摘 要：采用低频超声胸腔成像技术对实际的人体胸腔进行信号采集时，超声换能器接收到的胸腔信号中会含有大量的噪声干扰，较大地影响了成像效果。因此文章通过 COMSOL 平台建立二维胸腔模型，在接收到的胸腔信号中添加信噪比为 2 dB高斯白噪声作为模拟噪声。通过小波阈值降噪技术对含噪的胸腔信号进行处理，发现 db7 小波基在分解层数为 1 层，阈值准则为 minimaxi，软阈值处理函数时可以有效降噪，提高数据的信噪比。
关键词：低频超声；COMSOL；小波阈值
DOI:10.19850/j.cnki.2096-4706.2022.09.029
中图分类号：TP391 文献标识码：A 文章编号：2096-4706（2022）09-0114-04
Denoising of Low-frequency Ultrasound Signal in Thoracic Cavity Based on Wavelet Threshold
ZHOU Yinggang, LUO Hao
(School of Artificial Intelligence, Shenyang University of Technology, Shenyang 110870, China)
Abstract: When low-frequency ultrasound thoracic imaging technology is used for signal acquisition of the actual human thoracic cavity, the thoracic cavity signal received by the ultrasound transducer will contain a large amount of noise interference, which greatly affects the imaging effect. Therefore, in this paper, a two-dimensional thoracic cavity model is established by COMSOL platform, and the received thoracic cavity signal is added with 2 dB Gaussian white noise with a signal-to-noise ratio of 2 dB as the analog noise. The noise-containing thoracic cavity signal is processed by wavelet threshold noise reduction technology, and it is found that the db7 wavelet basis can effectively reduce the noise and improve the signal-to-noise ratio of the data when the number of decomposition layers is 1, the threshold criterion is minimaxi, and the soft threshold is used to process the function.
Keywords: low-frequency ultrasound; COMSOL; wavelet threshold
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作者简介：周英钢（1971—），男，汉族，辽宁凌源人，副教授，工学博士，研究方向：低频超声胸腔成像技术、电容层析成像；罗浩（1995—），男，汉族，吉林松原人，硕士在读，研究方向：低频超声胸腔成像技术。