Dual-domain compressed beamforming for medical ultrasound imaging

In this paper, we propose a novel beamforming approach based on a dual-domain compressed sensing (CS) technique. We model the image as a combination of geometry information and residual details. The beamforming is formulated as depth-dependent optimization problems, solved successively in wavelet domain to capture the overall geometry, and in the image domain to preserve details. With a budget of few iterations, our approach preserves better features and produces less holey-tissue artifacts compared to single-domain reconstructions. Tested on simulated data, CIRS phantom and a cardiac scan, our beamforming requires typically three plane/spherical-wave transmissions to achieve comparable or better image quality than delay-and-sum (DAS) using eleven transmissions. We thus attain a theoretical frame rate over 1KHz at depth of 15cm.