Computationally efficient minimum-variance baseband delay-multiply-and-sum beamforming for adjustable enhancement of ultrasound image resolution

Abstract

Baseband Delay-Multiply-and-Sum (BB-DMAS) beamforming takes advantage of the baseband spatial coherence of receiving aperture to improve image resolution and contrast. Meanwhile, the side-lobe clutter and noise level can also be effectively suppressed in BB-DMAS beamforming due to their low coherence when being detected by channels in different spatial locations. BB-DMAS scales the magnitude of channel signal by p-th root and restores the output dimensionality by p-th power after channel summation. Higher p value introduces more spatial coherence into DMAS beamforming and provides higher image resolution at the cost of background speckle quality. In this study, a computationally efficient integration of BB-DMAS with minimum-variance (MV) beamforming is developed so that the image resolution can be drastically improved with low p value (e.g. p < 2) while maintaining the speckle quality. For each image pixel, the proposed MV-DMAS only requires single MV estimation to optimize the aperture apodization for DMAS beamforming. Our simulation results show that, with p = 1.5, the −6-dB lateral width of wire reflector noticeably improves from 0.22 mm to 0.13 mm by adopting MV estimation in BB-DMAS beamforming. In MV-DMAS, the suppression of uncorrelated random noises also remains effective. Experimental results not only confirm the superior resolution in MV-DMAS beamforming but also demonstrates comparable image contrast and speckle quality to BB-DMAS counterpart. In conclusion, MV-DMAS beamforming can provide improvement in image resolution while maintaining the other image quality metrics using an efficient combination of moderate spatial coherence and MV estimation of receiving aperture apodization in ultrasonic imaging.