Phase-corrective compressed-beamforming for ultrasound imaging

Compressed-sensing (CS) based beamformers have drawn increasing interest in ultrasound community for their potential of providing better image quality with fewer data. In practice, this framework usually requires good signal models for data explanation and the final estimation could be sensitive to model imperfectness on real data. In this paper, we extend our previous work [1] and robustify the compressed beamforming in presence of unknown phase perturbations in acoustic measurements. We explicitly introduce additional phase regularization, at each step of optimization, to correct the discrepancy between the predicted and the measured phases. The effectiveness of this approach is shown on simulated and phantom data with added aberrations.