Journal of Clinical Monitoring and Computing

, Volume 19, Issue 4–5, pp 339–349 | Cite as

Grid-enabling medical image analysis

  • C. GermainEmail author
  • V. Breton
  • P. Clarysse
  • Y. Gaudeau
  • T. Glatard
  • E. Jeannot
  • Y Legré
  • C. Loomis
  • I. Magnin
  • J. Montagnat
  • J. -M. Moureaux
  • A. Osorio
  • X. Pennec
  • R. Texier


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.


Grid computing medical image analysis 


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Copyright information

© Springer Science + Business Media, Inc. 2005

Authors and Affiliations

  • C. Germain
    • 1
    • 2
    Email author
  • V. Breton
    • 2
  • P. Clarysse
    • 3
  • Y. Gaudeau
    • 4
  • T. Glatard
    • 5
  • E. Jeannot
    • 6
  • Y Legré
    • 2
  • C. Loomis
    • 7
  • I. Magnin
    • 3
  • J. Montagnat
    • 5
  • J. -M. Moureaux
    • 4
  • A. Osorio
    • 9
  • X. Pennec
    • 8
  • R. Texier
    • 1
  1. 1.Laboratoire de Recherche en Informatique (LRI) – CNRSUniversité Paris-SudFrance
  2. 2.Laboratoire de Physique Corpusculaire (LPC) – CNRSFrance
  4. 4.Centre de Recherche en Automatique de Nancy (CRAN) – CNRS, INPLUniversités de NancyFrance
  5. 5.Laboratoire Informatique Signaux et Syst‘emes (I3S) – CNRSUniversité de NiceFrance
  6. 6.Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA) – CNRS, INRIA, INPLUniversités de NancyFrance
  7. 7.Laboratoire de l'Accélérateur Linéaire (LAL) – CNRSUniversité Paris-SudFrance
  8. 8.Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur (LIMSI) – CNRSFrance
  9. 9.INRIA Sophia-AntipolisFrance

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