2004/05/24 by D. Rogulin, D Rogulin, Rogulin, D +12
Computer Science · Decision Sciences · #Databases (cs.DB) #Distributed #Distributed and Parallel Computing Systems #FOS: Computer and information sciences #H2.4 #J.3 #Parallel #Scientific Computing and Data Management #and Cluster Computing (cs.DC) #cs.DB #cs.DC
paper · pdf · doi:10.48550/arxiv.cs/0405087
9 pages, 5 figures
arxiv created 2004/05/24 · openalex publication_date 2004/05/24 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The storage and manipulation of digital images and the analysis of the information held in those images are essential requirements for next-generation medical information systems. The medical community has been exploring collaborative approaches for managing image data and exchanging knowledge and Grid technology [1] is a promising approach to enabling distributed analysis across medical institutions and for developing new collaborative and cooperative approaches for image analysis without the necessity for clinicians to co-locate. The EU-funded MammoGrid project [2] is one example of this and it aims to develop a Europe-wide database of mammograms to support effective co-working between healthcare professionals across the EU. The MammoGrid prototype comprises a high-quality clinician visualization workstation (for data acquisition and inspection), a DICOM-compliant interface to a set of medical services (annotation, security, image analysis, data storage and querying services) residing on a so-called Grid-box and secure access to a network of other Grid-boxes connected through Grid middleware. One of the main deliverables of the project is a Grid-enabled infrastructure that manages federated mammogram databases across Europe. This paper outlines the MammoGrid Information Infrastructure (MII) for meta-data analysis and knowledge discovery in the medical imaging domain.