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Resource-intensive and complex medical imaging applications can benefit from the use of scientific workflow technology for their design, rapid implementation and reuse, but at the same time they require a grid computing infrastructure to execute efficiently. In this paper we describe a technical architecture that bridges the gap between the Taverna workflow management system and the EGEE grid infrastructure. This is achieved through a novel Taverna gLite activity plugin that makes the interface between the multi-threaded, centralized workflow enactor and the massively distributed, batch-oriented grid infrastructure. The plugin significantly increases the performance of Medical Imaging workflows over an equivalent plain Taverna workflow.