IEEE Trans Ultrason Ferroelectr Freq Control. 2020 Aug;67(8):1573-1589. doi: 10.1109/TUFFC.2020.2977942. Epub 2020 Mar 3.
Adaptive beamforming has been widely studied for ultrasound imaging over the past few decades. The minimum variance (MV) and generalized coherence factor (GCF) approaches have been validated as effective methods. However, the MV method had a limited contribution to contrast improvement, while the GCF method suffered from severe speckle distortion in previous studies. In this article, a novel ultrasound beamforming approach based on MV and GCF beamformers is proposed to enhance the spatial resolution and contrast in synthetic aperture (SA) ultrasound imaging. First, the MV optimization problem is conceptually redefined by minimizing the total power of the transmitting and receiving outputs. Estimation of the covariance matrices in transmit and receive apertures is carried out and then utilized to determine adaptive weighting vectors. Second, a data-compounding method, viewed as a spatial low-pass filter, is introduced to the GCF method to optimize the spatial spectrum of echo signals and obtain better performance. Robust principal component analysis (RPCA) processing is additionally employed to obtain the final output. Simulation, experimental, and in vivo studies are conducted on different data sets. Relative to the traditional delay-and-sum (DAS) beamformer, mean improvements in the full-width at half-maximum and contrast ratio of 89% and 94%, respectively, are achieved. Thus, considerable enhancement of the spatial resolution and contrast is obtained by the proposed method. Moreover, the proposed method performs better in terms of the computational complexity. In summary, the proposed scheme effectively enhances ultrasound imaging quality.
在过去的几十年中,自适应波束形成技术在超声成像领域得到了广泛的研究。最小方差 (MV) 和广义相干因子 (GCF) 方法已被验证为有效的方法。然而,MV 方法对对比度的改善贡献有限,而 GCF 方法在以前的研究中存在严重的斑点伪影。本文提出了一种基于 MV 和 GCF 波束形成器的新型超声波束形成方法,以提高合成孔径 (SA) 超声成像中的空间分辨率和对比度。首先,通过最小化发射和接收输出的总功率,对 MV 优化问题进行了概念上的重新定义。在发射和接收孔径中进行协方差矩阵的估计,并利用它来确定自适应加权向量。其次,将一种数据复合方法(视为空间低通滤波器)引入到 GCF 方法中,以优化回波信号的空间谱,并获得更好的性能。此外,还采用鲁棒主成分分析 (RPCA) 处理来获得最终输出。在不同的数据集上进行了仿真、实验和体内研究。与传统的延迟求和 (DAS) 波束形成器相比,该方法在半最大值全宽和对比度比方面分别提高了 89%和 94%。因此,该方法可以显著提高空间分辨率和对比度。此外,该方法在计算复杂度方面表现更好。总之,该方案有效地提高了超声成像质量。