • e-ISSN

    1432-1769

  • Volume of the periodical

    31

  • Issue of the periodical within the volume

    4

  • Country of publishing house

    DE - GERMANY

  • Number of pages

    18

  • Pages from-to

  • UT code for WoS article

    000526453100001

  • EID of the result in the Scopus database

    2-s2.0-85083579824