A Cloud-Deployed 3D Medical Imaging System with Dynamically Optimized Scalability and Cloud Costs

Abstract

Medical imaging is established as a foundation for the delivery of high quality patient care in medicine. The growing data volume produced per examination increases the demand for 3D visualization of such data sets in radiology. Current medical imaging systems deliver 3D functionality either through Workstations or in Client/Server solutions. Workstation deployments suffer from the requirement to transfer huge data sets to every workstation where the data is needed. Client/Server solutions often suffer from scalability limits as data from all radiologists is rendered by a single server or a server farm, adding complexity and cost. In this paper, we present a novel 3D rendering approach using Cloud Computing that optimizes scalability and operational cost by architecture while flexibly adjusting to environments with low network quality.