Evaluation of Real-Time Remote 3D Rendering of Medical Images using GPUs

Remote visualization of medical data is a very attractive alternative to increased mobility, allowing volumetric data to be accessed even in devices with low processing capability. However, the amount of simultaneous accesses and the bandwidth available are natural bottlenecks for any solution in this field. This paper presents a methodology to evaluate 3D volumetric rendering client-servers systems with the goal of determining the maximum load of a specific system based on Quality of Service (QoS). With such input in mind, a system architect could project systems with better cost-benefit ratio, or even design a cloud system that predicts and rents servers based on the number of service requests. In order to check the viability of the methodology, a stress test was conducted in a client-server system developed to visualize Computed Tomography (CT) scans. Results have shown that it could handle at least 20 simultaneous remote visualizations, even in scenarios with low bandwidth, finding its upper limit when dealing with around 30 simultaneous visualizations.