Data grid for large-scale medical image archive and analysis
Proceedings of the 13th annual ACM international conference on Multimedia
The Globus Striped GridFTP Framework and Server
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
Scientific Programming
Journal of High Speed Networks - Broadband Multimedia Sensor Networks in Healthcare Applications
Globus toolkit version 4: software for service-oriented systems
NPC'05 Proceedings of the 2005 IFIP international conference on Network and Parallel Computing
Database design and implementation for quantitative image analysis research
IEEE Transactions on Information Technology in Biomedicine
Journal of High Speed Networks - Broadband Multimedia Sensor Networks in Healthcare Applications
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Clinical trials play a crucial role in testing new drugs or devices in modern clinical practice. Medical imaging has become an important tool in clinical trials because images provide a unique and fast diagnosis with visual observance and quantitative assessment. A typical imaging-based clinical trial consists of: (1) A well-defined rigorous clinical trial protocol, (2) a radiology core that has a quality control mechanism, a biostatistics component, and a server for storing and distributing data and analysis results; and (3) many field sites that generate and send clinical trial image studies to the radiology core. With ever-increasing number of clinical trials, it becomes a great challenge for a radiology core which handles multiple clinical trials to have a robust server to administrate multiple trials as well as satisfy the requirements to quickly distribute information to participating radiologists/clinicians worldwide to assess trials' results. Data Grid in the grid computing technology can satisfy the aforementioned requirements of imaging-based clinical trials. In this paper, we present a Data Grid architecture for worldwide imaging-based clinical trials. The Data Grid testbed has been set up in three international sites: Image Processing and Informatics (IPI) Laboratory at University of Southern California, USA; the Hong Kong Polytechnic University; and InCor (Heart Institute) at Sao Paulo, Brazil. The three chosen sites are connected with high speed international networks including the Internet2, the HARNET (Hong Kong Academic and Research Network), and the Brazilian National Research and Education Network (RNP2). The concept, design and implementation of the Data Grid are presented. Grid computing technology open source software Globus Toolkit 4.0 and DICOM technology were used to implement the DICOM compliance Data Grid. This paper also describes results of using Data Grid in imaging-based clinical trails for fault tolerance image data backup. The successful implementation and evaluation of the Data Grid for imaging-based clinical trials provide three major benefits: (1) an understanding of the methodology for using data grid technology and high speed networks in clinical trails; (2) an establishment of the performance benchmarks of Data Grid over high speed networks; and (3) a Data Grid test bed for performing worldwide imaging based clinical trials.