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Eigenspace-based minimum variance beamformer combined with sign coherence factor: Application to linear-array photoacoustic imaging

机译:基于EIGENSPACE的最小方差波束形成器与标志相干因子相结合:应用于线性阵列光声成像

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摘要

Photoacoustic (PA) imaging combining the advantages of high resolution of ultrasound imaging and high contrast of optical imaging provides images with good quality. PA imaging often suffers from disadvantages such as clutter noises and decreased signal-to-noise-ratio at higher depths. One studied method to reduce clutter noises is to use weighting factors such as coherence factor (CF) and its modified versions that improve resolution and contrast of images. In this study, we combined the Eigen-space based minimum variance (EIBMV) beamformer with the sign coherence factor (SCF) and show the ability of these methods for noise reduction when they are used in combination with each other. In addition, we compared the proposed method with delay-and-sum (DAS) and minimum variance (MV) beamformers in simulated and experimental studies. The simulation results show that the proposed EIBMV-SCF method improves the SNR about 94 dB, 87.65 dB, and 62.29 dB compared to the DAS, MV, and EIBMV, respectively, and the corresponding improvements were 79.37/34.43 dB, 77.25/26.96 dB, and 33.19/25.56 dB in the ex vivo/in vivo experiments.
机译:光声(PA)成像结合了高分辨率超声成像和光学成像的高对比度的优点提供了质量良好的图像。 PA成像通常遭受诸如杂波噪声等缺点,并且在更高深度下降低信噪比。减少杂波噪声的一个研究方法是使用加权因子,例如相干因子(CF)及其修改版本,其改善图像的分辨率和对比度。在这项研究中,我们将基于特征空间的最小方差(EIBMV)波束形成器与标志相干因子(SCF)组合,并显示这些方法在彼此组合使用时降噪方法的能力。此外,我们将提出的方法与模拟和实验研究中的延迟和和(DAS)和最小方差(MV)波束形成器进行了比较。仿真结果表明,与DAS,MV和EIBMV相比,所提出的EIBMV-SCF方法可改善约94dB,87.65dB和62.29dB的SNR,相应的改进为79.37 / 34.43 dB,77.25 / 26.96 dB在exvivo /体内实验中,33.19 / 25.56 dB。

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