Sinusoid-Golay编码单脉冲激励提升磁声电成像精度

Precision improvement of magneto-acousto-electrical imaging based on the excitation of single Sinusoid-Golay coded pulse

针对低电导率生物组织的成像需求,利用Sinusoid-Golay编码单脉冲激励提高磁声电信号的信噪比和定位精度,实现了高精度的磁声电成像。首先,在考虑换能器指向性的基础上,推导了Sinusoid-Golay编码单脉冲激励的磁声电理论公式,并引入激励转换因子和自相关计算,实现磁声电信号测量和解码重建,理论证明了N位Sinusoid-Golay编码可以将磁声电信号的主瓣幅度提高2N倍,并具有良好的脉冲压缩和噪声抑制能力。然后,在5 dB信噪比条件下,模拟了16位Sinusoid-Golay编码单脉冲激励层状组织模型所产生的磁声电信号,通过匹配滤波解码和叠加增强了磁声电信号的主瓣,并消除了其旁瓣,实现了组织边界的精确定位和电导率梯度的准确重建。最后,搭建了磁声电检测和线性扫描成像系统,利用正弦单周期和16位Sinusoid-Golay编码单脉冲激励,对三层凝胶仿体进行了磁声电测量和图像重建。Sinusoid-Golay编码单脉冲激励能够提高磁声电信号的信噪比约6.5 dB,并精确重构了组织边界电导率变化的幅值和极性。该研究为基于电学特性差异的组织病变早期检测提供了一种高精度磁声电快速成像方法。

Based on imaging requirements for biological tissues with low-level electrical conductivities,the single Sinusoid-Golay coded pulse excitation is introduced to enhance the signal-to-noise ratio(SNR)and the positioning accuracy of magneto-acoustoelectrical(MAE)signals,resulting in the improved precision of MAE imaging.Firstly,the formula of the detected MAE signal is derived for the single-excitation of a Sinusoid-Golay coded pulse with the consideration of the radiation pattern of actual transducers.The MAE measurement of the dual-excitation is realized by introducing the excitation conversion factor and the autocorrelation calculation.The main lobe amplitude enhancement by 2N times is demonstrated in theory for the N-bit Sinusoid-Golay coded pulse excitation with the favorable capabilities of pulse compression and noise suppression.Then,numerical studies for MAE signals are conducted for a layered gel model under the SNR of 5 dB.The pulse compression and suppression of side-lobes for decoded MAE signals are accomplished by the matched filter and the wave superposition with improved accuracies of boundary positions and conductivity gradients.Finally,compared with the one-cycle sinusoidal excitation,the SNR improvement of about 6.5 dB is proved by the experimental measurement of MAE signals for a three-layer gel model with the 16-bit Sinusoid-Golay coded pulse excitation.The image of tissue boundaries is reconstructed accurately in terms of amplitude and polarity of conductivity variations.This study provides an optimized fast imaging technology for the detection of early tissue lesions based on the difference of electrical properties.