An Agile Ultrasound Development Platform Based on GPU and FPGA

Ultrasound imaging is widely used as a diagnostic tool in clinical medicine. In a conventional ultrasound system, imaging algorithms are implemented in hardware. Although the hardware-based system can generally achieve higher processing speed with less hardware resource usage, system development is relatively a long process. Recently, with the advancement of graphics processing units (GPU’s) and parallel programming, software-based ultrasound imaging has been developed. Compared with the hardware-based system, GPU’s have more flexibility in algorithm designs but the GPU’s resource usage and computation speed may not be as good as those of a hardware-based system. To this end, this research has two purposes. First, ultrasound imaging algorithms are implemented in two common GPU programming languages, CUDA and OpenCL. Second, based on OpenCL, an agile ultrasound development platform that exploits the advantages of both the hardware based system and the software-based system is constructed. This research uses OpenCL SDK provided by ALTERA to convert OpenCL code to FPGA based language. In this research, we successfully implement two systems, including a 1D array system and a single element high frequency system, with four major imaging modes, including B-mode, C-mode, PW-mode and M-mode. Performance of the hardware based system was compared against that of the software based system, including memory copy and computation times. Our results show that both CUDA and OpenCL can reach real-time imaging frame rate (i.e., > 30 frame/s). For the FPGA-based system, code conversion from OpenCL is successful and several optimization tasks are necessary to fully exploit the advantages of the agile platform.