ELECTROMAGNETISM, OPTICS, ACOUSTICS, HEAT TRANSFER, CLASSICAL MECHANICS, AND FLUID DYNAMICS |
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Performance improvement of magneto-acousto-electrical tomography for biological tissues with sinusoid-Barker coded excitation |
Zheng-Feng Yu(余正风)1, Yan Zhou(周)1, Yu-Zhi Li(李禹志)1, Qing-Yu Ma(马青玉)1, Ge-Pu Guo(郭各朴)1, Juan Tu(屠娟)2, Dong Zhang(章东)2 |
1 Jiangsu Provincial Engineering Laboratory of Audio Technology, School of Physics and Technology, Nanjing Normal University, Nanjing 210023, China;
2 Institute of Acoustics, Nanjing University, Nanjing 210093, China |
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Abstract By combining magnetics, acoustics and electrics, the magneto-acoustic-electrical tomography (MAET) proves to possess the capability of differentiating electrical impedance variation and thus improving the spatial resolution. However, the signal-to-noise ratio (SNR) of the collected MAET signal is still unsatisfactory for biological tissues with low-level electrical conductivity. In this study, the formula of MAET measurement with sinusoid-Barker coded excitation is derived and simplified for a planar piston transducer. Numerical simulations are conducted for a four-layered gel phantom with the 13-bit sinusoid-Barker coded excitation, and the performances of wave packet recovery with side-lobe suppression are improved by using the mismatched compression filter, which is also demonstrated by experimentally measuring a three-layered gel phantom. It is demonstrated that comparing with the single-cycle sinusoidal excitation, the amplitude of the driving signal can be reduced greatly with an SNR enhancement of 10 dB using the 13-bit sinusoid-Barker coded excitation. The amplitude and polarity of the wave packet filtered from the collected MAET signal can be used to achieve the conductivity derivative at the tissue boundary. In this study, we apply the sinusoid-Barker coded modulation method and the mismatched suppression scheme to MAET measurement to ensure the safety for biological tissues with improved SNR and spatial resolution, and suggest the potential applications in biomedical imaging.
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Received: 28 May 2018
Revised: 03 July 2018
Accepted manuscript online:
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PACS:
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43.80.Ev
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(Acoustical measurement methods in biological systems and media)
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72.55.+s
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(Magnetoacoustic effects)
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Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 11474166 and 11604156), the Natural Science Foundation of Jiangsu Province, China (Grant No. BK20161013), the Postdoctoral Science Foundation of China (Grant No. 2016M591874), the Postgraduate Research & Practice Innovation Program of Jiangsu Province, China (Grant No. KYCX17_1083), and the Priority Academic Program Development of Jiangsu Provincial Higher Education Institutions, China. |
Corresponding Authors:
Qing-Yu Ma
E-mail: maqingyu@njnu.edu.cn
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Cite this article:
Zheng-Feng Yu(余正风), Yan Zhou(周), Yu-Zhi Li(李禹志), Qing-Yu Ma(马青玉), Ge-Pu Guo(郭各朴), Juan Tu(屠娟), Dong Zhang(章东) Performance improvement of magneto-acousto-electrical tomography for biological tissues with sinusoid-Barker coded excitation 2018 Chin. Phys. B 27 094302
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[1] |
Peters M J, Stinstra G and Hendriks M 2001 Electromagnetics 21 545
|
[2] |
Gielen F L H, Wallinga-de Jonge W and Boon K L 1984 Med. Biol. Eng. Comput. 22 569
|
[3] |
Gabriel C, Gabriel S and Corthout E 1996 Phys. Med. Biol. 41 2231
|
[4] |
Surowiec A J, Stuchly S S, Barr J R, et al. 1988 IEEE Trans. Biomed. Eng. 35 257
|
[5] |
Metherall P, Barber D C, Smallwood R H, et al. 1996 Nature 380 509
|
[6] |
Guo G, Su H, Ding H, et al. 2017 Acta. Phys. Sin. 66 164301
|
[7] |
Lionheart W R B 2004 Physiol. Meas. 25 125
|
[8] |
Wang Q, Wang H, Zhang R, et al. 2012 Rev. Sci. Instrum. 83 104707
|
[9] |
Li Y, Liu G, Xia H, et al. 2018 IEEE Trans. Magn. 54 5100704
|
[10] |
Zengin R and Gencer N G 2016 Phys. Med. Biol. 61 5887
|
[11] |
Roth B J and Schalte K 2009 Med. Biol. Eng. Comput. 47 573
|
[12] |
Kunyansky L, Ingram C P and Witte R S 2017 Phys. Med. Biol. 62 3025
|
[13] |
Han W, Shah J and Balaban R S 1998 IEEE Trans. Biomed. Eng. 45 119
|
[14] |
Han W 1999 Ultras. Imaging. 21 186
|
[15] |
Xu Y and He B 2005 Phys. Med. Biol. 50 5175
|
[16] |
Li Y, Liu Z, Ma Q, et al. 2010 Chin. Phys. Lett. 27 084302
|
[17] |
Guo G, Ding H, Dai S, et al. 2017 Chin. Phys. B 26 084301
|
[18] |
Ammari H, Qiu L, Santosa F, et al. 2017 Inverse Problems 33 125006
|
[19] |
Haider S, Hrbek A and Xu Y 2008 Physiol. Meas. 29 S41
|
[20] |
Zhou Y, Ma Q, Guo G, et al. 2018 IEEE Trans. Biomed. Eng. 65 1086
|
[21] |
Kunyansky L 2012 Inverse Problems 28 035002
|
[22] |
Ammari H, Grasland-Mongrain P, Millen P, et al. 2015 J. Math. Pures App. 103 1390
|
[23] |
Polydorides N 2018 Physiol. Meas. 39 044003
|
[24] |
Grasland-Mongrain P, Mari J M, Chapelon J Y, et al. 2013 IRBM 34 357
|
[25] |
Renzhiglova E, Ivantsiv V and Xu, Y 2010 IEEE Trans. Ultrason., Ferroelectr., Freq. Control. 57 2391
|
[26] |
Pedersen M H, Misaridis T X and Jensen J A 2003 Ultrasound Med. Biol. 29 895
|
[27] |
Dantas T M, Costa-Felix R P B and Machado J C 2018 Appl. Acoust. 130 238
|
[28] |
Sun Z, Liu G, Xia H, et al. 2018 IEEE Trans. Ultrason., Ferroelectr. Freq. Control. 65 168
|
[29] |
Sun Z, Liu G and Xia H 2017 Chin. Phys. B 26 124302
|
[30] |
Sun Z, Liu G and Xia H 2018 Chin. Phys. Lett. 35 014301
|
[31] |
Nowicki A, Klimonda Z, Lewandowski M, et al. 2006 Ultrasonics 44 121
|
[32] |
Hansen K L, Udesen J, Gran F, et al. 2009 Ultraschall. Der. Med. 30 471
|
[33] |
Nowicki A, Trots I, Lewin P A, et al. 2007 Ultrasonics 47 64
|
[34] |
Xiang L, Zhao H and Gao S 2009 Ultrasound. Med. Biol. 35 94
|
[35] |
Sun X, Wang X, Zhou Y, et al. 2015 Chin. Phys. B 24 014302
|
[36] |
Grasland-Mongrain P, Destrempes F, Mari J M, et al. 2015 Phys. Med. Biol. 60 3747
|
[37] |
Rihaczek A W and Golden R M 1971 IEEE Trans. Aero. Elec. Sys. AES-7 1087
|
[38] |
O'Donnell M 1992 IEEE Trans. Ultrason., Ferroelectr. Freq. Control. 39 341
|
[39] |
Fu J, Wei G, Huang Q, et al. 2014 Biomed. Signal. Proces. 13 306
|
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