Grid-enabling medical image analysis

Authors:
C. Germain;V. Breton;P. Clarysse;Y. Gaudeau;T. Glatard;E. Jeannot;Y. Legre;C. Loomis;J. Montagnat;J.-M. Moureaux;A. Osorio;X. Pennec;R. Texier
Affiliations:
Sect. Computational Sci., Amsterdam Univ., Netherlands;Cybermedia Center, Osaka Univ., Japan;Cybermedia Center, Osaka Univ., Japan;Math. & Comput. Sci. Div., Argonne Nat. Lab., IL, USA;Math. & Comput. Sci. Div., Argonne Nat. Lab., IL, USA;Math. & Comput. Sci. Div., Argonne Nat. Lab., IL, USA;Math. & Comput. Sci. Div., Argonne Nat. Lab., IL, USA;-;-;-;-;-;-
Venue:
CCGRID '05 Proceedings of the Fifth IEEE International Symposium on Cluster Computing and the Grid - Volume 01
Year:
2005

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Abstract

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.