Sparse Convolutional Beamforming For Wireless Ultrasound

Wireless ultrasound systems can make the imaging process much more efficient, affordable and accessible for users. The standard technique to create B-mode images is to rely on delay and sum (DAS) beamforming, in which the signals at each transducer element are sampled and processed by introducing appropriate delays. However, the sampling rates required to perform digital beamforming are typically high, resulting in high power requirements and a considerable amount of data which cannot be transferred over standard WiFi channels. In this paper we combine recently proposed methods for reducing sampling rate in each channel, and spatial reduction in the number of channels using sparse arrays, in order to implement beamforming at a low data rate without impacting image quality. We refer to our approach as sparse Fourier domain convolutional beamforming, and demonstrate that it can generate B-mode images at rates that are 33 times lower than standard DAS implementations.