Research on processing methods to improve the signal-to-noise ratio of a magnetoacoustic signal

被引:4
作者
Zhang, Shunqi [1 ]
Ma, Ren [1 ]
Zhou, Xiaoqing [1 ]
Yin, Tao [1 ]
Liu, Zhipeng [1 ]
机构
[1] Chinese Acad Med Sci & Peking Union Med Coll, Inst Biomed Engn, Tianjin 300192, Peoples R China
基金
中国国家自然科学基金;
关键词
Magnetoacoustic signal; Signal processing; Signal-to-noise ratio; Coded excitation; M-sequence; Chirp signal;
D O I
10.1016/j.bspc.2020.101955
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Objective: Magnetoacoustic imaging provides valuable information for monitoring bioelectricity and early tumor diagnosis. However, the low signal-to-noise ratio (SNR) of the magnetoacoustic signal, resulting from the single pulsed excitation, limits the imaging quality. A signal processing method of frequency coding excitation is proposed to increase the SNR of the magnetoacoustic signal. Methods: Chirp signal frequency coding is studied by simulation. M-sequence phase coding and wave averaging are also adopted in the studies. The experiments are conducted using a phantom of beef and fat with embedded copper rings. Two evaluation parameters, SNR improvement per unit pulse duration and SNR improvement per unit pulse duration per unit time, as well as the processing speed, are proposed to evaluate the SNR improvement. Results: The results show that the frequency coding approach can rapidly improve the SNR of the magnetoacoustic signal as well as phase coding excitation, compared with the wave averaging approach. Conclusions: A method of combining the coding and waveform averaging to improve the SNR of magnetoacoustic signal has been developed. A higher SNR improvement in the magnetoacoustic signal, up to 235x, with a short processing time of 0.867 s, can be obtained. Significance: This study provides an effective method to improve the SNR in magnetoacoustic imaging. (C) 2020 Elsevier Ltd. All rights reserved.
引用
收藏
页数:8
相关论文
共 24 条
  • [1] Frequency-modulated magneto-acoustic detection and imaging
    Aliroteh, M. S.
    Scott, G.
    Arbabian, A.
    [J]. ELECTRONICS LETTERS, 2014, 50 (11) : 790 - 791
  • [2] WiFi-Based Passive Bistatic Radar: Data Processing Schemes and Experimental Results
    Colone, Fabiola
    Falcone, Paolo
    Bongioanni, Carlo
    Lombardo, Pierfrancesco
    [J]. IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2012, 48 (02) : 1061 - 1079
  • [3] Electromagnetic Acoustic Imaging
    Emerson, Jane F.
    Chang, David B.
    McNaughton, Stuart
    Jeong, Jong Seob
    Shung, K. Kirk
    Cerwin, Stephen A.
    [J]. IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL, 2013, 60 (02) : 364 - 372
  • [4] Coexisting and mixing phenomena of thermoacoustic and magnetoacoustic waves in water
    Feng, Xiaohua
    Gao, Fei
    Kishor, Rahul
    Zheng, Yuanjin
    [J]. SCIENTIFIC REPORTS, 2015, 5
  • [5] The dielectric properties of biological tissues .2. Measurements in the frequency range 10 Hz to 20 GHz
    Gabriel, S
    Lau, RW
    Gabriel, C
    [J]. PHYSICS IN MEDICINE AND BIOLOGY, 1996, 41 (11) : 2251 - 2269
  • [6] Lorentz force electrical impedance tomography
    Grasland-Mongrain, P.
    Mari, J. -M.
    Chapelon, J. -Y.
    Lafon, C.
    [J]. IRBM, 2013, 34 (4-5) : 357 - 360
  • [7] Electrical conductivity measurement of excised human metastatic liver tumours before and after thermal ablation
    Haemmerich, Dieter
    Schutt, David J.
    Wright, Andrew W.
    Webster, John G.
    Mahvi, David M.
    [J]. PHYSIOLOGICAL MEASUREMENT, 2009, 30 (05) : 459 - 466
  • [8] Jibiki Takao, 2001, Igaku Butsuri, V21, P136
  • [9] Magnetoacoustic tomography with magnetic induction (MAT-MI) for imaging electrical conductivity of biological tissue: a tutorial review
    Li, Xu
    Yu, Kai
    He, Bin
    [J]. PHYSICS IN MEDICINE AND BIOLOGY, 2016, 61 (18) : R249 - R270
  • [10] Multi-excitation Magnetoacoustic Tomography With Magnetic Induction for Bioimpedance Imaging
    Li, Xu
    He, Bin
    [J]. IEEE TRANSACTIONS ON MEDICAL IMAGING, 2010, 29 (10) : 1759 - 1767