Grid-enabling medical image analysis

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 medi...

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Bibliographic Details
Published in:Journal of clinical monitoring and computing 2005-10, Vol.19 (4-5), p.339-349
Main Authors: Germain, C, Breton, V, Clarysse, P, Gaudeau, Y, Glatard, T, Jeannot, E, Legré, Y, Loomis, C, Magnin, I, Montagnat, J, Moureaux, J-M, Osorio, A, Pennec, X, Texier, R
Format: Article
Language:English
Subjects:
Computer Communication Networks
Data processing
Digital imaging
Health services
Image analysis
Image processing
Image Processing, Computer-Assisted
Information Storage and Retrieval
Medical imaging
Middleware
Research projects
Systems Integration
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Summary: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.
ISSN:1387-1307
1573-2614
DOI:10.1007/s10877-005-0679-9