• DocumentCode
    617542
  • Title

    Image-based representation and modeling of spatiotemporal cell dynamics

  • Author

    Ge Yang ; Olivo-Marin, Jean-Christophe

  • fYear
    2013
  • fDate
    7-11 April 2013
  • Firstpage
    1198
  • Lastpage
    1201
  • Abstract
    Successful completion of dynamic cellular processes ranging from intracellular transport to embryonic development depends critically on precise spatial and temporal coordination of the molecules and cells involved. Understanding spatiotemporal behaviors of these molecules and cells is therefore essential to understanding mechanisms of their associated cellular processes. Over the past two decades, a wide variety of image feature tracking techniques have been developed for recovery of spatiotemporal trajectories of molecules and cells from their images. From these trajectories, simple descriptors such as velocities or diffusion coefficients are often calculated for behavior characterization. However, for complex cellular processes, these descriptors cannot fully characterize or represent spatiotemporal behaviors of the molecules and cells involved. Instead, comprehensive computational representations and models become essential. This short paper introduces a special session that we organize to invite investigators to present their work related to this important emerging topic in biological imaging. We illustrate the necessity for computational representation and modeling of spatiotemporal cell dynamics using a specific example and review briefly some of the key technical challenges to be addressed. We conclude with an overview of the invited presentations.
  • Keywords
    biodiffusion; biological techniques; cellular transport; molecular biophysics; optical images; optical microscopy; physiological models; spatiotemporal phenomena; biological imaging; biomolecules; cellular transport; descriptors; diffusion coefficient; dynamic cellular processes; image feature tracking method; image-based representation; spatiotemporal cell dynamics; Biology; Computational modeling; Computer architecture; Hidden Markov models; Microprocessors; Spatiotemporal phenomena; Trajectory; computational representation; feature tracking; modeling; spatiotemporal cell dynamics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Imaging (ISBI), 2013 IEEE 10th International Symposium on
  • Conference_Location
    San Francisco, CA
  • ISSN
    1945-7928
  • Print_ISBN
    978-1-4673-6456-0
  • Type

    conf

  • DOI
    10.1109/ISBI.2013.6556695
  • Filename
    6556695