The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, People's Republic of China.
Med Phys. 2019 Oct;46(10):4441-4454. doi: 10.1002/mp.13714. Epub 2019 Aug 10.
Passive acoustic mapping (PAM) has been proposed as a means of monitoring ultrasound therapy, particularly nonthermal cavitation-mediated applications. In PAM, the most common beamforming algorithm is a delay, sum, and integrate (DSAI) approach. However, using DSAI leads to low-quality images for the case where a narrow-aperture receiving array such as a standard B-mode linear array is used. This study aims to propose an enhanced linear-array PAM algorithm based on delay, multiply, sum, and integrate (DMSAI).
In the proposed algorithm, before summation, the delayed signals are combinatorially coupled and multiplied, which means that the beamformed output of the proposed algorithm is the spatial coherence of received acoustic emissions. We tested the performance of the proposed DMSAI using both simulated and experimental data and compared it with DSAI. The reconstructed cavitation images were evaluated quantitatively by using source location errors between the two algorithms, full width at half maximum (FWHM), size of point spread function (A area), signal-to-noise ratio (SNR), and computational time.
The results of simulations and experiments for single cavitation source show that, by introducing DMSAI, the FWHM and the A area are reduced and the SNR is improved compared with those obtained by DSAI. The simulation results for two symmetric or nonsymmetric cavitation sources and multiple cavitation sources show that DMSAI can significantly reduce the A area and improve the SNR, therefore improving the detectability of multiple cavitation sources.
The results indicate that the proposed DMSAI algorithm outperforms the conventionally used DSAI algorithm. This work may have the potential of providing an appropriate method for ultrasound therapy monitoring.
被动声学成像（PAM）已被提议作为监测超声治疗的一种手段，特别是用于非热空化介导的应用。在 PAM 中，最常用的波束形成算法是延迟、求和、积分（DSAI）方法。然而，对于使用窄孔径接收阵列（如标准 B 模式线性阵列）的情况，使用 DSAI 会导致图像质量较低。本研究旨在提出一种基于延迟、乘法、求和、积分（DMSAI）的增强型线性阵列 PAM 算法。
在提出的算法中，在求和之前，延迟信号进行组合耦合和乘法运算，这意味着所提出的算法的波束形成输出是接收声发射的空间相干性。我们使用模拟和实验数据测试了所提出的 DMSAI 的性能，并将其与 DSAI 进行了比较。通过两种算法之间的声源位置误差、半最大值全宽（FWHM）、点扩散函数（A 区）大小、信噪比（SNR）和计算时间，对重建的空化图像进行了定量评估。
单声源模拟和实验结果表明，通过引入 DMSAI，与 DSAI 相比，FWHM 和 A 区减小，SNR 提高。对于两个对称或非对称的空化源和多个空化源的模拟结果表明，DMSAI 可以显著减小 A 区并提高 SNR，从而提高多个空化源的可检测性。
结果表明，所提出的 DMSAI 算法优于传统的 DSAI 算法。这项工作可能有潜力为超声治疗监测提供一种合适的方法。
