Partitioning medical image databases for content-based queries on a Grid.

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.