[1]陶 进,郭各朴.基于磁致边界振动希尔伯特变换的电导率重建简化算法[J].南京师范大学学报(自然科学版),2017,40(03):94.[doi:10.3969/j.issn.1001-4616.2017.03.014]
 Tao Jin,Guo Gepu.Simplified Conductivity Reconstruction Algorithm Based on HilbertTransform of Magnetic Induced Boundary Vibration[J].Journal of Nanjing Normal University(Natural Science Edition),2017,40(03):94.[doi:10.3969/j.issn.1001-4616.2017.03.014]
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基于磁致边界振动希尔伯特变换的电导率重建简化算法()
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《南京师范大学学报》(自然科学版)[ISSN:1001-4616/CN:32-1239/N]

卷:
第40卷
期数:
2017年03期
页码:
94
栏目:
·物理学·
出版日期:
2017-09-30

文章信息/Info

Title:
Simplified Conductivity Reconstruction Algorithm Based on HilbertTransform of Magnetic Induced Boundary Vibration
文章编号:
1001-4616(2017)03-0094-08
作者:
陶 进郭各朴
南京师范大学物理科学与技术学院,江苏 南京 210023
Author(s):
Tao JinGuo Gepu
School of Physics and Technology,Nanjing Normal University,Nanjing 210023,China
关键词:
磁致边界振动希尔伯特变换换能器指向性电导率重建
Keywords:
magnetic induced boundary vibrationHilbert transformtransducer directivityconductivity reconstruction
分类号:
O421+.2
DOI:
10.3969/j.issn.1001-4616.2017.03.014
文献标志码:
A
摘要:
磁声成像是一种结合电阻抗成像和超声成像优点的多物理场耦合新型成像方法,能实现组织的电阻抗对比成像,重建组织内部电阻抗分布的边界. 本研究首先利用强指向性换能器来提高磁致振动检测的方向精确性,通过磁声声压导数实现边界振动声源法向声压的提取; 然后从换能器的接收声压出发,利用三维空间的格林函数推导了一种基于磁致边界振动法向声压的电导率重建算法,明确了重建过程中声压及其导数的物理意义; 最后建立了圆柱坐标下的柱状扫描系统,对双层偏心圆柱组织模型所产生的声压和换能器所接收到的磁声声波进行了模拟,利用Hilbert变换实现波簇包络定位和相位分析,恢复磁致边界振动声压,重建扫描面的二维电导率分布和模型截面具有较高的一致性,不但获得了组织的边界信息,还实现了组织内部电导率分布的精确重建. 所提出的基于磁致边界振动希尔伯特变换的电阻抗重建简化算法为组织病变的电阻抗成像和磁声诊断提供了新方法.
Abstract:
As a new multi-physics imaging method possessing the advantages of electrical impedance tomography and sonography,magnetic induced acoustic imaging is demonstrated to have the capability of electrical impedance contrast imaging for tissues. In this study,the normal pressure of magnetic induced boundary vibration is retrieved by the derivative calculation from the detected acoustic pressure with a strong directional transducer to enhance the detection accuracy of acoustic transmission.Then,by decomposing Green function in three-dimensional free space,an electrical conductivity reconstruction algorithm based on Hilbert transform of the acoustic pressure of magnetic induced boundary vibration is derived with clear physical meanings of acoustic pressures and the corresponding derivatives.Lastly,a cylindrical scanning system is established to perform numerical simulations for magnetic induced vibration and the acoustic waveforms collected by an experimental transducer for a 2-layer eccentric cylindrical tissue model. By applying Hilbert transform to the collected waveforms for cluster envelope localization and vibration polarity identification,the time dependent pressure distributions of magnetic induced boundary vibrations are restored for further image reconstruction. The reconstructed image of the scanned layer shows good agreement with the cross-sectional conductivity distribution of the model.Not only the boundaries of the model in terms of shape and size,but also precise conductivity distributions inside the conductive media are reconstructed. Therefore,the proposed simplified conductivity reconstruction algorithm,based on Hilbert transform of the normal pressure of magnetic induced boundary vibration,provides a new method for the practical application of magnetic induced acoustic imaging in diagnostic analysis for biological tissues.

参考文献/References:

[1] XU Y,HE B. Magnetoacoustic tomography with magnetic induction[J]. Phys Med Biol,2005,50(21):5 175-5 187.
[2]METHERALL P,BARBER D C,SMALLWOOD R H,et al. Three-dimensional electrical impedance tomography[J]. Nature,1996,380(6 574):509-512.
[3]PAULSON K,LIONHEART W,PIDCOCK M. Optimal experiments in electrical impedance tomography[J]. IEEE Trans Med Imag,1993,12(12):681-686.
[4]HARTOV A,LEPIVERT P,SONI N,et al. Using multiple-electrode impedance measurements to monitor cryosurgery[J]. Med Phys,2002,29(12):2 806-2 814.
[5]WELLS P N T. Ultrasound imaging[J]. Phys Med Biol,2006,51(13):R83-98.
[6]OELZE M L,ZACHARY J F. Examination of cancer in mouse models using high-frequency quantitative ultrasound[J]. Ultrasound Med Biol,2006,32(11):1 639-1 648.
[7]LI X,XU Y,HE B. Magnetoacoustic tomography with magnetic induction for imaging electrical impedance of biological tissue[J]. J Appl Phys,2006,99(6):066112.
[8]MARIAPPAN L,HU G,HE B. Magnetoacoustic tomography with magnetic induction for high-resolution bioimepedance imaging through vector source reconstruction under the static field of MRI magnet[J]. Med Phys,2014,41(2):131-134.
[9]XIA R,LI X,HE B. Magnetoacoustic tomographic imaging of electrical impedance with magnetic induction[J]. Appl Phys Lett,2007,91(8):083903.
[10]BRINKER K,ROTH B J. The effect of electrical anisotropy during magnetoacoustic tomography with magnetic induction[J]. IEEE Trans Biomed Eng,2008,55(5):1 637-1 639.
[11]HU G,HE B. Magnetoacoustic imaging of electrical conductivity of biological tissues at a spatial resolution better than 2 mm[J]. Plos One,2011,6(8):e23421.
[12]SUN X D,ZHOU Y Q,MA Q Y,et al. Radiation theory comparison for magnetoacoustic tomography with magnetic induction(MAT-MI)[J]. Sci Bull,2014,59(26):3 246-3 254.
[13]GUO L,LIU G,YANG Y. Difference frequency magnetoacoustic tomography without static magnetic field[J]. Appl Phys Exp,2015,8(8):086601.
[14]LI Y,MA Q,ZHANG D,et al. Acoustic dipole radiation model for magnetoacoustic tomography with magnetic induction[J]. Chin Phys B,2011,20(8):084302.
[15]LI Y,LIU Z,MA Q,et al. Two-dimensional Lorentz force image reconstruction for magnetoacoustic tomography with magnetic induction[J]. Chin Phys Lett,2010,27(8):084302.
[16]LU M,LIU X,SHI Y,et al. Propagation of shear waves generated by acoustic radiation force in nondissipative inhomogeneous media[J]. Chin Phys Lett,2012,29(1):014301.
[17]MA Q,HE B. Magnetoacoustic tomography with magnetic induction:a rigorous theory[J]. IEEE Trans Biomed Eng,2008,55(2):813-816.
[18]SUN X,ZHANG F,MA Q,et al. Acoustic dipole radiation based conductivity image reconstruction for magnetoacoustic tomography with magnetic induction[J]. Appl Phys Lett,2012,100(2):024105.
[19]MARIAPPAN L,HE B. Magnetoacoustic tomography with magnetic induction:bioimepedance reconstruction through vector source imaging[J]. IEEE Trans Med Imag,2013,32(3):619-627.
[20]GUO L,LIU G,XIA H. Magneto-acousto-electrical tomography with magnetic induction for conductivity reconstruction[J]. IEEE Trans Biomed Eng,2015,62(9):2 114-2 124.
[21]YU K,SHAO Q,ASHKENAZI S,et al. In vivo electrical conductivity contrast imaging in a mouse model of cancer using high-frequency magnetoacoustic tomography with magnetic induction(hfMAT-MI)[J]. IEEE Trans Med Imag,2016,35(10):2 301-2 311.
[22]ZHANG W,MA R,ZHANG S,et al. Image reconstruction in magnetoacoustic tomography with magnetic induction(MAT-MI)with variable sound speeds[J]. IEEE Trans Biomed Eng,2016,63(12):2 585-2 594.
[23]MARIAPPAN L,SHAO Q,JIANG C,et al. Magnetoacoustic tomography with short pulsed magnetic field for in-vivo imaging of magnetic iron oxide nanoparticles[J]. Nanomed Nanotech Biol Med,2015,12(3):689-699.
[24]ZHOU Y,WANG J,SUN X,et al. Transducer selection and application in magnetoacoustic tomography with magnetic induction[J]. J Appl Phys,2016,119(9):094903.
[25]程建春. 声学原理[M]. 北京:科学出版社,2012:96-246.
[26]SUN X,FANG D,ZHANG D,et al. Acoustic dipole radiation based electrical impedance contrast imaging approach of magnetoacoustic tomography with magnetic induction[J]. Med Phys,2013,40(5):052902.
[27]XU M,WANG L. Time-domain reconstruction algorithms and numerical simulations for thermoacoustic tomography in various geometries[J]. IEEE Trans Biomed Eng,2003,50(9):1 086-1 099.
[28]MORSE P,FESHBACH H. Methods of theoretical physics[M]. New York:McGraw-Hill,1953:762-814.
[29]ARFKEN G,WEBER H. Mathematical methods for physicists[M]. San Diego:Academic Press,1995:268-356.
[30]WANG J,ZHOU Y,SUN X,et al. Acoustic source analysis of magnetoacoustic tomography with magnetic induction for conductivity gradual-varying tissues[J]. IEEE Trans Biomed Eng,2016,63(4)758-764.
[31]沈宜昕,郭各朴,孙晓冬,等. 换能器指向性对磁感应磁声成像伪影的影响[J]. 南京师范大学学报(工程技术版),2016,16(4):1-7.
[32]LOUPAS T,PYE S D,MCDICKENM W N. Deconvolution in medical ultrasonics:practical considerations[J]. Phys Med Biol,1989,34(11):1 691-1 700.
[33]TAO Y,WANG M,XIA W. Semiconductor laser self-mixing micro-vibration measuring technology based on Hilbert transform[J]. Opt Comm,2016,368:12-19.

备注/Memo

备注/Memo:
收稿日期:2017-09-06.
基金项目:国家自然科学基金(11604156)、江苏省高校自然科学研究项目(16KJB430020)、江苏省自然科学基金(BK20161013)、中国博士后科学基金(2016M591874).
通讯联系人:郭各朴,博士,讲师,研究方向:电子信息和声学. E-mail:guogepu@njnu.edu.cn
更新日期/Last Update: 2017-09-30