A low-complexity subtraction-based weighting coefficient for synthetic aperture ultrasound imaging

A major challenge in medical ultrasound beamforming is developing algorithms capable of producing high-resolution images. The minimum variance (MV) algorithm achieves higher resolution than the delay-and-sum (DAS) approach but suffers from high computational cost, limiting its practical use. Recently, the null subtraction imaging (NSI) algorithm has been proposed, offering high resolution with significantly lower complexity than MV. However, its main drawback is the loss of background speckle information. In this paper, a novel method is introduced to simultaneously achieve high resolution and preserve background speckle. The proposed technique reconstructs a high-resolution image while maintaining speckle characteristics comparable to those of DAS. Appropriate weights are determined based on a subtraction process between beamformed images corresponding to two transmit sub-arrays. Moreover, the computational burden of the proposed method is low, making it suitable for real-time applications. Simulated and experimental evaluations demonstrate that the proposed technique outperforms the MV and NSI algorithms in terms of resolution enhancement. Furthermore, among existing methods, it uniquely achieves simultaneous improvement in image resolution, contrast, and background speckle preservation.