Fast Beamforming Method for Plane Wave Compounding Based on Beamspace Adaptive Beamformer and Delay-Multiply-and-Sum

波束赋形 计算机科学 稳健性(进化) 自适应波束形成器 图像质量 斑点图案 算法 平滑的 帧速率 图像分辨率 对比度(视觉) 最小方差无偏估计量 平面波 人工智能 数学 图像(数学) 计算机视觉 光学 物理 电信 均方误差 统计 生物化学 基因 化学
作者
Mahsa Sotoodeh Ziksari,Babak Mohammadzadeh Asl
出处
期刊:Ultrasound in Medicine and Biology [Elsevier]
卷期号:49 (5): 1164-1172 被引量:3
标识
DOI:10.1016/j.ultrasmedbio.2023.01.001
摘要

Objective

Although the use of coherent plane wave compounding is a promising technique for enabling the attainment of very high frame rate imaging, it achieves relatively low image quality because of data-independent reconstruction. Adaptive beamformers rather than delay-and-sum (DAS) conventional techniques have been proposed to improve the imaging quality. The minimum variance (MV) and delay-multiply-and-sum (DMAS) beamformers have been validated as effective in improving image quality. The MV improves mainly the resolution of the image, while being computationally expensive and having little impact on contrast. The DMAS increases the contrast while over-suppressing the speckle region in the case of 2-D summation for multi-transmission applications.

Methods

In a new approach, a beamformer based on MV and DMAS is proposed to enhance both spatial resolution and contrast in plane wave imaging. Prior to estimating the weight vector of MV, the backscattered echoes are decorrelated without any spatial smoothing. This enhances the robustness of MV without compromising the improvement in resolution. With a shift from element space to beamspace, MV weights are calculated using the spatial statistics of a set of orthogonal beams, which allows the high-complexity algorithm to be run faster. After that, the MV weights are applied to the DMAS output vector beamformed over different transmissions.

Discussion and Conclusion

The proposed method can result in better contrast resolution, thereby avoiding over-suppression. The complexity of the applied DMAS version is also similar to that of DAS. Imaging results reveal that the proposed method offers improvements over the traditional compounding method in terms of spatial and contrast resolution. It also can achieve a higher image quality compared with some existing adaptive methods applied in the literature.
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