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首页> 外文期刊>IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control >Combining Slow Flow Techniques With Adaptive Demodulation for Improved Perfusion Ultrasound Imaging Without Contrast
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Combining Slow Flow Techniques With Adaptive Demodulation for Improved Perfusion Ultrasound Imaging Without Contrast

机译：将缓慢的流动技术与自适应解调相结合，以改善灌注超声成像而没有对比

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Noncontrast perfusion ultrasound imaging remains challenging due to spectral broadening of the tissue clutter signal caused by patient and sonographer hand motion. To address this problem, we previously introduced an adaptive demodulation scheme to suppress the bandwidth of tissue prior to high-pass filtering. Our initial implementation used single plane wave power Doppler imaging and a conventional tissue filter. Recent advancements in beamforming and tissue filtering have been proposed for improved slow flow imaging, including coherent flow power Doppler (CFPD) imaging and singular value decomposition (SVD) filtering. Here, we aim to evaluate adaptive demodulation in conjunction with improvements in beamforming and filtering using simulations, single-vessel phantoms, and an in vivo liver tumor embolization study. We show that simulated blood-to-background contrast-to-noise ratios are highest when using adaptive demodulation with CFPD and a 100-ms ensemble, which resulted in a 13.6-dB average increase in contrast-to-noise ratio compared to basic IIR filtering alone. We also show that combining adaptive demodulation with SVD and with CFPD + SVD results in 9.3- and 19-dB increases in contrast-to-noise ratios compared to IIR filtering alone at 700- and 500-ms ensembles for phantom data with 1- and 5-mm/s average flows, respectively. In general, combining techniques resulted in higher signal-to-noise, contrast-to-noise, and generalized contrast-to-noise ratios in both simulations and phantoms. Finally, adaptive demodulation with SVD resulted in the largest qualitative and quantitative changes in tumor-to-background contrast postembolization.
机译：由于患者和超声波手动动作引起的组织杂波信号的光谱扩展，非共同灌注超声成像仍然具有挑战性。为了解决这个问题，我们之前引入了一种自适应解调方案，以在高通滤波之前抑制组织的带宽。我们的初始实现使用了单面波功率多普勒成像和传统的组织过滤器。已经提出了用于改进的慢速成像的波束成形和组织过滤的最新进步，包括相干流量多普勒（CFPD）成像和奇异值分解（SVD）滤波。在这里，我们的目标是使用模拟，单血管素和体内肝肿瘤栓塞研究结合使用模拟和滤波的改进来评估自适应解调。我们表明，当使用CFPD和100-MS合奏的自适应解调时，模拟血液到背景对比度噪声比率最高，这导致与基本IIR相比的对比度对比度的平均增加13.6dB平均增加单独过滤。我们还表明，与SVD和CFPD + SVD的适应性解调与CFPD + SVD相结合，与IIR滤波在700-和500-MS合奏中的幻像数据中与1-和分别为5毫米/秒的平均流动。通常，组合技术导致较高的信噪比，对比度，以及两种模拟和幻像中的广义对比度噪声比。最后，随着SVD的自适应解调导致肿瘤到背景对比后栓塞中最大的定性和定量变化。

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