首页> 外文期刊>IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control >Joint Generalized Coherence Factor and Minimum Variance Beamformer for Synthetic Aperture Ultrasound Imaging
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Joint Generalized Coherence Factor and Minimum Variance Beamformer for Synthetic Aperture Ultrasound Imaging

机译:合成孔径超声成像的联合广义相干因子和最小方差波束形成器

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摘要

The delay-and-sum (DAS) beamformer is the most commonly used method in medical ultrasound imaging. Compared with the DAS beamformer, the minimum variance (MV) beamformer has an excellent ability to improve lateral resolution by minimizing the output of interference and noise power. However, it is hard to overcome the tradeoff between satisfactory lateral resolution and speckle preservation performance due to the fixed subarray length of covariance matrix estimation. In this study, a new approach for MV beamforming with adaptive spatial smoothing is developed to address this problem. In the new approach, the generalized coherence factor (GCF) is used as a local coherence detection tool to adaptively determine the subarray length for spatial smoothing, which is called adaptive spatial-smoothed MV (AMV). Furthermore, another adaptive regional weighting strategy based on the local signal-to-noise ratio (SNR) and GCF is devised for AMV to enhance the image contrast, which is called GCF regional weighted AMV (GAMV). To evaluate the performance of the proposed methods, we compare them with the standard MV by conducting the simulation, in vitro experiment, and the in vivo rat mammary tumor study. The results show that the proposed methods outperform MV in speckle preservation without an appreciable loss in lateral resolution. Moreover, GAMV offers excellent performance in image contrast. In particular, AMV can achieve maximal improvements of speckle signal-to-noise ratio (SNR) by 96.19% (simulation) and 62.82% (in vitro) compared with MV. GAMV achieves improvements of contrast-to-noise ratio by 27.16% (simulation) and 47.47% (in vitro) compared with GCF. Meanwhile, the losses in lateral resolution of AMV are 0.01 mm (simulation) and 0.17 mm (in vitro) compared with MV. Overall, this indicates that the proposed methods can effectively address the inherent limitation of the standard MV in order to improve the image quality.
机译:延迟和总和(DAS)波束形成器是医疗超声成像中最常用的方法。与DAS波束形成器相比,最小方差(MV)波束形成器通过最小化干扰和噪声功率的输出,具有出色的能力来提高横向分辨率。然而,由于协方差矩阵估计的固定子阵列长度,难以克服令人满意的横向分辨率和散斑保存性能之间的权衡。在这项研究中,开发了一种具有自适应空间平滑的MV波束形成的新方法来解决这个问题。在新方法中,广义相干因子(GCF)用作局部相干检测工具,以自适应地确定用于空间平滑的子阵列长度,其称为自适应空间平滑的MV(AMV)。此外,基于局部信噪比(SNR)和GCF的另一种自适应区域加权策略被设计为AMV,以增强图像对比度,其称为GCF区域加权AMV(GAMV)。为了评估所提出的方法的性能,通过进行模拟,体外实验和体内大鼠乳腺肿瘤研究,将它们与标准MV进行比较。结果表明,所提出的方法在没有明显的横向分辨率的情况下占据散斑保存的MV。此外,GAMV在图像对比中提供出色的性能。特别是,与MV相比,AMV可以通过96.19%(模拟)和62.82%(体外)来实现斑点信噪比(SNR)的最大改善。与GCF相比,GAMV通过27.16%(模拟)和47.47%(体外)来实现对比度噪声比的改善。同时,与MV相比,AMV的横向分辨率的损失为0.01mm(模拟)和0.17mm(体外)。总的来说,这表明所提出的方法可以有效地解决标准MV的固有限制,以提高图像质量。

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