Plane-wave compounding is an active topic of research in ultrasound imaging because it is a promising technique for ultrafast ultrasound imaging. Unfortunately, due to the data-independent nature of the traditional compounding method, it imposes a fundamental limit on image quality. To address this issue, adaptive beamformers have been implemented in the compounding procedure. In this article, a new adaptive beamformer for the 2-D data set obtained from multiple plane-wave transmissions is investigated. In the proposed scheme, the minimum variance (MV) weights are applied to the backscattered echoes. Then, the final image is obtained by employing a modified version of the delay multiply-and-sum (DMAS) beamformer in the coherent compounding. The results demonstrate that the presented MV-DMAS scheme outperforms the conventional coherent compounding in both terms of resolution and contrast. It also offers improvements over the 2-D-DMAS and some MV-based methods presented in the literature, such that it achieves at least 20.9% enhancement in sidelobe reduction compared with the best result of MV-based methods. Also, by the proposed method, the in vivo study shows an improved generalized contrast-to-noise ratio (GCNR) that implies a higher probability of lesion detection.

中文翻译：

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最小方差与修正延迟乘和求和波束成形相结合的平面波合成

平面波复合是超声成像研究的一个活跃主题，因为它是超快超声成像的有前途的技术。不幸的是，由于传统复合方法的数据独立性，它对图像质量施加了基本限制。为了解决这个问题，已经在复合过程中实现了自适应波束形成器。在本文中，研究了一种用于从多个平面波传输中获得的二维数据集的新型自适应波束形成器。在提出的方案中，最小方差（MV）权重应用于反向散射回波。然后，通过在相干复合中采用延迟乘和和（DMAS）波束形成器的改进版本来获得最终图像。结果表明，所提出的MV-DMAS方案在分辨率和对比度方面均优于常规的相干复合。它还提供了对2-D-DMAS和文献中提出的某些基于MV的方法的改进，因此与基于MV的方法的最佳结果相比，它在旁瓣减小方面实现了至少20.9％的增强。此外，通过提出的方法，体内 研究表明，改进的广义对比噪声比（GCNR）意味着更高的病变检出率。