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Telemedicine for 3-D images on mobile devices presents promising development opportunities. Being constrained by computing power and storage capacity on mobile devices, the processing performance of 3-D medical images is insufficient for more demanding tasks. Using virtual mobile infrastructure technology to utilize cloud resources is a common solution. But it encounters the challenge of poor performance in data transmission, image rendering and image coding. This article presents a graphics processing unit (GPU) and video process unit (VPU) enabled open virtual mobile infrastructure (OpenVMI) for 3-D image rendering to solve the challenge. It makes two improvements. First, a bespoke GPU driver is developed in the Android Docker, optimizing the transmission workflow for data transmission and image rendering. Second, a VPU is added to the hardware layer to code rendered results in H.264 format, replacing CPU coding which consumes a large amount of CPU resources. By adopting the OpenVMI, the telemedicine training system proposed in this article presents an easy-to-set up, cheap and low-latency solution that is particularly helpful for telemedicine training in remote and underdeveloped areas. Performance experiments suggest that the OpenVMI delivers better performance than existing state-of-the-art systems, even in mobile devices with weaker hardware capabilities. Concurrency experiment suggests that a single host server can support up to 24 concurrent training sessions, which makes the OpenVMI very helpful for telemedicine training that demands high concurrency. The OpenVMI-based solution proposed in this article is not restricted to the use of telemedicine training, but also suitable for other application areas, such as virtual reality and augmented reality in mobile environments.

GPU and VPU Enabled Virtual Mobile Infrastructure for 3-D Image Rendering and its Application in Telemedicine