J Montagnat1, V Breton, I E Magnin. 1. CREATIS, bâtiment B. Pascal, 20 av. A. Einstein, 69621 Villeurbanne Cedex, France. johan@creatis.insa-lyon.fr
Abstract
OBJECTIVES: In this paper we study the impact of executing a medical image database query application on the grid. For lowering the total computation time, the image database is partitioned into subsets to be processed on different grid nodes. METHODS: A theoretical model of the application complexity and estimates of the grid execution overhead are used to efficiently partition the database. RESULTS: We show results demonstrating that smart partitioning of the database can lead to significant improvements in terms of total computation time. CONCLUSIONS: Grids are promising for content-based image retrieval in medical databases.
OBJECTIVES: In this paper we study the impact of executing a medical image database query application on the grid. For lowering the total computation time, the image database is partitioned into subsets to be processed on different grid nodes. METHODS: A theoretical model of the application complexity and estimates of the grid execution overhead are used to efficiently partition the database. RESULTS: We show results demonstrating that smart partitioning of the database can lead to significant improvements in terms of total computation time. CONCLUSIONS: Grids are promising for content-based image retrieval in medical databases.
Authors: C Germain; 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 Journal: J Clin Monit Comput Date: 2005-10 Impact factor: 1.977