Design considerations of real-time adaptive beamformer for medical ultrasound research using FPGA and GPU

Adaptive beamforming has been well considered as a potential solution for improving the imaging quality of medical ultrasound systems. Despite the promised improvement in lateral resolution, image contrast and imaging penetration, the use of adaptive beamforming is substantially more computationally demanding than conventional delay-and-sum beamformers. While a dedicated hardware solution may be able to address the computational demand of one particular design, the need for an efficient algorithm exploration framework demands a platform solution that is high-performance and easily reprogrammable. To that end, the use of FPGA and GPU for implementing real-time adaptive beamforming on such platform has been explored. The results are evaluated quantitatively in terms of performance and image quality, and qualitatively with respect to ease of system integration and ease of use. In our test cases, both FPGA- and GPU-based solutions achieved real-time throughput exceeding 80 frames-per-second, and over 38x improvement when compared to our baseline CPU implementation. While the development time on GPU platform remains much lower than its FPGA counterpart, the FPGA solution is effective in providing the necessary I/O bandwidth to enable an end-to-end real-time reconfigurable image formation system.