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Cell Migration Analysis After In Vitro Wounding Injury with a Multi-Agent Approach

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Abstract

This paper presents a multiagent system for studying in vitro cell motion. A typical application on the wound closure process is presented to illustrate the possibilities of the system, where different image sequences will be treated. The motion issue involves three aspects: image segmentation, object tracking and motion analysis. The current system version focuses mainly on the image segmentation aspect. A general agent model has been designed, which will be further expanded to include tracking and motion analysis behaviors as well. The agents integrate three basic behaviors: perception, interaction and reproduction. The perception evaluates pixels upon static and motion-based criteria. The interaction behavior allows two agents to merge or to negotiate parts of regions. The negotiation can be seen as a segmentation refinement process done by the agents. Finally, the reproduction behavior defines an exploration strategy of the images. Agents can start other agents around them, or they can duplicate themselves in the next frame. The frames are processed in pipeline, where previous information is used to treat the current frame. One unique agent model exist. Agents are specialized on execution time according to their goals. The results, coming from an existing prototype, show different types of cell behavior during cell migration, based on cell nuclei analysis.

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Authors and Affiliations

  1. Laboratoire TIMC/IMAG, Grenoble, France

    Alain Boucher & Catherine Garbay

  2. DyOGen (UPRES n° EA 2021), INSERM U309, Grenoble, France

    Anne Doisy & Xavier Ronot

  3. Laboratoire de Neurobiologie du Développement, E.P.H.E., Montpellier, France

    Anne Doisy

  4. Institut Albert Bonniot, Domaine de la Merci, 38706, La Tronche Cedex, France

    Anne Doisy

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  1. Alain Boucher
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  2. Anne Doisy
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  3. Xavier Ronot
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  4. Catherine Garbay
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Boucher, A., Doisy, A., Ronot, X. et al. Cell Migration Analysis After In Vitro Wounding Injury with a Multi-Agent Approach. Artificial Intelligence Review 12, 137–162 (1998). https://doi.org/10.1023/A:1006500808998

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