A multi-resolution approach for a content-based image retrieval on the grid
Résumé
Hospitals and medical centers are producing more and more data, that need to be pro cessed. Those data are confidential, heterogeneous, and limited to the geographic site where they have been produced. Unless properly anonymised, they cannot be distributed on wide area networks. Grid technologies allow the globalization of storage and processing resources, and enable large-scale experimentations on distributed data. They constitute a promising tool to treat the different data and analyse the knowledge they contain, while offering secured access and high-performance computing capacities to the different users. Our aim is to evaluate the possibilities of grid technologies for handling medical data. In this paper, we focus on a breast cancer diagnosis assistance tool, based on a distributed and incremental knowledge construction and a content-based image retrieval system. We analyse the different scenarii of uses of such a tool. We further propose an algorithm that indexes mammographie images for content-based query purposes. This algorithm is tested on images of different resolutions in or der to reduce the indexation time and we analyse its performances with first experiments on the grid.