Minimum Variance Optimizations With Different Covariance Matrices in Plane-Wave Ultrasound Imaging

Coherent plane-wave compounding (CPWC) is a commonly applied beamforming technique for realizing ultrafast ultrasound imaging, though it often involves a trade-off in image quality. To address this limitation, the minimum variance distortionless response (MVDR) is advanced for the adaptive combination of ultrasound signals obtained from different directions. This process effectively suppresses the artifacts and improves the imaging quality. While previous studies have proved that MVDR can be approximated to a minimum mean square error (MMSE) algorithm after combining it with a Wiener post-filter (WPF), a systematic survey of optimized MVDR beamformers utilizing different estimation of covariance matrices and corresponding post-filter has not been undertaken. In this study, we scrutinize the impact on the image resolution and contrast ratios (CRs) by varying beamforming combination strategies related to MVDR beamformers for CPWC imaging. Moreover, we propose a novel approach to effectively integrate the multidimensional signals from both the transmission and reception stages, improving overall image quality for MVDR beamformers. Our comprehensive evaluation, including the simulation, phantom, and in vivo experiments suggests that the spatial-smoothing MVDR in the reception and transmission stages have inherent strengths in lateral and axial resolution, respectively. Also, WPF further benefits the improvement of the image contrast and lateral resolution. By comparison, the results of our proposed approach offer valuable insights into the future of research in optimized ultrafast ultrasound imaging related to MVDR and coherence-based factors, paving a better way to combine the correlated signals in the transmission and reception stages, applicable not only to CPWC but also other two-way focusing systems.