Please wait a minute...
浙江大学学报(工学版)
J4  2011, Vol. 45 Issue (1): 168-172    DOI: 10.3785/j.issn.1008-973X.2011.01.029
    
Induced current magnetic resonance electrical impedance tomography
for anisotropic brain tissues
LIU Yang1, WU Zhan-xiong1, ZHU Shan-an1, HE Bin2
1.College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China;
2. Department of Biomedical Engineering, University of Minnesota, Minneapolis 55455, USA
Download:   PDF(0KB) HTML
Export: BibTeX | EndNote (RIS)      

Abstract  

A novel induced current magnetic resonance electrical impedance tomography (ICMREIT) algorithm was developed with the diffusion tensor magnetic resonance imaging (DTMRI) technique in order to image the anisotropic conductivity distribution of brain tissues. The isotropic conductivity distribution of  scalp, skull, cerebrospinal fluid, gray matter and the equivalent isotropic conductivity distribution of  white matter were reconstructed by ICMREIT Jsubstitution algorithm. The equivalent isotropic conductivity distribution was used as the initial information in order to iteratively reconstruct anisotropic conductivity distribution of the white matter. A realistic head model consisting of five compartments was constructed based on the magnetic resonance imaging (MRI) data, and the model was used to examine the feasibility of the algorithm. With the 0% and 15% noise levels, the relative errors between the target and the reconstructed conductivity distribution were less than 15% and 24%, respectively. The simulation results show that the algorithm is robust to measurement noise and has high accuracy．

Published: 03 March 2011
CLC:  TM 15  
  TP 391.9  
Service
E-mail this article
Add to my bookshelf
Add to citation manager
E-mail Alert
RSS
Articles by authors
Cite this article:

LIU Yang, WU Zhan-xiong, ZHU Shan-an, HE Bin. Induced current magnetic resonance electrical impedance tomography
for anisotropic brain tissues. J4, 2011, 45(1): 168-172.

URL:

http://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2011.01.029     OR     http://www.zjujournals.com/eng/Y2011/V45/I1/168


各向异性头部组织感应电流磁共振电阻抗成像

为了对人体头部组织各向异性电导率分布进行成像,借助扩散张量核磁共振成像(DT-MRI)技术,提出一种新的感应电流磁共振电阻抗成像(IC-MREIT)算法.采用IC-MREIT J-substitution算法,重构头皮、颅骨、脑脊液、灰质组织的各向同性电导率及白质组织的等效各向同性电导率分布,以该等效各向同性电导率分布作为初始信息,迭代重构脑白质各向异性电导率分布.基于磁共振成像(MRI)数据,构建包含5种组织的真实头模型,在该模型上对重构算法的可行性进行验证.在无噪声及15％的噪声水平下,重构电导率的相对误差分别小于15％和24％.仿真结果表明,该算法具有较高的抗噪声能力和成像精度.

［1］ OZPARLAK L, DER Y Z. Induced current magnetic resonanceelectrical impedance tomography ［J］ . Physiological Measurement, 2005, 26(2): 289-305．
［2］ XU Y, HE B. Magnetoacoustic tomography with magnetic induction ［J］. Physics in Medicine and Biology, 2005, 50(21): 5175-5187．
［3］ HE B. Modeling and imaging of bioelectrical activity: principles and applications ［M］. USA: Kluwer Academic Publishers, 2004: 128．
［4］ HE B. Neural engineering ［M］. USA: Kluwer Academic Publishers, 2005: 206．
［5］ GAO N, ZHU S A, HE B. Estimation of electrical conductivity distribution within the human head from magnetic flux density measurement ［J］. Physics in Medicine and Biology, 2005, 50(11): 2675-2687．
［6］ GAO N, ZHU S A, HE B. A new magnetic resonance electrical impedance tomography (MREIT) algorithm: the RSMMREIT algorithm with applications to estimation of human head conductivity ［J］. Physics in Medicine and Biology, 2006, 51(12): 3067-3083．
［7］ 闫丹丹,张孝通,朱善安,等.头部异物两步和磁共振电阻抗成像算法的仿真研究 ［J］.浙江大学学报：工学版,2008,42(4)：661-666.
YAN Dandan, ZhANG Xiaotong, ZHU Shanan, et al. Simulation study on twostep magnetic resonance electrical impedance tomography of brain anomaly tissues ［J］. Journal of Zhejiang University: Engineering Science, 2008, 42(4): 661-666．
［8］ AKHTARI M, BRYANT H C, MAMELAK A N, et al. Conductivities of threelayer live human skull ［J］.Brain Topography, 2000, 14(3): 151-167．
［9］ ZHANG Y C, ZHU S A, HE B. A secondorder finite element algorithm for solving the threedimensional EEG forward problem ［J］. Physics in Medicine and Biology, 2004, 49(13): 2975-2987．
［10］ NICHOLSON P W. Specific impedance of cerebral white matter ［J］. Experimental Neurology, 1965, 13(4): 386-401．
［11］ BASSER P J, MATTIELLO J, LEBIHAN D. MR diffusion tensor spectroscopy and imaging ［J］. Biophysical Journal, 1994, 66(1): 259-267．
［12］ TUCH D S, WEDEEN V J, DALE A M, et al. Conductivity tensor mapping of the human brain using diffusion MRI ［J］. Proceedings of the National Academy of Sciences of the United States of America, 2001, 98(20): 11697-11701．
［13］ WOLTERS C H, ANWANDER A, TRIOCHE X, et al. Influence of tissue conductivity anisotropy on EEG/MEG field and return current computation in a realistic head model: a simulation and visualization study using highresolution finite element modeling ［J］. NeuroImage, 2006, 30(3): 813-826．
［14］ ZHANG Y C, DING L, DRONGELEN W V, et al. A cortical potential imaging study from simultaneous extra and intracranial electrical recordings by means of the finite element method ［J］. NeuroImage, 2006, 31(4): 1513-1524．
［15］ ZHANG Y C, VAN DRONGELEN W, HE B. Estimation of in vivo human braintoskull conductivity ratio with the aid of intracranial electrical simulation ［J］. Applied Physics Letters, 2006, 89(22): 2239031-2239033.
［16］ GENCER N G, KUZUOGLU M, DER Y Z. Electrical impedance tomography using induced currents ［J］ . IEEE Transactions on Medical Imaging, 1994, 13(2): 338-350．
［17］ GENCER N G, DER Y Z, WILLIAMSON S J. Electrical impedance tomography: inducedcurrent imaging achieved with a multiple coil system ［J］ . IEEE Transactions on Biomedical Engineering, 1996, 43(2): 139-149．
［18］ LIU Y, ZHU S A, HE B. Induced current magnetic resonance electrical impedance tomography of brain tissues based on Jsubstitution algorithm: a simulation study ［J］. Physics in Medicine and Biology, 2009, 54(14): 4561-4573．
［19］ KWON O, WOO E J, YOON J R, et al. Magnetic resonance electrical impedance tomography (MREIT): simulation study of Jsubstitution algorithm ［J］. IEEE Transactions on Biomedical Engineering, 2002, 49(2): 160-167．
[1] LIU Yang, DAI Song-shi. Comparison between injected current and induced current magnetic
resonance electrical impedance tomography[J]. J4, 2011, 45(10): 1848-1854.
[2] WANG Qi-Han, TAO Ying-Yang. Controlling voltage computation in electromagnetic induction heating[J]. J4, 2010, 44(8): 1553-1557.
[3] MENG Bao, HUANG Peng-jie, XIE Bo, et al. Analytical modeling for pulsed eddy current testing[J]. J4, 2009, 43(09): 1621-1624.