Research on coded excitation processing method for magneto-acoustic signal_Journal of Biomedical Engineering

Authors：

ZHANG Shunqi , YIN Tao ,  LIU Zhipeng

Institute of Biomedical Engineering, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300192, P.R.China;

Corresponding author：

LIU Zhipeng, Email: lzpeng67@163.com

Keywords：

magneto-acoustic coupling effect; coded excitation; Barker code; Golay code; signal-to-noise ratio

DOI：

10.7507/1001-5515.201702042

Video：

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Detecting and imaging method of biological electrical characteristics based on magneto-acoustic coupling effect gives valuable information of tissue in early tumor diagnosis and bioelectrical current monitoring. Normal exciting and receiving method is to use single pulse. In this method the signal to noise ratio (SNR) is limited, so the imaging quality and imaging speed are low. In this study, we propose a processing method based on coded excitation to improve SNR and shorten the processing time. The processing method using 13 bit Barker coded excitation and 16 bit Golay code excitation are studied by simulation and experiments. The results show that SNR of magneto-acoustic signal is improved by 20.96 dB and 20.62 dB by using 13 bit Barker coded and 16 bit Golay coded excitation, respectively. It also indicates the processing time is short compare to single pulse mode. In the case of the SNR increasing, the overall acquiring and processing time under 13 bit Barker coded excitation and the 16 bit Golay coded excitation is shortened to 3.62% and 4.73%, respectively, compared to the single pulse excitation with waveform averaging method. In conclusion, the coded excitation will be significant for the improvement of magneto-acoustic signal SNR and imaging quality.

Citation： ZHANG Shunqi, YIN Tao, LIU Zhipeng. Research on coded excitation processing method for magneto-acoustic signal. Journal of Biomedical Engineering, 2017, 34(5): 653-659. doi: 10.7507/1001-5515.201702042 Copy

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8.	周廉, 朱善安, 贺斌. 三维磁感应磁声成像的新算法研究. 电子学报, 2013, 41(2): 288-2940.
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11.	Yu Kai, Shao Qi, Ashkenazi S, et al. <italic>In vivo</italic> electrical conductivity contrast imaging in a mouse model of Cancer using High-Frequency magnetoacoustic tomography with magnetic induction (hfMAT-MI) IEEE Trans Med Imaging, 2016, 35(10): 2301-2311.
12.	Zhang Shunqi, Zhou Xiaoqing, Ma Ren, et al. A study on locating the sonic source of sinusoidal magneto-acoustic signals using a vector method. Biomed Mater Eng, 2015, 26(1): S1177-S1184.
13.	张顺起, 周晓青, 殷涛, 等. 基于连续波的频域磁声耦合成像方法正问题研究. 生物医学工程研究, 2015, 34(1): 1-60.
14.	Aliroteh M S, Scott G, Arbabian A. Frequency-modulated magneto-acoustic detection and imaging. Electron Lett, 2014, 50(11): 790-791.
15.	Renzhiglova E, Ivantsiv V, Xu Yuan. Difference frequency Magneto-Acousto-Electrical tomography (DF-MAET): application of Ultrasound-Induced radiation force to imaging electrical current density. IEEE Trans Ultrason Ferroelectr Freq Control, 2010, 57(11): 2391-2402.
16.	Guo Liang, Liu Guangfu, Yang Yanju. Difference frequency magnetoacoustic tomography without static magnetic field. Applied Physics Express, 2015, 8(8): 086601.
17.	周浩, 王友钊, 郑音飞. 医学超声编码激励技术研究进展. 浙江大学学报:工学版, 2011, 45(2): 387-3910.
18.	于超鹏, 郝亮飞, 谢金华. 线性调频和巴克码组合调制雷达信号. 探测与控制学报, 2009, 31(5): 20-240.
19.	Xu Yuan, He Bin. Magnetoacoustic tomography with magnetic induction (MAT-MI) Phys Med Biol, 2005, 50(21): 5175-5187.
20.	吴振兴, 阮怀林, 何宇. 基于谱特征的雷达信号脉内编码调制样式识别. 电子信息对抗技术, 2015, 30(2): 16-20, 660.
21.	刘桂雄, 唐文明, 纪轩荣. 准单次正交互补 Golay 码超声编解码方法研究. 仪器仪表学报, 2016, 37(6): 1309-13150.

1. Wang Hang, He Yong, Yang Min, et al. Dielectric properties of human liver from 10 Hz to 100 MHz: normal liver, hepatocellular carcinoma, hepatic fibrosis and liver hemangioma. Biomed Mater Eng, 2014, 24(6): 2725-2732.
2. Gabriel S, Lau R W, Gabriel C. The dielectric properties of biological tissues II: Measurements on the frequency range 10Hz to 20 GHz. Phys Med Biol, 1996, 41(11): 2251-2269.
3. Surowiec A J, Stuchly S S, Barr J R, et al. Dielectric-properties of breast-carcinoma and the surrounding tissues. IEEE Trans Biomed Eng, 1988, 35(4): 257-263.
4. Han W, Jatin S, Robert S B. Hall effect imaging. IEEE Transactions on Biomedical Engineering, 1998, 45(1): 119-124.
5. Roth B J. The role of magnetic forces in biology and medicine. Exp Biol Med, 2011, 236(2): 132-137.
6. Emerson J F, Chang D B, Mcnaughton S, et al. Electromagnetic acoustic imaging. IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control, 2013, 60(2): 364-372.
7. Sun Xiaodong, Wang Xin, Zhou Yuqi, et al. Reception pattern influence on magnetoacoustic tomography with magnetic induction. Chinese Physics B, 2015, 24(1): 329-337.
8. 周廉, 朱善安, 贺斌. 三维磁感应磁声成像的新算法研究. 电子学报, 2013, 41(2): 288-2940.
9. Towe B C, Islam M R. A magneto-acoustic method for the noninvasive measurement of bioelectric currents. IEEE Transactions on Biomedical Engineering, 1988, 35(10): 892-894.
10. Roth B J, Basser P J, Wikswo J P. A theoretical-model for magnetoacoustic imaging of bioelectric currents. IEEE Trans Biomed Eng, 1994, 41(8): 723-728.
11. Yu Kai, Shao Qi, Ashkenazi S, et al. <italic>In vivo</italic> electrical conductivity contrast imaging in a mouse model of Cancer using High-Frequency magnetoacoustic tomography with magnetic induction (hfMAT-MI) IEEE Trans Med Imaging, 2016, 35(10): 2301-2311.
12. Zhang Shunqi, Zhou Xiaoqing, Ma Ren, et al. A study on locating the sonic source of sinusoidal magneto-acoustic signals using a vector method. Biomed Mater Eng, 2015, 26(1): S1177-S1184.
13. 张顺起, 周晓青, 殷涛, 等. 基于连续波的频域磁声耦合成像方法正问题研究. 生物医学工程研究, 2015, 34(1): 1-60.
14. Aliroteh M S, Scott G, Arbabian A. Frequency-modulated magneto-acoustic detection and imaging. Electron Lett, 2014, 50(11): 790-791.
15. Renzhiglova E, Ivantsiv V, Xu Yuan. Difference frequency Magneto-Acousto-Electrical tomography (DF-MAET): application of Ultrasound-Induced radiation force to imaging electrical current density. IEEE Trans Ultrason Ferroelectr Freq Control, 2010, 57(11): 2391-2402.
16. Guo Liang, Liu Guangfu, Yang Yanju. Difference frequency magnetoacoustic tomography without static magnetic field. Applied Physics Express, 2015, 8(8): 086601.
17. 周浩, 王友钊, 郑音飞. 医学超声编码激励技术研究进展. 浙江大学学报:工学版, 2011, 45(2): 387-3910.
18. 于超鹏, 郝亮飞, 谢金华. 线性调频和巴克码组合调制雷达信号. 探测与控制学报, 2009, 31(5): 20-240.
19. Xu Yuan, He Bin. Magnetoacoustic tomography with magnetic induction (MAT-MI) Phys Med Biol, 2005, 50(21): 5175-5187.
20. 吴振兴, 阮怀林, 何宇. 基于谱特征的雷达信号脉内编码调制样式识别. 电子信息对抗技术, 2015, 30(2): 16-20, 660.
21. 刘桂雄, 唐文明, 纪轩荣. 准单次正交互补 Golay 码超声编解码方法研究. 仪器仪表学报, 2016, 37(6): 1309-13150.

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