Degradation of image quality caused by aberrations and off-axis interferences is common in medical ultrasound imaging. The ring-array echo imaging also suffers from these constraints, where phase aberrations caused by tissue heterogeneity create overlapping of interest target and worsen the interpretability of anatomical structures; while off-axis interferences reduce the spatial resolution and contrast of the reconstructed images. To address them, the signal coherence is available since they can be considered as incoherent interference and noise. The coherence factor (CF) is sensitive to phase aberrations and is thus adopted in this study. Moreover, the convolutional beamforming algorithm (COBA) specifically exploits the autocorrelation operation to improve the signal coherence and effectively reduce noise. Therefore, we first utilize the CF to detect the local coherence and its maximization criterion as a way to estimate the sound speed to correct for phase aberration. Then, CF is used as an adaptive weighting factor to suppress the noise, and based on this, we develop a short-lag COBA to further enhance the image quality, referred to as the CF_SLCOBA method. Simulations and experiments were performed to evaluate the performance of the proposed methods. Results show that, the improvements of the CF_SLCOBA method in resolution is about 26.8% compared with CF; while about 92.0% in contrast ratio (CR) compared with COBA, in the experiments. Meanwhile, the proposed method yields a good performance in phase aberration correction. This demonstrates that the proposed method may provide benefits for rebuilding high-quality images, which also reveals that it offers a certain potential for practical applications.

中文翻译：

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用于环形阵列超声成像的基于相干性的相位像差校正和波束形成


像差和离轴干扰引起的图像质量下降在医学超声成像中很常见。环形阵列回波成像也受到这些限制，组织异质性引起的相位畸变会造成感兴趣目标的重叠，并恶化解剖结构的可解释性；而离轴干扰会降低重建图像的空间分辨率和对比度。为了解决这些问题，可以使用信号相干性，因为它们可以被视为不相干的干扰和噪声。相干因子（CF）对相位像差敏感，因此在本研究中采用。此外，卷积波束形成算法（COBA）专门利用自相关运算来提高信号相干性并有效降低噪声。因此，我们首先利用 CF 来检测局部相干性及其最大化准则，作为估计声速以校正相位畸变的方法。然后，使用CF作为自适应权重因子来抑制噪声，在此基础上，我们开发了一种短滞后COBA来进一步增强图像质量，简称CF_SLCOBA方法。进行了模拟和实验来评估所提出方法的性能。结果表明，CF_SLCOBA方法与CF相比，分辨率提高了约26.8%；实验中，与COBA相比，对比度（CR）约为92.0%。同时，该方法在相位像差校正方面具有良好的性能。这表明所提出的方法可以为重建高质量图像提供好处，这也表明它为实际应用提供了一定的潜力。