Covariance Mean-to-Standard-Deviation Factor for Ultrasound Imaging

We previously proposed mean-to-standard-deviation ratio-based adaptive weighting factors for ultrasound imaging. However, there exists a trade-off between side lobe suppression and speckle statistics preservation performances. The goal of this paper is to implement a new covariance mean-to-standard-deviation factor (CMSF) for ultrasound imaging. In CMSF, adaptive selection of subarray length and diagonal reducing are introduced to effectively reduce off-axis energy. Simulated and experimental data sets were used to evaluate the imaging performance of the proposed method. The quantitative results indicate that, compared with RSMSF, CMSF
$(\delta=\mathbf{1})$
leads to average improvements of 50.8%, 28.4%, 19.4%, and 15.0% in resolution, contrast ratio (CR), generalized contrast-to-noise ratio (gCNR), and speckle signal-to-noise ratio (speckle SNR), respectively. Simulation and experimental results suggest that CMSF has the potential to improve the lateral resolution and maintain the speckle reliably.