The potential benefits of HPCC resource for biomedicine challenge the imagination and can effect every aspect of medicine, including education and training, administration, and clinical practice. The development of effective resource integration and management strategies is key to the realization of these benefits. In academic settings, HPCC systems will likely evolve from resources distributed in individual operational units, e.g., departments or research centers, in much the same way that networks of conventional computing resources are evolving now. The extent to which current IAIMS model and experiences are applicable to orderly evolution and efficient management integrated HPCC systems is uncertain however because of significant differences in major factors such as initial, operating, and administrative cost; technological complexity; user access and training; specific applications; and overall impact on existing educational, research, and medical systems. Well focused HPCC demonstration projects in an IAIMS environment can provide valuable data regarding the applicability of existing models, and steer model development in directions that anticipate rather than react to HPCC technology. The overall aims of this project are to 1) demonstrate the feasibility of using HPCC resources to extend the use of computers in the clinical setting to access large data banks and to perform complex analyses of large data sets, such as medical images, for on-site, real-time support of critical medical decisions, and 2) evaluate issues and implications associated with incorporating HPCC resources in an IAIMS setting. The specific demonstration project, which involves the use of both computer vision of HPCC technology for deciding whether or not to proceed with the delivery of each dose fraction of radiation therapy, is expected to provide valuable insight into the technological, administrative, and related issues that are of general significance to other clinical applications that could benefit from HPCC technology for-on-site support when critical medical decisions are required
