Journal of Clinical Monitoring and Computing

, Volume 19, Issue 4, pp 339–349

Grid-enabling medical image analysis

Authors

    • Laboratoire de Recherche en Informatique (LRI) – CNRSUniversité Paris-Sud
    • Laboratoire de Physique Corpusculaire (LPC) – CNRS
  • V. Breton
    • Laboratoire de Physique Corpusculaire (LPC) – CNRS
  • P. Clarysse
    • CREATIS – CNRS, INSA, INSERM
  • Y. Gaudeau
    • Centre de Recherche en Automatique de Nancy (CRAN) – CNRS, INPLUniversités de Nancy
  • T. Glatard
    • Laboratoire Informatique Signaux et Syst‘emes (I3S) – CNRSUniversité de Nice
  • E. Jeannot
    • Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA) – CNRS, INRIA, INPLUniversités de Nancy
  • Y Legré
    • Laboratoire de Physique Corpusculaire (LPC) – CNRS
  • C. Loomis
    • Laboratoire de l'Accélérateur Linéaire (LAL) – CNRSUniversité Paris-Sud
  • I. Magnin
    • CREATIS – CNRS, INSA, INSERM
  • J. Montagnat
    • Laboratoire Informatique Signaux et Syst‘emes (I3S) – CNRSUniversité de Nice
  • J. -M. Moureaux
    • Centre de Recherche en Automatique de Nancy (CRAN) – CNRS, INPLUniversités de Nancy
  • A. Osorio
    • INRIA Sophia-Antipolis
  • X. Pennec
    • Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur (LIMSI) – CNRS
  • R. Texier
    • Laboratoire de Recherche en Informatique (LRI) – CNRSUniversité Paris-Sud
Article

DOI: 10.1007/s10877-005-0679-9

Cite this article as:
Germain, C., Breton, V., Clarysse, P. et al. J Clin Monit Comput (2005) 19: 339. doi:10.1007/s10877-005-0679-9

Abstract

Grids have emerged as a promising technology to handle the data and compute intensive requirements of many application areas. Digital medical image processing is a promising application area for grids. Given the volume of data, the sensitivity of medical information, and the joint complexity of medical datasets and computations expected in clinical practice, the challenge is to fill the gap between the grid middleware and the requirements of clinical applications. The research project AGIR (Grid Analysis of Radiological Data) presented in this paper addresses this challenge through a combined approach: on one hand, leveraging the grid middleware through core grid medical services which target the requirements of medical data processing applications; on the other hand, grid-enabling a panel of applications ranging from algorithmic research to clinical applications.

Keywords

Grid computingmedical image analysis
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Copyright information

© Springer Science + Business Media, Inc. 2005