新算法提升超声血管成像分辨率与信噪比，适合临床使用。
Enhanced Acoustic Beamforming with Sub-Aperture Angular Multiply and Sum -- in vivo and in Human Demonstration
- 结合时序与空间相干性，改进传统超声波束成形方法
- 在活体实验中使信噪比提升18分贝，对比度噪声比提升11分贝
- 已在兔肾和人体淋巴结验证，适用于临床超声成像
功率多普勒超声广泛用于无创血管成像，但当前主流的延迟求和（DAS）波束成形法存在分辨率低、旁瓣高的问题。本文提出子孔径角乘积求和（SAMAS）算法，融合了基于信号时序相干性的帧乘积求和（FMAS）与基于空间相干性的子孔径（ASAP）算法的优点。经体外实验优化相位信息使用及子孔径配对策略后，该算法在活体实验中分别于兔子肾脏和人体淋巴结进行测试，采用静脉注射造影剂获取的超快超声图像显示，相较于DAS，SAMAS在所有测试中均显著提升了信噪比（SNR）与对比度噪声比（CNR），平均分别提高18 dB和11 dB。该研究展示了一种具有广泛应用前景的血管成像新方法。
原文摘要 · Abstract (English)
Power Doppler ultrasound is in widespread clinical use for non-invasive vascular imaging but the most common current method - Delay and Sum (DAS) beamforming - suffers from limited resolution and high side-lobes. Here we propose the Sub-Aperture Angular Multiply and Sum (SAMAS) algorithm; it combines the advantages of two recent non-linear beamformers, Frame Multiply and Sum (FMAS) which uses signal temporal coherence and the acoustic sub-aperture (ASAP) algorithm, which uses signal spatial coherence, respectively. Following in vitro experiments to optimise the algorithm, particularly the use of phase information and sub-aperture pairing, it was evaluated in vivo, first in a rabbit kidney and then in human lymph node, using ultrafast ultrasound images obtained with intravenous contrast agents. The SAMAS algorithm improved the CNR and SNR across all tests, on average raising the CNR by 11 dB and the SNR by 18 dB over DAS in vivo. This work demonstrates a promising vascular imaging method that could have widespread clinical utility.
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