Mobile ultrasound imaging on heterogeneous multi-core platforms

Ultrasound imaging is one of the most important medical diagnostic methods. The bulkiness of state-of-the-art high-quality ultrasound devices, however, drastically limits their usability in important application scenarios. In this paper, we show how a portable medical ultrasound device can be built using many-core technology and programmable logic, combining low power consumption with high flexibility. We discuss a typical ultrasound image reconstruction algorithm and how it can be parallelized using a pipelined design that efficiently partitions the workload among heterogeneous processing elements. A special focus lies on the limited memory resources and data bandwidth between components. To tackle both problems, we use floating window buffers and approximate computations, and we minimize lookup table sizes using on-the-fly calculations. We evaluate the design on the Adapteva Parallella platform, which contains a power-efficient 16-core Epiphany coprocessor and a Zynq SoC including a dual-core ARM A9 processor and programmable logic. Experimental results show that parallel beamforming of 128 input channels to a 288x128 pixel ultrasound image can be achieved on the Parallella at a rate of 5.3 frames per second consuming only 2 watt of dynamic power.