Foroozan, ForooharSadeghi, Parastoo2016-06-14April 19 -9781467369978http://hdl.handle.net/1885/103404The paper investigates combining Compressive Sensing (CS) with the robust Capon beamformer (RCB) for the purpose of medical ultrasound image formation with a much reduced number of samples compared to those used in current state-of-art ultrasound. The proposed CS algorithm uses wave atom dictionary as a low dimension projection, a Bernouli random matrix as a sensing matrix and a regularized-l1 optimization technique for recovery. The reconstructed signals are then pre-processed before using the RCB technique augmented with spatial smoothing and diagonal loading. This approach is demonstrated through simulations, wire phantom and in vivo cardiac data with a reduction of up to 1/8 in the processed data rate and ultrasound images of similar perceived quality.201510.1109/ICASSP.2015.71784162016-06-14