MediGRID: Towards a user friendly secured grid infrastructure
Future Generation Computer Systems
A core ontology of instruments used for neurological, behavioral and cognitive assessments
Proceedings of the 2010 conference on Formal Ontology in Information Systems: Proceedings of the Sixth International Conference (FOIS 2010)
Web-services-based resource discovery model and service deployment on healthgrids
IEEE Transactions on Information Technology in Biomedicine - Special section on new and emerging technologies in bioinformatics and bioengineering
Overview of Medical Data Management Solutions for Research Communities
CCGRID '10 Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing
Journal of Cognitive Neuroscience
Semi-supervised image classification for automatic construction of a health image library
Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium
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The aggregation of imaging, clinical, and behavioral data from multiple independent institutions and researchers presents both a great opportunity for biomedical research as well as a formidable challenge. Many research groups have well-established data collection and analysis procedures, as well as data and metadata format requirements that are particular to that group. Moreover, the types of data and metadata collected are quite diverse, including image, physiological, and behavioral data, as well as descriptions of experimental design, and preprocessing and analysis methods. Each of these types of data utilizes a variety of software tools for collection, storage, and processing. Furthermore sites are reluctant to release control over the distribution and access to the data and the tools. To address these needs, the biomedical informatics research network (BIRN) has developed a federated and distributed infrastructure for the storage, retrieval, analysis, and documentation of biomedical imaging data. The infrastructure consists of distributed data collections hosted on dedicated storage and computational resources located at each participating site, a federated data management system and data integration environment, an extensible markup language (XML) schema for data exchange, and analysis pipelines, designed to leverage both the distributed data management environment and the available grid computing resources.