Chinese Academy of Sciences, Institute of Electrical Engineering, Beijing, People's Republic of China.
Shandong University of Science and Technology, Qingdao, People's Republic of China.
Phys Med Biol. 2023 Jul 10;68(14). doi: 10.1088/1361-6560/ace09c.
Magneto-acousto-electrical tomography (MAET), which couples ultrasound imaging with electrical impedance tomography, is an electrical property imaging method which is expected to have a wide range of clinical applications, including the early detection of breast and liver cancers. Obviously, as a coupled imaging method, how to improve the signal-to-noise ratio (SNR) is a key issue in the imaging process. In this paper, a wavelet filtering method is introduced into MAET, which includes the filtering effect of the db6 wavelet, and its filtering effect at different decomposition levels. At the same time, based on the Lorentz reciprocity theorem, the wave equation satisfied by the detected voltage obtained by electrode was deduced. We also built an experimental platform to acquire signals by keeping the position of the target unchanged and moving the ultrasound transducer along the trajectory of a circular arc. The experimental results show that the wavelet filtering scheme proposed in this paper improves the SNR of the detected signal of 15.1 dB, and the images of electrical properties of the phantom and pork from isolated tissues were realized by the filtered signal of the db6 wavelet and time reversal method, which reflects the interface of electrical conductivity change of tissues. This scanning method, of fixing the target body and rotating the transducer, can effectively reduce the error and noise caused by the movement of the detection electrodes in the experiment. The filtering technique and imaging algorithm proposed in this paper have improved the SNR and contrast of the images. Thus, the images of the low conductivity phantom with 0.2 S mand isolated tissue were obtained, which indicates that the MAET has good prospects in clinical applications.
磁声电成像（MAET）结合了超声成像和电阻抗断层成像，是一种电特性成像方法，预计在临床应用中有广泛的应用前景，包括早期检测乳腺癌和肝癌。显然，作为一种耦合成像方法，如何提高信号噪声比（SNR）是成像过程中的一个关键问题。在本文中，将一种小波滤波方法引入 MAET 中，该方法包括 db6 小波的滤波效果及其在不同分解层次上的滤波效果。同时，基于洛伦兹互易定理，推导出通过电极获得的检测电压所满足的波动方程。我们还建立了一个实验平台，通过保持目标位置不变，同时使超声换能器沿着圆弧轨迹移动，来获取信号。实验结果表明，所提出的小波滤波方案提高了检测信号的 SNR 达 15.1dB，并且通过 db6 小波和时间反转方法对滤过信号实现了对组织电导率变化界面的电特性的成像，实现了对离体组织的电特性成像。这种扫描方法，即固定目标体，旋转换能器，能够有效降低实验中检测电极运动带来的误差和噪声。本文提出的滤波技术和成像算法提高了图像的 SNR 和对比度。因此，获得了具有 0.2S/m 低电导率的电特性成像和孤立组织的图像，表明 MAET 在临床应用中有很好的前景。
