生物电阻抗成像技术研究
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摘要
生物电阻抗成像技术(Biological electrical impedance tomography,BEIT)是一种新型无损功能成像技术。其基本原理是根据人体内不同组织器官在不同生理或病理状态下具有不同的阻抗特性。通过配置体表电极阵列施加一定频率的低幅交变安全电流,并通过扫描电极测量电压数据,重构被测组织或器官的断层分布图像,从而提取与人体生理、病理状态相关组织或器官的电特性信息。BEIT具有安全无辐射、非侵入、低成本、便携、可视化等优点,可实现长期、动态、连续图像监测。本课题基于人体呼吸过程的BEIT图像监护技术进行系统研究:
1、对图像重建算法展开研究。基于广义Tikhonov正则化算法,针对图像重建算法的分辨率、鲁棒性、实时性等指标,分别提出最大熵正则化算法有效提高了EIT成像精度,消除图像伪影;引入先验信息构建正则化矩阵,改进人体肺部呼吸EIT成像效果;组合算法克服了单一迭代中收敛慢及半收敛现象,增强了算法的鲁棒性;基于预处理技术的组合算法则在保证成像分辨率和稳定性的前提下,进一步提高算法的实时性。
2、研究三维EIT电极结构与激励模式,获取三维场空间分布信息。为获取更好的三维图像重构结果,必需构建多层传感器阵列系统,以增加独立测量数据量。文中介绍两种三维电极分布模型,并对四种不同激励模式进行研究。此外,针对三维EIT成像提出了一种新的图像重建算法,在保证算法稳定性前提下,有效提高了重建分辨率和实时性。
3、基于MEIT-TJU数字EIT系统对人体肺部呼吸过程进行实时监测,并分别对测量数据以及重建图像序列进行分析研究,挖掘有效信息。
4、对三维人体模型进行仿真研究。根据人体胸部CT扫描图,分别构建2.5D和3D不同程度肺萎陷模型,分析比较电导率特性与复电导率特性对于不同模型EIT图像重构的影响。基于EIT引入几种肺通气量指标分析评价各种状态下肺部通气量变化,对比不同电特性对通气指标参数计算的影响。
Biological electrical impedance tomography ( BEIT ) is a new non-invasive functional imaging technology. The principle of BEIT is that different tissues and organs have different electrical impedance properties in different physiological or pathological conditions. A set of electrodes are positioned around the periphery of the body with low amplitude safe currents being applied into the body through a pair of electrodes, and the resulting voltages on the other electrodes are subsequently collected. Based on the measured data, the internal conductivity distribution and its change can be estimated. Therefore, the electrical properties related to different physiological or pathological conditions can be explored. BEIT has the advantages of non-radiation, safe, non-invasive, low cost, portability, and visualization, etc. It can be used for continuous dynamic monitoring at bedside. The research work is focused on EIT technique applied for lung ventilation monitoring.
1. Image reconstruction methods are studied. In order to improve the accuracy of reconstructed image, stability of the reconstruction, and the imaging speed, respectively, different methods are introduced based on the generalized Tikhononv regularization. The maximum entropy regularization method can effectively reduce the artefacts of reconstructed images and improve the accuracy. By incorporating prior information into Tikhonov regularization matrix, the differentiability and quality of the lung are improved. The hybrid method can overcome the phenomenon of slow convergence or semi-convergence in single-iteration algorithms and enhance the stability. Pre-conditioned hybrid method can further improve the algorithm in real time without losing accuracy and stability.
2. To obtain the information of three-dimensional (3D) spatial distribution, 3D electrode structure and drive pattern are investigated. Two different structures of electrode array are proposed and four drive patterns are compared. Moreover, a new image reconstruction algorithm is put forward for 3D image reconstruction, in order to ensure the real-time property, accuracy and stability.
3. The experiments for monitoring lung ventilation are carried out based on the digital system of MEIT_TJU. Measuremed data and corresponding image sequences of reconstruction are analysed to explore effective information.
4. 3D human thorax models are established for simulation. Based on CT images of human thorax, true 3D thorax models with conductivity distribution or complex conductivity distribution under different ARDS conditions are built up in comparison with the 2.5D ones, and EIT-derived numeric indices are also employed for evaluation of the lung ventilation. The purpose of the research is to study different effects of different thorax models with either conductivity or complex conductivity on the reconstructed images and ventilation indices.
1、对图像重建算法展开研究。基于广义Tikhonov正则化算法,针对图像重建算法的分辨率、鲁棒性、实时性等指标,分别提出最大熵正则化算法有效提高了EIT成像精度,消除图像伪影;引入先验信息构建正则化矩阵,改进人体肺部呼吸EIT成像效果;组合算法克服了单一迭代中收敛慢及半收敛现象,增强了算法的鲁棒性;基于预处理技术的组合算法则在保证成像分辨率和稳定性的前提下,进一步提高算法的实时性。
2、研究三维EIT电极结构与激励模式,获取三维场空间分布信息。为获取更好的三维图像重构结果,必需构建多层传感器阵列系统,以增加独立测量数据量。文中介绍两种三维电极分布模型,并对四种不同激励模式进行研究。此外,针对三维EIT成像提出了一种新的图像重建算法,在保证算法稳定性前提下,有效提高了重建分辨率和实时性。
3、基于MEIT-TJU数字EIT系统对人体肺部呼吸过程进行实时监测,并分别对测量数据以及重建图像序列进行分析研究,挖掘有效信息。
4、对三维人体模型进行仿真研究。根据人体胸部CT扫描图,分别构建2.5D和3D不同程度肺萎陷模型,分析比较电导率特性与复电导率特性对于不同模型EIT图像重构的影响。基于EIT引入几种肺通气量指标分析评价各种状态下肺部通气量变化,对比不同电特性对通气指标参数计算的影响。
Biological electrical impedance tomography ( BEIT ) is a new non-invasive functional imaging technology. The principle of BEIT is that different tissues and organs have different electrical impedance properties in different physiological or pathological conditions. A set of electrodes are positioned around the periphery of the body with low amplitude safe currents being applied into the body through a pair of electrodes, and the resulting voltages on the other electrodes are subsequently collected. Based on the measured data, the internal conductivity distribution and its change can be estimated. Therefore, the electrical properties related to different physiological or pathological conditions can be explored. BEIT has the advantages of non-radiation, safe, non-invasive, low cost, portability, and visualization, etc. It can be used for continuous dynamic monitoring at bedside. The research work is focused on EIT technique applied for lung ventilation monitoring.
1. Image reconstruction methods are studied. In order to improve the accuracy of reconstructed image, stability of the reconstruction, and the imaging speed, respectively, different methods are introduced based on the generalized Tikhononv regularization. The maximum entropy regularization method can effectively reduce the artefacts of reconstructed images and improve the accuracy. By incorporating prior information into Tikhonov regularization matrix, the differentiability and quality of the lung are improved. The hybrid method can overcome the phenomenon of slow convergence or semi-convergence in single-iteration algorithms and enhance the stability. Pre-conditioned hybrid method can further improve the algorithm in real time without losing accuracy and stability.
2. To obtain the information of three-dimensional (3D) spatial distribution, 3D electrode structure and drive pattern are investigated. Two different structures of electrode array are proposed and four drive patterns are compared. Moreover, a new image reconstruction algorithm is put forward for 3D image reconstruction, in order to ensure the real-time property, accuracy and stability.
3. The experiments for monitoring lung ventilation are carried out based on the digital system of MEIT_TJU. Measuremed data and corresponding image sequences of reconstruction are analysed to explore effective information.
4. 3D human thorax models are established for simulation. Based on CT images of human thorax, true 3D thorax models with conductivity distribution or complex conductivity distribution under different ARDS conditions are built up in comparison with the 2.5D ones, and EIT-derived numeric indices are also employed for evaluation of the lung ventilation. The purpose of the research is to study different effects of different thorax models with either conductivity or complex conductivity on the reconstructed images and ventilation indices.
引文
[1]王化祥,杨五强,电容过程成像技术的进展,仪器仪表学报, 2000, 21(1): 4-7.
[2] H. Dehghani, B. W. Pogue, J. Shudong, et al., Three-Dimensional Optical Tomography: Resolution in Small-Object Imaging, Appl. Opt., 2003, 42(16): 3117-3128.
[3] L. Ding, Y. Lai, B. He, et al., Low resolution brain electromagnetic tomography in a realistic geometry head model: a simulation study, Physics in Medicine and Biology, 2005, 50(1): 45-56.
[4] Brian H. Brown, Medical impedance tomography and process impedance tomography: a brief review, Measurement Science and Technology, 2001, 12(8): 991-996.
[5] G. Steiner,M. Soleimani,D. Watzenig, A bio-electromechanical imaging technique with combined electrical impedance and ultrasound tomography, Physiological Measurement, 2008, 29(6): S63-S75.
[6] Y. Xu,B. He, Magnetoacoustic tomography with magnetic induction (MAT-MI), Physics in Medicine and Biology, 2005, 50(21): 5175-5187.
[7] D. Evren,B. M. Eyuboglu, Anisotropic conductivity imaging with MREIT using equipotential projection algorithm, Physics in Medicine and Biology, 2007, 52(24): 7229-7242.
[8] M.Cheney ,D. Isaacson ,J. Newell Electrical impedance tomography, SIAM Review, 1999, 41(1): 85-101.
[9] Y. Zou,Z. Guo, A review of electrical impedance techniques for breast cancer detection, Medical Engineering & Physics, 2003, 25(2): 79-90.
[10] A. M. Dijkstra, B. H. Brown, A. D. Leathard, et al., Review Clinical applications of electrical impedance tomography, Journal of Medical Engineering & Technology, 1993, 17(3): 89-98.
[11] R. P. Henderson,J. G. Webster, An Impedance Camera for Spatially Specific Measurements of the Thorax, Biomedical Engineering, IEEE Transactions on, 1978, BME-25(3): 250-254.
[12] D. S. Holder, Electrical impedance tomography methods, history and applications, Bristol and Philadelphia: IoP Publishing, 2004.
[13] R. W. M. Smith,I. L. Freeston,B. H. Brown, A real-time electrical impedance tomography system for clinical use-design and preliminary results, Biomedical Engineering, IEEE Transactions on, 1995, 42(2): 133-140.
[14] B. H. Brown,A. D. Seagar, The Sheffield data collection system, Clinical Physics and Physiological Measurement, 1987, 8(4A): 91-97.
[15] A. J. Wilson, P. Milnes, A. R. Waterworth, et al., Mk3.5: a modular, multi-frequency successor to the Mk3a EIS/EIT system, Physiological Measurement, 2001, 22(1): 49-54.
[16] V. Cherepenin, A. Karpov, A. Korjenevsky, et al., Preliminary static EIT images of the thorax in health and disease, Physiological Measurement, 2002, 23(1): 33-41.
[17] V. Cherepenin,et al., A 3D electrical impedance tomography (EIT) system for breast cancer detection, Physiological Measurement, 2001, 22(1): 9-18.
[18] V. A. Cherepenin, A. Y. Karpov, A. V. Korjenevsky, et al., Three-dimensional EIT imaging of breast tissues: system design and clinical testing, Medical Imaging, IEEE Transactions on, 2002, 21(6): 662-667.
[19] "TCI Medical: Diagnostic Imaging" (2003), retrieved http: //www.tcimed.com/diagnosticimaging.html.
[20] Q. Zhu, W. R. B. Lionheart, F. J. Lidgey, et al., An adaptive current tomograph using voltage sources, Biomedical Engineering, IEEE Transactions on, 1993, 40(2): 163-168.
[21] Q. S. Zhu, C. N. McLeod, C. W. Denyer, et al., Development of a real-time adaptive current tomograph, Physiological Measurement, 1994, 15: A37-A43.
[22] A. Hartov, R. A. Mazzarese, F. R. Reiss, et al., A multichannel continuously selectable multifrequency electrical impedance spectroscopy measurement system, Biomedical Engineering, IEEE Transactions on, 2000, 47(1): 49-58.
[23] R. J. Halter,A. Hartov,K. D. Paulsen, A Broadband High-Frequency Electrical Impedance Tomography System for Breast Imaging, Biomedical Engineering, IEEE Transactions on, 2008, 55(2): 650-659.
[24] R. D. Cook, G. J. Saulnier, D. G. Gisser, et al., ACT3: a high-speed, high-precision electrical impedance tomograph, Biomedical Engineering, IEEE Transactions on, 1994, 41(8): 713-722.
[25] P. M. Edic, G. J. Saulnier, J. C. Newell, et al., A real-time electrical impedance tomograph, Biomedical Engineering, IEEE Transactions on, 1995, 42(9): 849-859.
[26] K. Tzu-Jen, G. J. Saulnier, D. Isaacson, et al., A Versatile High-Permittivity Phantom for EIT, Biomedical Engineering, IEEE Transactions on, 2008, 55(11): 2601-2607.
[27] R. J. Yerworth, R. H. Bayford, G. Cusick, et al., Design and performance of the UCLH Mark 1b 64 channel electrical impedance tomography (EIT) system, optimized for imaging brain function, Physiological Measurement, 2002, 23(1): 149-158.
[28] R. E. Serrano,et al., Assessment of the unilateral pulmonary function by means of electrical impedance tomography using a reduced electrode set, Physiological Measurement, 2004, 25(4): 803-813.
[29] S. Jin Keun, L. Jeehyun, K. Sung Wan, et al., Frequency-difference electrical impedance tomography (fdEIT): algorithm development and feasibility study, Physiological Measurement, 2008, 29(8): 929-944.
[30] AM Dijkstra, BH Brown, AD Leathard, et al., Clinical applications of electrical impedance tomography, J Med Eng Technol., 1993, 17(3): 89-98.
[31] M. Cheney,D. Isaacson, Issues in electrical impedance imaging, Computational Science & Engineering, IEEE, 1995, 2(4): 53-62.
[32] Z. Jie,P. P. Robert, EIT images of ventilation: what contributes to the resistivity changes?, Physiological Measurement, 2005, 26(2): S81-S92.
[33] H. J. Smit, A. V. Noordegraaf, R. J. Roeleveld, et al., Epoprostenol-induced pulmonary vasodilatation in patients with pulmonary hypertension measured by electrical impedance tomography, Physiological Measurement, 2002, 23(1): 237-243.
[34] M. W. Robert, G. A. Robert, M. Sha, et al., Markov chain Monte Carlo techniques and spatial-temporal modelling for medical EIT, Physiological Measurement, 2004, 25(1): 181-194.
[35] R. P. Patterson, J. Zhang, L. I. Mason, et al., Variability in the cardiac EIT image as a function of electrode position, lung volume and body position, Physiological Measurement, 2001, 22(1): 159-166.
[36] S. Zlochiver, D. Freimark, M. Arad, et al., Parametric EIT for monitoring cardiac stroke volume, Physiological Measurement, 2006, 27(5): S139-146.
[37] A. R. Hampshire, R. H. Smallwood, B. H. Brown, et al., Multifrequency and parametric EIT images of neonatal lungs, Physiological Measurement, 1995, 16(3A): A175-A189.
[38] T. Dudykevych, H. Richter, G. Hahn, et al., "Software and Operational Concept for EIT-Based regional lung Function monitoring," (Department of Anaesthesiological Research Center of Anaesthesiology, Emergency and Intensive Care Medicine TL 195, G?ttingen, Germany, 2005).
[39] G. Hahn, J. Dittmar, A. Just, et al., Different approaches for quantifying ventilation distribution and lung tissue properties by functional EIT, Physiol Meas, 2010, 31(8): S73-84.
[40] C. M. Michel, G. Thut, S. Morand, et al., Electric source imaging of human brain functions, Brain Research Reviews, 2001, 36(2-3): 108-118.
[41] J. W. Wheless, E. Castillo, V. Maggio, et al., Magnetoencephalography (MEG) and magnetic source imaging (MSI), Neurologist, 2004, 10(3): 138-153.
[42] L. Fabrizi, A. McEwan, E. Woo, et al., Analysis of resting noise characteristics of three EIT systems in order to compare suitability for time difference imaging with scalp electrodes during epileptic seizures, Physiological Measurement, 2007, 28(7): S217-S236.
[43] D. Holder, Feasibility of developing a method of imaging neuronal activity in the human brain: a theoretical review, Medical and Biological Engineering and Computing, 1987, 25(1): 2-11.
[44] D. S. Holder, Detection of cerebral ischaemia in the anaesthetised rat by impedance measurement with scalp electrodes: implications for non-invasive imaging of stroke by electrical impedance tomography, Clinical Physics and Physiological Measurement, 1992, 13(1): 63-75.
[45] D. S. Holder, Electrical impedance tomography with cortical or scalp electrodes during global cerebral ischaemia in the anaesthetised rat, Clinical Physics and Physiological Measurement, 1992, 13(1): 87-98.
[46] K. Boone, A. M. Lewis and D. S. Holder, Imaging of cortical spreading depression by EIT: implications for localization of epileptic foci, Physiological Measurement, 1994, 15(2A): A189-A198.
[47] D. S. Holder,A. Rao,Y. Hanquan, Imaging of physiologically evoked responses by electrical impedance tomography with cortical electrodes in the anaesthetized rabbit, Physiological Measurement, 1996, 17(4A): A179-A186.
[48] A. Rao,Gibson A,H. D. S, EIT images of electrically induced epileptic activity in anaesthetised rabbits, Med. Biol. Eng. Comp, 1997, 35(10): 327-339.
[49] A. Romsauerova, A. McEwan, L. Horesh, et al., Multi-frequency electrical impedance tomography (EIT) of the adult human head: initial findings in brain tumours, arteriovenous malformations and chronic stroke, development of an analysis method and calibration, Physiological Measurement, 2006, 27(5): S147-S161.
[50] J. Abascal, S. R. Arridge, D. Atkinson, et al., Use of anisotropic modelling in electrical impedance tomography; Description of method and preliminary assessment of utility in imaging brain function in the adult human head, NeuroImage, 2008, 43(2): 258-268.
[51] R. J. Sadleir,T. Te, Electrode configurations for detection of intraventricular haemorrhage in the premature neonate, Physiological Measurement, 2009, 30(1): 63-79.
[52] A. Tizzard,R. H. Bayford, Improving the finite element forward model of the human head by warping using elastic deformation, Physiological Measurement, 2007, 28(7): S163-S182.
[53] A. Hartov, R. A. Mazzarese, F. R. Reiss, et al., A multichannel continuously selectable multifrequency electrical impedance spectroscopy measurement system, Biomedical Engineering, IEEE Transactions on, 2000, 47(1): 49-58.
[54] R. J. Halter, A. Schned, J. Heaney, et al., Electrical Impedance Spectroscopy of Benign and Malignant Prostatic Tissues, The Journal of Urology, 2008, 179(4): 1580-1586.
[55] J. H. Ryan, H. Alex, D. P. Keith, Experimental justification for using 3D conductivity reconstructions in electrical impedance tomography, Physiological Measurement, 2007, 28(7): S115-S127.
[56]周吕,柯美云,神经胃肠病学与动力一基础与临床,北京:科学出版社, 2005.
[57] H. Piessevaux, J. Tack, S. Walrand, et al., Intragastric distribution of a standardized meal in health and functional dyspepsia: correlation with specific symptoms, Neurogastroenterology & Motility, 2003, 15(5): 447-455.
[58]赵舒,任超世,生物电阻抗法检测胃动力功能,国际生物医学工程杂志, 2006, 29(92-95.
[59] C. T. Soulsby, M. Khela, E. Yazaki, et al., Measurements of gastric emptying during continuous nasogastric infusion of liquid feed: Electric impedance tomography versus gamma scintigraphy, Clinical Nutrition, 2006, 25(4): 671-680.
[60] F. Podczeck, C. L. Mitchell, J. M. Newton, et al., The gastric emptying of food as measured by gamma-scintigraphy and electrical impedance tomography (EIT) and its influence on the gastric emptying of tablets of different dimensions, Journal of Pharmacy and Pharmacology, 2007, 59(11): 1527-1536.
[61] J. W. Wright, The effect of intraluminal content on gastrointestinal motility in man, Nottingham; University of Nottingham, 1995.
[62] K. D. Paulsen, M. J. Moskowitz, T. P. Ryan, et al., Initial in vivo experience with EIT as a thermal estimator during hyperthermia, Int J Hyperthermia, 1996, 12(5): 573-591.
[63] F. Ferraioli, A. Formisano, R. Martone, Effective Exploitation of Prior Information in Electrical Impedance Tomography for Thermal Monitoring of Hyperthermia Treatments, Magnetics, IEEE Transactions on, 2009, 45(3): 1554-1557.
[64] D. C. Thomas, F. J. Mcardle, V. E. Rogers, et al., Local Blood Volume Changes in Women With Pelvic Congestion Measured by Applied Potential Tomography, Obstetrical & Gynecological Survey, 1992, 47(4): 265-266.
[65] A. Vonk Noordegraaf, P. W. A. Kunst, A. Janse, et al., Validity and reproducibility of electrical impedance tomography for measurement of calfblood flow in healthy subjects Medical and Biological Engineering and Computing, 1997, 35(2): 107-112.
[66] R. J. Sadleir, R. A. Fox, Detection and quantification of intraperitoneal fluid using electrical impedance tomography, Biomedical Engineering, IEEE Transactions on, 2001, 48(4): 484-491.
[67] B. H. Brown,et al., Applied potential tomography: possible clinical applications, Clinical Physics and Physiological Measurement, 1985, 6(2): 109-121.
[68] B. M. Eyübo?lu, B. H. Brown, D. C. Barber, et al., Localisation of cardiac related impedance changes in the thorax, Clin Phys Physiol Meas, 1987, 8 (Suppl A): 67-73.
[69] F. J. McArdle, A. J. Suggett, B. H. Brown, et al., An assessment of dynamic images by applied potential tomography for monitoring pulmonary perfusion, Clinical Physics and Physiological Measurement, 1988, 9(4A): 87-91.
[70] B. M. Eyuboglu, B. H. Brown, D. C. Barber, In vivo imaging of cardiac related impedance changes, Engineering in Medicine and Biology Magazine, IEEE, 1989, 8(1): 39-45.
[71] D. Isaacson, J. C. Newell, J. C. Goble, et al., Thoracic Impedance Images During Ventilation, Annual Intematisnal Conference of the IEEE Engineering in Medicine and Biology Society, 1990: 106-107.
[72] L. F. Fuks, M. Cheney, D. Isaacson, et al., Detection and imaging of electric conductivity and permittivity at low frequency, Biomedical Engineering, IEEE Transactions on, 1991, 38(11): 1106-1110.
[73] H. Griffiths, H. T. L. Leung, R. J. Williams, Imaging the complex impedance of the thorax, Clinical Physics and Physiological Measurement, 1992, 13(A): 77-81.
[74] J. H. Campbell, N. D. Harris, F. Zhang, et al., Clinical applications of electrical impedance tomography in the monitoring of changes in intrathoracic fluid volumes, Physiological Measurement, 1994, 15(2A): A217-A222.
[75] G. Hahn, I. Sipinkova, F. Baisch, et al., Changes in the thoracic impedance distribution under different ventilatory conditions, Physiological Measurement, 1995, 16(3A): A161-A173.
[76] J. C. Newell, D. Isaacson, R. S. Blue, Regional ventilation and perfusion assessed by electrical impedance imaging, 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Amsterdam, 1996: 780-781.
[77] A. Adler, R. Amyot, R. Guardo, et al., Monitoring changes in lung air and liquid volumes with electrical impedance tomography, J Appl Physiol, 1997, 83(5): 1762-1767.
[78] N. Anton Vonk, W. A. K. Peter, J. Andre, et al., Pulmonary perfusion measured by means of electrical impedance tomography, Physiological Measurement, 1998, 19(2): 263-273.
[79] I. Frerichs,G. Hahn,G. Hellige, Thoracic electrical impedance tomographic measurements during volume controlled ventilation-effects of tidal volume and positive end-expiratory pressure, Medical Imaging, IEEE Transactions on, 1999, 18(9): 764-773.
[80] I. Frerichs, G. Hahn, H. Schiffmann, et al., Monitoring regional lung ventilation by functional electrical impedance tomography during assisted ventilation, Ann. NY Acad. Sci., 1999, 873: 493-505.
[81] V.-N. Anton, J. Andre, T. M. Johan, et al., Determination of stroke volume by means of electrical impedance tomography, Physiological Measurement, 2000, 21(2): 285-293.
[82] N. Kerrouche,C. N. McLeod,W. R. B. Lionheart, Time series of EIT chest images using singular value decomposition and Fourier transform, Physiological Measurement, 2001, 22(1): 147-157.
[83] I. Frerichs, J. Hinz, P. Herrmann, et al., Regional lung perfusion as determined by electrical impedance tomography in comparison with electron beam CT imaging, Medical Imaging, IEEE Transactions on, 2002, 21(6): 646-652.
[84] I. Frerichs, J. Hinz, P. Herrmann, et al., Detection of local lung air content by electrical impedance tomography compared with electron beam CT, J Appl Physiol, 2002, 93(2): 660-666.
[85] Henk J. Smit, Anton Vonk-Noordegraaf, J. Tim Marcus, et al., Pulmonary Vascular Responses to Hypoxia and Hyperoxia in Healthy Volunteers and COPD Patients Measured by Electrical Impedance Tomography, Chest, 2003, 123(6): 1803-1809.
[86] J. Hinz, G. Hahn, P. Neumann, et al., End-expiratory lung impedance change enables bedside monitoring of end-expiratory lung volume change, Intensive Care Medicine, 2003, 29(11): 37-43.
[87] Josue′A. Victorino, Joa?o B. Borges, Valdelis N. Okamoto, et al., Imbalances in Regional Lung Ventilation: A Validation Study on Electrical Impedance Tomography, Am J Respir Crit Care Med, 2004, 169(1): 791-800.
[88] I. Frerichs, M. Bodenstein, T. Dudykevych, et al., Effect of lower body negative pressure and gravity on regional lung ventilation determined by EIT, Physiological Measurement, 2005, 26(2): S27-S37.
[89] G. Hahn, A. Just, T. Dudykevych, et al., Imaging pathologic pulmonary air and fluid accumulation by functional and absolute EIT, Physiological Measurement, 2006, 27(5): S187-S198.
[90] L. Beckmann, D. Van Riesen, S. Leonhardt, Optimal electrode placement and frequency range selection for the detection of lung water using Bioimpedance Spectroscopy, 29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07, Lyon, France, 2007: 2685-2688.
[91] M. Risdal, S. O. Aase, M. Stavland, et al., Impedance-Based Ventilation Detection During Cardiopulmonary Resuscitation, Biomedical Engineering, IEEE Transactions on, 2007, 54(12): 2237-2245.
[92] R. Bayford, P. Kantartzis, A. Tizzard, et al., Development of a neonate lung reconstruction algorithm using a wavelet AMG and estimated boundary form, Physiological Measurement, 2008, 29(6): S125-S138.
[93] J. Bruno de Lema, E. Serrano, T. Feixas, et al., Assessment of Differential Lung Function by Electrical Impedance Tomography, Archivos de Bronconeumolog韆 (English Edition), 2008, 44(8): 408-412.
[94] J. M. Deibele, H. Luepschen, S. Leonhardt, Dynamic separation of pulmonary and cardiac changes in electrical impedance tomography, Physiological Measurement, 2008, 29(6): S1-S14.
[95] M. Denai, M. Mahfouf, S. Mohamad-Samuri, et al., Absolute Electrical Impedance Tomography (aEIT) Guided Ventilation Therapy in Critical Care Patients: Simulations and Future Trends, Information Technology in Biomedicine, IEEE Transactions on , 2010, 14(3): 641-649.
[96] K. Jihyeon, W. Eung Je, S. Jin Keun, Multi-frequency time-difference complex conductivity imaging of canine and human lungs using the KHU Mark1 EIT system, Physiological Measurement, 2009, 30(6): S149-S164.
[97] B. Grychtol, G. K. Wolf, J. H. Arnold, Differences in regional pulmonary pressure--impedance curves before and after lung injury assessed with a novel algorithm, Physiological Measurement, 2009, 30(6): S137-S148.
[98] J. Zhang, R. Patterson, Non-invasive determination of absolute lung resistivity in adults using electrical impedance tomography, Physiological Measurement, 2010, 31(8): S45-S56.
[99] B. Grychtol, et al., Towards lung EIT image segmentation: automatic classification of lung tissue state from analysis of EIT monitored recruitment manoeuvres, Physiological Measurement, 2010, 31(8): S31-S43.
[100]董秀珍,秦明新,付峰,生物电阻抗断层成像技术的研究进展,第四军医大学学报, 1999, 20(3): 252-255.
[101]尤富生,董秀珍,史学涛,等,电阻抗断层成像中临近和对向驱动模式的研究,第四军医大学学报, 2004, 25(1): 88-91.
[102]史学涛,董秀珍,帅万钧,等,适用于脑部电阻抗断层成像的单源驱动电流模式,第四军医大学学报, 2006, 27(3): 279-282.
[103]廖琪梅,徐玉乔,董秀珍,等,乳腺癌及周围组织电阻抗频谱特性与其病理学特征的研究,生物医学工程与临床, 2008, 12(4): 263-266.
[104]A. Ni, X. Dong, G. Yang, et al., Image reconstruction incorporated with the skull inhomogeneity for electrical impedance tomography, Computerized Medical Imaging and Graphics, 2008, 32(5): 409-415.
[105]Z. Cui, H. Wang, L. Tang, et al., A Specific Data Acquisition Scheme for Electrical Tomography, Instrumentation and Measurement Technology Conference Proceedings, IMTC. IEEE, 2008: 726-729.
[106]崔自强,双模态电学层析成像技术研究: [博士学位论文],天津;天津大学, 2009.
[107]张帅,人体胸腔电阻抗成像系统研究: [博士学位论文],天津;河北工业大学, 2009.
[108]毕德显,电磁场理论,北京:电子工业出版社, 1985.
[109]M. Vauhkonen, Electrical impedance tomography and prior information, [Phd thesis], Finland; University of Kuopio, 1997.
[110]Andrea Borsic, Regularisation Methods for Imaging from Electrical Measurements, Oxford Brookes University, 2002.
[111]倪光正,钱秀英,电磁场数值计算,北京:高等教育出版社, 1996.
[112]N. Polydorides, W. R. B. Lionheart, A Matlab toolkit for three-dimensional electrical impedance tomography: a contribution to the Electrical Impedance and Diffuse Optical Reconstruction Software project, Measurement Science and Technology, 2002, 13(4): 1871-1883.
[113]M. Vauhkonen, P. A. Karjalainen, J. P. Kaipio, A Kalman filter approach to track fast impedance changes in electrical impedance tomography, Biomedical Engineering, IEEE Transactions on, 1998, 45(4): 486-493.
[114]P. M. Edic, D. Isaacson, G. J. Saulnier, et al., An iterative Newton-Raphson method to solve the inverse admittivity problem, Biomedical Engineering, IEEE Transactions on, 1998, 45(7): 899-908.
[115]王超,医学电阻抗断层成像的研究: [博士学位论文],天津大学, 2001.
[116]D. B. Geselowitz, An Application of Electrocardiographic Lead Theory to Impedance Plethysmography, Biomedical Engineering, IEEE Transactions on, 1971, BME-18(1): 38-41.
[117]J. Lehr, A Vector Derivation Useful in Impedance Plethysmographic Field Calculations, Biomedical Engineering, IEEE Transactions on, 1972, BME-19(2): 156-157.
[118]T. Murai, Y. Kagawa, Electrical Impedance Computed Tomography Based on a Finite Element Model, Biomedical Engineering, IEEE Transactions on, 1985, BME-32(3): 177-184.
[119]M.-L. H. Rasmussen,L. K. H. Clemmensen, The Effect of Regularizing Matrices and Norms in Tikhonov Based Image Restorations, Denmark; Technical University of Denmark, 2003.
[120]P. C. Hansen, Discrete inverse problems insight and algorithms Denmark; Technical University of Denmark, 2005.
[121]W. Q. Yang, D. M. Spink, T. A. York, et al., An image-reconstruction algorithm based on Landweber's iteration method for electrical-capacitance tomography, Measurement Science and Technology, 1999, 10(11): 1065-1069.
[122]W. Q. Yang, P. Lihui, Image reconstruction algorithms for electrical capacitance tomography, Measurement Science and Technology, 2003, 14(1): R1-R13.
[123]M. Wang, Inverse solutions for electrical impedance tomography based on conjugate gradients methods, Measurement Science and Technology, 2002, 13(101-117.
[124]H. Wang, C. Wang, W. Yin, A pre-iteration method for the inverse problem in electrical impedance tomography, IEEE Instrumentation and Measurement Technology Conference, 2004: 392-395.
[125]M. Hanke, P.C. Hansen, Conjugate gradient type methods for ill-posed problems, Essex: Scientific & Technical, Longman, 1995.
[126]P. J. Vauhkonen, M. Vauhkonen, J. P. Kaipio, Fixed-lag smoothing and state estimation in dynamic electrical impedance tomography, International Journal for Numerical Methods in Engineering, 2001, 50(9): 2195-2209.
[127]O. P. Tossavainen, M. Vauhkonen, V. Kolehmainen, A three-dimensional shape estimation approach for tracking of phase interfaces in sedimentation processes using electrical impedance tomography, Measurement Science and Technology, 2007, 18(5): 1413-1424.
[128]A. Seppaen, M. Vauhkonen, P. J. Vauhkonen, et al., State estimation in process tomography--Three-dimensional impedance imaging of moving fluids, International Journal for Numerical Methods in Engineering, 2008, 73(11): 1651-1670.
[129]K. Y. Kim, B. S. Kim, M. C. Kim, et al., Image reconstruction in time-varying electrical impedance tomography based on the extended Kalman filter, Measurement Science and Technology, 2001, 12(8): 1032-1039.
[130]A. Seppanen, M. Vauhkonen, P. J. Vauhkonen, et al., State estimation with fluid dynamical evolution models in process tomography - an application to impedance tomography, Inverse Problems, 2001, 17(3): 467-483.
[131]S. M. Fernando, C. C. A. Julio, G. L. Raul, et al., Online transition matrix identification of the state evolution model for the extended Kalman filter in electrical impedance tomography, Journal of Physics: Conference Series, 2008, 012052.
[132]F. S. Moura, J. C. C. Aya, A. T. Fleury, et al., Dynamic Imaging in Electrical Impedance Tomography of the Human Chest With Online Transition Matrix Identification, Biomedical Engineering, IEEE Transactions on, 2010, 57(2): 422-431.
[133]K. Knudsen, J. Mueller, S. Siltanen, Numerical solution method for the dbar-equation in the plane, Journal of Computational Physics, 2004, 198(2): 500-517.
[134]D. Isaacson, J. L. Mueller, J. C. Newell, et al., Reconstructions of chest phantoms by the D-bar method for electrical impedance tomography, Medical Imaging, IEEE Transactions on, 2004, 23(7): 821-828.
[135]D. Isaacson, J. L. Mueller, J. C. Newell, et al., Imaging cardiac activity by the D-bar method for electrical impedance tomography, Physiological Measurement, 2006, 27(5): S43-S50.
[136]J. G. Webster, ed., Electrical Impedance Tomography, Hilger, Bristol, 1990.
[137]M. Cheney, D. Isaacson, E. J. Somersalo, et al., A Layer-stripping Reconstruction Algorithm For Impedance Imaging, Proceedings of the Annual International Conference of the IEEE, Engineering in Medicine and Biology Society, 1991: 3-4.
[138]C. R. Smith, W. T. Grandy, Maximum-Entropy and Bayesian Methods in Inverse Problems, Reidel, Boston, 1985.
[139]Jorge Nocedal, S. J. Wright, Numerical optimization Springer-Verlag New York, Inc, 1999.
[140]王化祥,汪婧,胡理,等,基于肺部先验知识的电阻抗成像重构算法,天津大学学报, 2008, 41(4): 383-388.
[141]Y. S. Kim, S. H. Lee, U. Z. Ijaz, et al., Sensitivity map generation in electrical capacitance tomography using mixed normalization models, Measurement Science and Technology, 2007, 18(6): 2092-2102.
[142]M. T. Clay, T. C. Ferree, Weighted regularization in electrical impedance tomography with applications to acute cerebral stroke, Medical Imaging, IEEE Transactions on, 2002, 21(6): 629-637.
[143]R. B. L. William, EIT reconstruction algorithms: pitfalls, challenges and recent developments, Physiological Measurement, 2004, 25(1): 125-142.
[144]H. Dehghani, D. C. Barber, I. Basarab-Horwath, Incorporating a priori anatomical information into image reconstruction in electrical impedance tomography, Physiological Measurement, 1999, 20: 87-102.
[145]G. H. Golub, C. H. Vanloan, Matrix computations Baltimore: The Johns Hopkins University Press, 1989.
[146]P. C. Hansen, T. K. Jensen, G. Rodriguez, An adaptive pruning algorithm for the discrete L-curve criterion, J. Comput. Appl. Math., 2007, 198(2): 483-492.
[147]G. H. Golub,U. v. Matt, Generalized cross-validation for large scale problems, Proceedings of the second international workshop on Recent advances in total least squares techniques and errors-in-variables modeling, Leuven, Belgium, 1997: 139-148.
[148]F. Bauer, S. Kindermann, The quasi-optimality criterion for classical inverse problems, Inverse Problems, 2008, 24: 035002 (20pp).
[149]M. Jacobsen, Modular regularization algorithms Denmark, [PhD Thesis], Technical University of Denmark, 2004.
[150]D. Calvetti, L. Reichel, A. Shuibi, Invertible smoothing preconditioners for linear discrete ill-posed problems, Appl. Numer. Math., 2005, 54(2): 135-149.
[151]W. Mi, M. Yixin, N. Holliday, et al., A high-performance EIT system, Sensors Journal, IEEE, 2005, 5(2): 289-299.
[152]W. R. Fan, H. X. Wang, X. Y. Chen, et al., Three dimensional EIT models for human lung reconstruction based on Schur CG algorithm, New York: Ieee, 2009.
[153]A. Seppanen, A. Voutilainen, J. P. Kaipio, State estimation in process tomography-reconstruction of velocity fields using EIT, Inverse Problems, 2009, 25: 085009 (24pp).
[154]L. Hu, H. Wang, B. Zhao, et al., A hybrid reconstruction algorithm for electrical impedance tomography, Measurement Science and Technology, 2007, 18(3): 813-818.
[155]I. Basarab-Horwath, J. Piotrowski, P. M. McEwan, Calculated measures of performance in electrical impedance tomography using a finite-element model, Physiological Measurement, 1995, 16: 263-271.
[156]D. Calvetti, L. Reichel, A. Shuibi, Invertible smoothing preconditioners for linear discrete ill-posed problems, Applied Numerical Mathematics, 2005, 54(2): 135-149.
[157]C. R. Vogel and M. Hanke, Two-level preconditioners for regularized inverse problems I, Theory Numer. Math., 1999, 83: 385-402.
[158]M. Jacobsen,P. C. Hansen,M. A. Saunders, Subspace preconditioned LSQR for discrete ill-posed problems, BIT, 2003, 43: 975-989.
[159]O. M. Nielsen, Wavelets in scientific computing, Technical University of Denmark, 1998.
[160]G. Strang, The discrete cosine transform, SIAM Rev, 1999.
[161]H. Luepschen, D. van Riesen, L. Beckmann, et al., Modeling of Fluid Shifts in the Human Thorax for Electrical Impedance Tomography, Magnetics, IEEE Transactions on, 2008, 44(6): 1450-1453.
[162]"Dielectric properties of body tissue" (Institute for Applied Physics, Italian National Research Council, 2007), retrieved Jun, 2007, http://niremf.ifac.cnr.it/tissprop/.
[163]O. Hjalmarson, K. L. Sandberg, Lung function at term reflects severity of bronchopulmonary dysplasia, The Journal of Pediatrics, 2005, 146(1): 86-90.
[164]W. Shuai, F. You, W. Zhang, et al., Image monitoring for an intraperitoneal bleeding model of pigs using electrical impedance tomography, Physiological Measurement, 2008, 29(2): 217-225.
[165]P. J. Vauhkonen, M. Vauhkonen, T. Savolainen, et al., Three-dimensional electrical impedance tomography based on the complete electrode model, Biomedical Engineering, IEEE Transactions on, 1999, 46(9): 1150-1160.
[166]A. D. Leathard, B. H. Brown, J. Campbell, et al., A comparison of ventilatory and cardiac related changes in EIT images of normal human lungs and of lungs with pulmonary emboli, Physiological Measurement, 1994, 15(2A): A137-A146.
[167]D. P. Berrar ,W. Dubitzky,M. Granzow, A Practical Approach to Microarray Data Analysis Springer, 2002.
[168]董秀珍,生物电阻抗成像研究的现状与挑战,中国生物医学工程学报2008, 27(5): 641-643.
[169]罗辞勇,陈民铀,王平,等,电阻抗成像交叉测量模式的抗噪声性能研究,仪器仪表学报, 2009, 30(1): 14-19.
[170]徐管鑫,王平,何为,实时电阻抗成像系统及实验研究,仪器仪表学报, 2005, 26(9): 886-891.
[171]A. Andy, H. A. John, B. Richard, et al., GREIT: a unified approach to 2D linear EIT reconstruction of lung images, Physiological Measurement, 2009, 30(6): S35-S55.
[172]A. Fagerberg, O. Stenqvist, A. Aneman, Electrical impedance tomography applied to assess matching of pulmonary ventilation and perfusion in a porcine experimental model, Critical Care, 2009, 13(2): R34.
[173]A. Borsic, B. M. Graham, A. Adler , et al., In vivo Impedance Imaging with Total Variation Regularization, IEEE Transaction on Medical Imaging, 2010, 29(1): 44-54.
[174]J. Bikowski, J. L. Mueller, 2D EIT reconstrutions using Calderon's method, Inverse Problem and imaging, 2008, 2(1): 43-61.
[175]G. Mehran, B. Mark-John, J. Aravinthan, et al., A novel approach for EIT regularization via spatial and spectral principal component analysis, Physiological Measurement, 2007, 28(9): 1001-1016.
[176]B. M. Graham, A. Adler, Electrode placement configurations for 3D EIT, Physiological Measurement, 2007, 28(7): S29-S44.
[177]F Kleinermann, N. J. Avis and F. A. Alhargan, Analytical solution to the three-dimensional electrical forward problem for an elliptical cylinder, Physiological Measurement, 2002, 23(1): 141-147.
[178]A. P. Bagshaw, A. D. Liston, R. H. Bayford, et al., Electrical impedance tomography of human brain function using reconstruction algorithms based on the finite element method, NeuroImage, 2003, 20(2): 752-764.
[179]A. Adler,R. Guardo,Y. Berthiaume, Impedance imaging of lung ventilation: do we need to account for chest expansion?, Biomedical Engineering, IEEE Transactions on, 1996, 43(4): 414-420.
[2] H. Dehghani, B. W. Pogue, J. Shudong, et al., Three-Dimensional Optical Tomography: Resolution in Small-Object Imaging, Appl. Opt., 2003, 42(16): 3117-3128.
[3] L. Ding, Y. Lai, B. He, et al., Low resolution brain electromagnetic tomography in a realistic geometry head model: a simulation study, Physics in Medicine and Biology, 2005, 50(1): 45-56.
[4] Brian H. Brown, Medical impedance tomography and process impedance tomography: a brief review, Measurement Science and Technology, 2001, 12(8): 991-996.
[5] G. Steiner,M. Soleimani,D. Watzenig, A bio-electromechanical imaging technique with combined electrical impedance and ultrasound tomography, Physiological Measurement, 2008, 29(6): S63-S75.
[6] Y. Xu,B. He, Magnetoacoustic tomography with magnetic induction (MAT-MI), Physics in Medicine and Biology, 2005, 50(21): 5175-5187.
[7] D. Evren,B. M. Eyuboglu, Anisotropic conductivity imaging with MREIT using equipotential projection algorithm, Physics in Medicine and Biology, 2007, 52(24): 7229-7242.
[8] M.Cheney ,D. Isaacson ,J. Newell Electrical impedance tomography, SIAM Review, 1999, 41(1): 85-101.
[9] Y. Zou,Z. Guo, A review of electrical impedance techniques for breast cancer detection, Medical Engineering & Physics, 2003, 25(2): 79-90.
[10] A. M. Dijkstra, B. H. Brown, A. D. Leathard, et al., Review Clinical applications of electrical impedance tomography, Journal of Medical Engineering & Technology, 1993, 17(3): 89-98.
[11] R. P. Henderson,J. G. Webster, An Impedance Camera for Spatially Specific Measurements of the Thorax, Biomedical Engineering, IEEE Transactions on, 1978, BME-25(3): 250-254.
[12] D. S. Holder, Electrical impedance tomography methods, history and applications, Bristol and Philadelphia: IoP Publishing, 2004.
[13] R. W. M. Smith,I. L. Freeston,B. H. Brown, A real-time electrical impedance tomography system for clinical use-design and preliminary results, Biomedical Engineering, IEEE Transactions on, 1995, 42(2): 133-140.
[14] B. H. Brown,A. D. Seagar, The Sheffield data collection system, Clinical Physics and Physiological Measurement, 1987, 8(4A): 91-97.
[15] A. J. Wilson, P. Milnes, A. R. Waterworth, et al., Mk3.5: a modular, multi-frequency successor to the Mk3a EIS/EIT system, Physiological Measurement, 2001, 22(1): 49-54.
[16] V. Cherepenin, A. Karpov, A. Korjenevsky, et al., Preliminary static EIT images of the thorax in health and disease, Physiological Measurement, 2002, 23(1): 33-41.
[17] V. Cherepenin,et al., A 3D electrical impedance tomography (EIT) system for breast cancer detection, Physiological Measurement, 2001, 22(1): 9-18.
[18] V. A. Cherepenin, A. Y. Karpov, A. V. Korjenevsky, et al., Three-dimensional EIT imaging of breast tissues: system design and clinical testing, Medical Imaging, IEEE Transactions on, 2002, 21(6): 662-667.
[19] "TCI Medical: Diagnostic Imaging" (2003), retrieved http: //www.tcimed.com/diagnosticimaging.html.
[20] Q. Zhu, W. R. B. Lionheart, F. J. Lidgey, et al., An adaptive current tomograph using voltage sources, Biomedical Engineering, IEEE Transactions on, 1993, 40(2): 163-168.
[21] Q. S. Zhu, C. N. McLeod, C. W. Denyer, et al., Development of a real-time adaptive current tomograph, Physiological Measurement, 1994, 15: A37-A43.
[22] A. Hartov, R. A. Mazzarese, F. R. Reiss, et al., A multichannel continuously selectable multifrequency electrical impedance spectroscopy measurement system, Biomedical Engineering, IEEE Transactions on, 2000, 47(1): 49-58.
[23] R. J. Halter,A. Hartov,K. D. Paulsen, A Broadband High-Frequency Electrical Impedance Tomography System for Breast Imaging, Biomedical Engineering, IEEE Transactions on, 2008, 55(2): 650-659.
[24] R. D. Cook, G. J. Saulnier, D. G. Gisser, et al., ACT3: a high-speed, high-precision electrical impedance tomograph, Biomedical Engineering, IEEE Transactions on, 1994, 41(8): 713-722.
[25] P. M. Edic, G. J. Saulnier, J. C. Newell, et al., A real-time electrical impedance tomograph, Biomedical Engineering, IEEE Transactions on, 1995, 42(9): 849-859.
[26] K. Tzu-Jen, G. J. Saulnier, D. Isaacson, et al., A Versatile High-Permittivity Phantom for EIT, Biomedical Engineering, IEEE Transactions on, 2008, 55(11): 2601-2607.
[27] R. J. Yerworth, R. H. Bayford, G. Cusick, et al., Design and performance of the UCLH Mark 1b 64 channel electrical impedance tomography (EIT) system, optimized for imaging brain function, Physiological Measurement, 2002, 23(1): 149-158.
[28] R. E. Serrano,et al., Assessment of the unilateral pulmonary function by means of electrical impedance tomography using a reduced electrode set, Physiological Measurement, 2004, 25(4): 803-813.
[29] S. Jin Keun, L. Jeehyun, K. Sung Wan, et al., Frequency-difference electrical impedance tomography (fdEIT): algorithm development and feasibility study, Physiological Measurement, 2008, 29(8): 929-944.
[30] AM Dijkstra, BH Brown, AD Leathard, et al., Clinical applications of electrical impedance tomography, J Med Eng Technol., 1993, 17(3): 89-98.
[31] M. Cheney,D. Isaacson, Issues in electrical impedance imaging, Computational Science & Engineering, IEEE, 1995, 2(4): 53-62.
[32] Z. Jie,P. P. Robert, EIT images of ventilation: what contributes to the resistivity changes?, Physiological Measurement, 2005, 26(2): S81-S92.
[33] H. J. Smit, A. V. Noordegraaf, R. J. Roeleveld, et al., Epoprostenol-induced pulmonary vasodilatation in patients with pulmonary hypertension measured by electrical impedance tomography, Physiological Measurement, 2002, 23(1): 237-243.
[34] M. W. Robert, G. A. Robert, M. Sha, et al., Markov chain Monte Carlo techniques and spatial-temporal modelling for medical EIT, Physiological Measurement, 2004, 25(1): 181-194.
[35] R. P. Patterson, J. Zhang, L. I. Mason, et al., Variability in the cardiac EIT image as a function of electrode position, lung volume and body position, Physiological Measurement, 2001, 22(1): 159-166.
[36] S. Zlochiver, D. Freimark, M. Arad, et al., Parametric EIT for monitoring cardiac stroke volume, Physiological Measurement, 2006, 27(5): S139-146.
[37] A. R. Hampshire, R. H. Smallwood, B. H. Brown, et al., Multifrequency and parametric EIT images of neonatal lungs, Physiological Measurement, 1995, 16(3A): A175-A189.
[38] T. Dudykevych, H. Richter, G. Hahn, et al., "Software and Operational Concept for EIT-Based regional lung Function monitoring," (Department of Anaesthesiological Research Center of Anaesthesiology, Emergency and Intensive Care Medicine TL 195, G?ttingen, Germany, 2005).
[39] G. Hahn, J. Dittmar, A. Just, et al., Different approaches for quantifying ventilation distribution and lung tissue properties by functional EIT, Physiol Meas, 2010, 31(8): S73-84.
[40] C. M. Michel, G. Thut, S. Morand, et al., Electric source imaging of human brain functions, Brain Research Reviews, 2001, 36(2-3): 108-118.
[41] J. W. Wheless, E. Castillo, V. Maggio, et al., Magnetoencephalography (MEG) and magnetic source imaging (MSI), Neurologist, 2004, 10(3): 138-153.
[42] L. Fabrizi, A. McEwan, E. Woo, et al., Analysis of resting noise characteristics of three EIT systems in order to compare suitability for time difference imaging with scalp electrodes during epileptic seizures, Physiological Measurement, 2007, 28(7): S217-S236.
[43] D. Holder, Feasibility of developing a method of imaging neuronal activity in the human brain: a theoretical review, Medical and Biological Engineering and Computing, 1987, 25(1): 2-11.
[44] D. S. Holder, Detection of cerebral ischaemia in the anaesthetised rat by impedance measurement with scalp electrodes: implications for non-invasive imaging of stroke by electrical impedance tomography, Clinical Physics and Physiological Measurement, 1992, 13(1): 63-75.
[45] D. S. Holder, Electrical impedance tomography with cortical or scalp electrodes during global cerebral ischaemia in the anaesthetised rat, Clinical Physics and Physiological Measurement, 1992, 13(1): 87-98.
[46] K. Boone, A. M. Lewis and D. S. Holder, Imaging of cortical spreading depression by EIT: implications for localization of epileptic foci, Physiological Measurement, 1994, 15(2A): A189-A198.
[47] D. S. Holder,A. Rao,Y. Hanquan, Imaging of physiologically evoked responses by electrical impedance tomography with cortical electrodes in the anaesthetized rabbit, Physiological Measurement, 1996, 17(4A): A179-A186.
[48] A. Rao,Gibson A,H. D. S, EIT images of electrically induced epileptic activity in anaesthetised rabbits, Med. Biol. Eng. Comp, 1997, 35(10): 327-339.
[49] A. Romsauerova, A. McEwan, L. Horesh, et al., Multi-frequency electrical impedance tomography (EIT) of the adult human head: initial findings in brain tumours, arteriovenous malformations and chronic stroke, development of an analysis method and calibration, Physiological Measurement, 2006, 27(5): S147-S161.
[50] J. Abascal, S. R. Arridge, D. Atkinson, et al., Use of anisotropic modelling in electrical impedance tomography; Description of method and preliminary assessment of utility in imaging brain function in the adult human head, NeuroImage, 2008, 43(2): 258-268.
[51] R. J. Sadleir,T. Te, Electrode configurations for detection of intraventricular haemorrhage in the premature neonate, Physiological Measurement, 2009, 30(1): 63-79.
[52] A. Tizzard,R. H. Bayford, Improving the finite element forward model of the human head by warping using elastic deformation, Physiological Measurement, 2007, 28(7): S163-S182.
[53] A. Hartov, R. A. Mazzarese, F. R. Reiss, et al., A multichannel continuously selectable multifrequency electrical impedance spectroscopy measurement system, Biomedical Engineering, IEEE Transactions on, 2000, 47(1): 49-58.
[54] R. J. Halter, A. Schned, J. Heaney, et al., Electrical Impedance Spectroscopy of Benign and Malignant Prostatic Tissues, The Journal of Urology, 2008, 179(4): 1580-1586.
[55] J. H. Ryan, H. Alex, D. P. Keith, Experimental justification for using 3D conductivity reconstructions in electrical impedance tomography, Physiological Measurement, 2007, 28(7): S115-S127.
[56]周吕,柯美云,神经胃肠病学与动力一基础与临床,北京:科学出版社, 2005.
[57] H. Piessevaux, J. Tack, S. Walrand, et al., Intragastric distribution of a standardized meal in health and functional dyspepsia: correlation with specific symptoms, Neurogastroenterology & Motility, 2003, 15(5): 447-455.
[58]赵舒,任超世,生物电阻抗法检测胃动力功能,国际生物医学工程杂志, 2006, 29(92-95.
[59] C. T. Soulsby, M. Khela, E. Yazaki, et al., Measurements of gastric emptying during continuous nasogastric infusion of liquid feed: Electric impedance tomography versus gamma scintigraphy, Clinical Nutrition, 2006, 25(4): 671-680.
[60] F. Podczeck, C. L. Mitchell, J. M. Newton, et al., The gastric emptying of food as measured by gamma-scintigraphy and electrical impedance tomography (EIT) and its influence on the gastric emptying of tablets of different dimensions, Journal of Pharmacy and Pharmacology, 2007, 59(11): 1527-1536.
[61] J. W. Wright, The effect of intraluminal content on gastrointestinal motility in man, Nottingham; University of Nottingham, 1995.
[62] K. D. Paulsen, M. J. Moskowitz, T. P. Ryan, et al., Initial in vivo experience with EIT as a thermal estimator during hyperthermia, Int J Hyperthermia, 1996, 12(5): 573-591.
[63] F. Ferraioli, A. Formisano, R. Martone, Effective Exploitation of Prior Information in Electrical Impedance Tomography for Thermal Monitoring of Hyperthermia Treatments, Magnetics, IEEE Transactions on, 2009, 45(3): 1554-1557.
[64] D. C. Thomas, F. J. Mcardle, V. E. Rogers, et al., Local Blood Volume Changes in Women With Pelvic Congestion Measured by Applied Potential Tomography, Obstetrical & Gynecological Survey, 1992, 47(4): 265-266.
[65] A. Vonk Noordegraaf, P. W. A. Kunst, A. Janse, et al., Validity and reproducibility of electrical impedance tomography for measurement of calfblood flow in healthy subjects Medical and Biological Engineering and Computing, 1997, 35(2): 107-112.
[66] R. J. Sadleir, R. A. Fox, Detection and quantification of intraperitoneal fluid using electrical impedance tomography, Biomedical Engineering, IEEE Transactions on, 2001, 48(4): 484-491.
[67] B. H. Brown,et al., Applied potential tomography: possible clinical applications, Clinical Physics and Physiological Measurement, 1985, 6(2): 109-121.
[68] B. M. Eyübo?lu, B. H. Brown, D. C. Barber, et al., Localisation of cardiac related impedance changes in the thorax, Clin Phys Physiol Meas, 1987, 8 (Suppl A): 67-73.
[69] F. J. McArdle, A. J. Suggett, B. H. Brown, et al., An assessment of dynamic images by applied potential tomography for monitoring pulmonary perfusion, Clinical Physics and Physiological Measurement, 1988, 9(4A): 87-91.
[70] B. M. Eyuboglu, B. H. Brown, D. C. Barber, In vivo imaging of cardiac related impedance changes, Engineering in Medicine and Biology Magazine, IEEE, 1989, 8(1): 39-45.
[71] D. Isaacson, J. C. Newell, J. C. Goble, et al., Thoracic Impedance Images During Ventilation, Annual Intematisnal Conference of the IEEE Engineering in Medicine and Biology Society, 1990: 106-107.
[72] L. F. Fuks, M. Cheney, D. Isaacson, et al., Detection and imaging of electric conductivity and permittivity at low frequency, Biomedical Engineering, IEEE Transactions on, 1991, 38(11): 1106-1110.
[73] H. Griffiths, H. T. L. Leung, R. J. Williams, Imaging the complex impedance of the thorax, Clinical Physics and Physiological Measurement, 1992, 13(A): 77-81.
[74] J. H. Campbell, N. D. Harris, F. Zhang, et al., Clinical applications of electrical impedance tomography in the monitoring of changes in intrathoracic fluid volumes, Physiological Measurement, 1994, 15(2A): A217-A222.
[75] G. Hahn, I. Sipinkova, F. Baisch, et al., Changes in the thoracic impedance distribution under different ventilatory conditions, Physiological Measurement, 1995, 16(3A): A161-A173.
[76] J. C. Newell, D. Isaacson, R. S. Blue, Regional ventilation and perfusion assessed by electrical impedance imaging, 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Amsterdam, 1996: 780-781.
[77] A. Adler, R. Amyot, R. Guardo, et al., Monitoring changes in lung air and liquid volumes with electrical impedance tomography, J Appl Physiol, 1997, 83(5): 1762-1767.
[78] N. Anton Vonk, W. A. K. Peter, J. Andre, et al., Pulmonary perfusion measured by means of electrical impedance tomography, Physiological Measurement, 1998, 19(2): 263-273.
[79] I. Frerichs,G. Hahn,G. Hellige, Thoracic electrical impedance tomographic measurements during volume controlled ventilation-effects of tidal volume and positive end-expiratory pressure, Medical Imaging, IEEE Transactions on, 1999, 18(9): 764-773.
[80] I. Frerichs, G. Hahn, H. Schiffmann, et al., Monitoring regional lung ventilation by functional electrical impedance tomography during assisted ventilation, Ann. NY Acad. Sci., 1999, 873: 493-505.
[81] V.-N. Anton, J. Andre, T. M. Johan, et al., Determination of stroke volume by means of electrical impedance tomography, Physiological Measurement, 2000, 21(2): 285-293.
[82] N. Kerrouche,C. N. McLeod,W. R. B. Lionheart, Time series of EIT chest images using singular value decomposition and Fourier transform, Physiological Measurement, 2001, 22(1): 147-157.
[83] I. Frerichs, J. Hinz, P. Herrmann, et al., Regional lung perfusion as determined by electrical impedance tomography in comparison with electron beam CT imaging, Medical Imaging, IEEE Transactions on, 2002, 21(6): 646-652.
[84] I. Frerichs, J. Hinz, P. Herrmann, et al., Detection of local lung air content by electrical impedance tomography compared with electron beam CT, J Appl Physiol, 2002, 93(2): 660-666.
[85] Henk J. Smit, Anton Vonk-Noordegraaf, J. Tim Marcus, et al., Pulmonary Vascular Responses to Hypoxia and Hyperoxia in Healthy Volunteers and COPD Patients Measured by Electrical Impedance Tomography, Chest, 2003, 123(6): 1803-1809.
[86] J. Hinz, G. Hahn, P. Neumann, et al., End-expiratory lung impedance change enables bedside monitoring of end-expiratory lung volume change, Intensive Care Medicine, 2003, 29(11): 37-43.
[87] Josue′A. Victorino, Joa?o B. Borges, Valdelis N. Okamoto, et al., Imbalances in Regional Lung Ventilation: A Validation Study on Electrical Impedance Tomography, Am J Respir Crit Care Med, 2004, 169(1): 791-800.
[88] I. Frerichs, M. Bodenstein, T. Dudykevych, et al., Effect of lower body negative pressure and gravity on regional lung ventilation determined by EIT, Physiological Measurement, 2005, 26(2): S27-S37.
[89] G. Hahn, A. Just, T. Dudykevych, et al., Imaging pathologic pulmonary air and fluid accumulation by functional and absolute EIT, Physiological Measurement, 2006, 27(5): S187-S198.
[90] L. Beckmann, D. Van Riesen, S. Leonhardt, Optimal electrode placement and frequency range selection for the detection of lung water using Bioimpedance Spectroscopy, 29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07, Lyon, France, 2007: 2685-2688.
[91] M. Risdal, S. O. Aase, M. Stavland, et al., Impedance-Based Ventilation Detection During Cardiopulmonary Resuscitation, Biomedical Engineering, IEEE Transactions on, 2007, 54(12): 2237-2245.
[92] R. Bayford, P. Kantartzis, A. Tizzard, et al., Development of a neonate lung reconstruction algorithm using a wavelet AMG and estimated boundary form, Physiological Measurement, 2008, 29(6): S125-S138.
[93] J. Bruno de Lema, E. Serrano, T. Feixas, et al., Assessment of Differential Lung Function by Electrical Impedance Tomography, Archivos de Bronconeumolog韆 (English Edition), 2008, 44(8): 408-412.
[94] J. M. Deibele, H. Luepschen, S. Leonhardt, Dynamic separation of pulmonary and cardiac changes in electrical impedance tomography, Physiological Measurement, 2008, 29(6): S1-S14.
[95] M. Denai, M. Mahfouf, S. Mohamad-Samuri, et al., Absolute Electrical Impedance Tomography (aEIT) Guided Ventilation Therapy in Critical Care Patients: Simulations and Future Trends, Information Technology in Biomedicine, IEEE Transactions on , 2010, 14(3): 641-649.
[96] K. Jihyeon, W. Eung Je, S. Jin Keun, Multi-frequency time-difference complex conductivity imaging of canine and human lungs using the KHU Mark1 EIT system, Physiological Measurement, 2009, 30(6): S149-S164.
[97] B. Grychtol, G. K. Wolf, J. H. Arnold, Differences in regional pulmonary pressure--impedance curves before and after lung injury assessed with a novel algorithm, Physiological Measurement, 2009, 30(6): S137-S148.
[98] J. Zhang, R. Patterson, Non-invasive determination of absolute lung resistivity in adults using electrical impedance tomography, Physiological Measurement, 2010, 31(8): S45-S56.
[99] B. Grychtol, et al., Towards lung EIT image segmentation: automatic classification of lung tissue state from analysis of EIT monitored recruitment manoeuvres, Physiological Measurement, 2010, 31(8): S31-S43.
[100]董秀珍,秦明新,付峰,生物电阻抗断层成像技术的研究进展,第四军医大学学报, 1999, 20(3): 252-255.
[101]尤富生,董秀珍,史学涛,等,电阻抗断层成像中临近和对向驱动模式的研究,第四军医大学学报, 2004, 25(1): 88-91.
[102]史学涛,董秀珍,帅万钧,等,适用于脑部电阻抗断层成像的单源驱动电流模式,第四军医大学学报, 2006, 27(3): 279-282.
[103]廖琪梅,徐玉乔,董秀珍,等,乳腺癌及周围组织电阻抗频谱特性与其病理学特征的研究,生物医学工程与临床, 2008, 12(4): 263-266.
[104]A. Ni, X. Dong, G. Yang, et al., Image reconstruction incorporated with the skull inhomogeneity for electrical impedance tomography, Computerized Medical Imaging and Graphics, 2008, 32(5): 409-415.
[105]Z. Cui, H. Wang, L. Tang, et al., A Specific Data Acquisition Scheme for Electrical Tomography, Instrumentation and Measurement Technology Conference Proceedings, IMTC. IEEE, 2008: 726-729.
[106]崔自强,双模态电学层析成像技术研究: [博士学位论文],天津;天津大学, 2009.
[107]张帅,人体胸腔电阻抗成像系统研究: [博士学位论文],天津;河北工业大学, 2009.
[108]毕德显,电磁场理论,北京:电子工业出版社, 1985.
[109]M. Vauhkonen, Electrical impedance tomography and prior information, [Phd thesis], Finland; University of Kuopio, 1997.
[110]Andrea Borsic, Regularisation Methods for Imaging from Electrical Measurements, Oxford Brookes University, 2002.
[111]倪光正,钱秀英,电磁场数值计算,北京:高等教育出版社, 1996.
[112]N. Polydorides, W. R. B. Lionheart, A Matlab toolkit for three-dimensional electrical impedance tomography: a contribution to the Electrical Impedance and Diffuse Optical Reconstruction Software project, Measurement Science and Technology, 2002, 13(4): 1871-1883.
[113]M. Vauhkonen, P. A. Karjalainen, J. P. Kaipio, A Kalman filter approach to track fast impedance changes in electrical impedance tomography, Biomedical Engineering, IEEE Transactions on, 1998, 45(4): 486-493.
[114]P. M. Edic, D. Isaacson, G. J. Saulnier, et al., An iterative Newton-Raphson method to solve the inverse admittivity problem, Biomedical Engineering, IEEE Transactions on, 1998, 45(7): 899-908.
[115]王超,医学电阻抗断层成像的研究: [博士学位论文],天津大学, 2001.
[116]D. B. Geselowitz, An Application of Electrocardiographic Lead Theory to Impedance Plethysmography, Biomedical Engineering, IEEE Transactions on, 1971, BME-18(1): 38-41.
[117]J. Lehr, A Vector Derivation Useful in Impedance Plethysmographic Field Calculations, Biomedical Engineering, IEEE Transactions on, 1972, BME-19(2): 156-157.
[118]T. Murai, Y. Kagawa, Electrical Impedance Computed Tomography Based on a Finite Element Model, Biomedical Engineering, IEEE Transactions on, 1985, BME-32(3): 177-184.
[119]M.-L. H. Rasmussen,L. K. H. Clemmensen, The Effect of Regularizing Matrices and Norms in Tikhonov Based Image Restorations, Denmark; Technical University of Denmark, 2003.
[120]P. C. Hansen, Discrete inverse problems insight and algorithms Denmark; Technical University of Denmark, 2005.
[121]W. Q. Yang, D. M. Spink, T. A. York, et al., An image-reconstruction algorithm based on Landweber's iteration method for electrical-capacitance tomography, Measurement Science and Technology, 1999, 10(11): 1065-1069.
[122]W. Q. Yang, P. Lihui, Image reconstruction algorithms for electrical capacitance tomography, Measurement Science and Technology, 2003, 14(1): R1-R13.
[123]M. Wang, Inverse solutions for electrical impedance tomography based on conjugate gradients methods, Measurement Science and Technology, 2002, 13(101-117.
[124]H. Wang, C. Wang, W. Yin, A pre-iteration method for the inverse problem in electrical impedance tomography, IEEE Instrumentation and Measurement Technology Conference, 2004: 392-395.
[125]M. Hanke, P.C. Hansen, Conjugate gradient type methods for ill-posed problems, Essex: Scientific & Technical, Longman, 1995.
[126]P. J. Vauhkonen, M. Vauhkonen, J. P. Kaipio, Fixed-lag smoothing and state estimation in dynamic electrical impedance tomography, International Journal for Numerical Methods in Engineering, 2001, 50(9): 2195-2209.
[127]O. P. Tossavainen, M. Vauhkonen, V. Kolehmainen, A three-dimensional shape estimation approach for tracking of phase interfaces in sedimentation processes using electrical impedance tomography, Measurement Science and Technology, 2007, 18(5): 1413-1424.
[128]A. Seppaen, M. Vauhkonen, P. J. Vauhkonen, et al., State estimation in process tomography--Three-dimensional impedance imaging of moving fluids, International Journal for Numerical Methods in Engineering, 2008, 73(11): 1651-1670.
[129]K. Y. Kim, B. S. Kim, M. C. Kim, et al., Image reconstruction in time-varying electrical impedance tomography based on the extended Kalman filter, Measurement Science and Technology, 2001, 12(8): 1032-1039.
[130]A. Seppanen, M. Vauhkonen, P. J. Vauhkonen, et al., State estimation with fluid dynamical evolution models in process tomography - an application to impedance tomography, Inverse Problems, 2001, 17(3): 467-483.
[131]S. M. Fernando, C. C. A. Julio, G. L. Raul, et al., Online transition matrix identification of the state evolution model for the extended Kalman filter in electrical impedance tomography, Journal of Physics: Conference Series, 2008, 012052.
[132]F. S. Moura, J. C. C. Aya, A. T. Fleury, et al., Dynamic Imaging in Electrical Impedance Tomography of the Human Chest With Online Transition Matrix Identification, Biomedical Engineering, IEEE Transactions on, 2010, 57(2): 422-431.
[133]K. Knudsen, J. Mueller, S. Siltanen, Numerical solution method for the dbar-equation in the plane, Journal of Computational Physics, 2004, 198(2): 500-517.
[134]D. Isaacson, J. L. Mueller, J. C. Newell, et al., Reconstructions of chest phantoms by the D-bar method for electrical impedance tomography, Medical Imaging, IEEE Transactions on, 2004, 23(7): 821-828.
[135]D. Isaacson, J. L. Mueller, J. C. Newell, et al., Imaging cardiac activity by the D-bar method for electrical impedance tomography, Physiological Measurement, 2006, 27(5): S43-S50.
[136]J. G. Webster, ed., Electrical Impedance Tomography, Hilger, Bristol, 1990.
[137]M. Cheney, D. Isaacson, E. J. Somersalo, et al., A Layer-stripping Reconstruction Algorithm For Impedance Imaging, Proceedings of the Annual International Conference of the IEEE, Engineering in Medicine and Biology Society, 1991: 3-4.
[138]C. R. Smith, W. T. Grandy, Maximum-Entropy and Bayesian Methods in Inverse Problems, Reidel, Boston, 1985.
[139]Jorge Nocedal, S. J. Wright, Numerical optimization Springer-Verlag New York, Inc, 1999.
[140]王化祥,汪婧,胡理,等,基于肺部先验知识的电阻抗成像重构算法,天津大学学报, 2008, 41(4): 383-388.
[141]Y. S. Kim, S. H. Lee, U. Z. Ijaz, et al., Sensitivity map generation in electrical capacitance tomography using mixed normalization models, Measurement Science and Technology, 2007, 18(6): 2092-2102.
[142]M. T. Clay, T. C. Ferree, Weighted regularization in electrical impedance tomography with applications to acute cerebral stroke, Medical Imaging, IEEE Transactions on, 2002, 21(6): 629-637.
[143]R. B. L. William, EIT reconstruction algorithms: pitfalls, challenges and recent developments, Physiological Measurement, 2004, 25(1): 125-142.
[144]H. Dehghani, D. C. Barber, I. Basarab-Horwath, Incorporating a priori anatomical information into image reconstruction in electrical impedance tomography, Physiological Measurement, 1999, 20: 87-102.
[145]G. H. Golub, C. H. Vanloan, Matrix computations Baltimore: The Johns Hopkins University Press, 1989.
[146]P. C. Hansen, T. K. Jensen, G. Rodriguez, An adaptive pruning algorithm for the discrete L-curve criterion, J. Comput. Appl. Math., 2007, 198(2): 483-492.
[147]G. H. Golub,U. v. Matt, Generalized cross-validation for large scale problems, Proceedings of the second international workshop on Recent advances in total least squares techniques and errors-in-variables modeling, Leuven, Belgium, 1997: 139-148.
[148]F. Bauer, S. Kindermann, The quasi-optimality criterion for classical inverse problems, Inverse Problems, 2008, 24: 035002 (20pp).
[149]M. Jacobsen, Modular regularization algorithms Denmark, [PhD Thesis], Technical University of Denmark, 2004.
[150]D. Calvetti, L. Reichel, A. Shuibi, Invertible smoothing preconditioners for linear discrete ill-posed problems, Appl. Numer. Math., 2005, 54(2): 135-149.
[151]W. Mi, M. Yixin, N. Holliday, et al., A high-performance EIT system, Sensors Journal, IEEE, 2005, 5(2): 289-299.
[152]W. R. Fan, H. X. Wang, X. Y. Chen, et al., Three dimensional EIT models for human lung reconstruction based on Schur CG algorithm, New York: Ieee, 2009.
[153]A. Seppanen, A. Voutilainen, J. P. Kaipio, State estimation in process tomography-reconstruction of velocity fields using EIT, Inverse Problems, 2009, 25: 085009 (24pp).
[154]L. Hu, H. Wang, B. Zhao, et al., A hybrid reconstruction algorithm for electrical impedance tomography, Measurement Science and Technology, 2007, 18(3): 813-818.
[155]I. Basarab-Horwath, J. Piotrowski, P. M. McEwan, Calculated measures of performance in electrical impedance tomography using a finite-element model, Physiological Measurement, 1995, 16: 263-271.
[156]D. Calvetti, L. Reichel, A. Shuibi, Invertible smoothing preconditioners for linear discrete ill-posed problems, Applied Numerical Mathematics, 2005, 54(2): 135-149.
[157]C. R. Vogel and M. Hanke, Two-level preconditioners for regularized inverse problems I, Theory Numer. Math., 1999, 83: 385-402.
[158]M. Jacobsen,P. C. Hansen,M. A. Saunders, Subspace preconditioned LSQR for discrete ill-posed problems, BIT, 2003, 43: 975-989.
[159]O. M. Nielsen, Wavelets in scientific computing, Technical University of Denmark, 1998.
[160]G. Strang, The discrete cosine transform, SIAM Rev, 1999.
[161]H. Luepschen, D. van Riesen, L. Beckmann, et al., Modeling of Fluid Shifts in the Human Thorax for Electrical Impedance Tomography, Magnetics, IEEE Transactions on, 2008, 44(6): 1450-1453.
[162]"Dielectric properties of body tissue" (Institute for Applied Physics, Italian National Research Council, 2007), retrieved Jun, 2007, http://niremf.ifac.cnr.it/tissprop/.
[163]O. Hjalmarson, K. L. Sandberg, Lung function at term reflects severity of bronchopulmonary dysplasia, The Journal of Pediatrics, 2005, 146(1): 86-90.
[164]W. Shuai, F. You, W. Zhang, et al., Image monitoring for an intraperitoneal bleeding model of pigs using electrical impedance tomography, Physiological Measurement, 2008, 29(2): 217-225.
[165]P. J. Vauhkonen, M. Vauhkonen, T. Savolainen, et al., Three-dimensional electrical impedance tomography based on the complete electrode model, Biomedical Engineering, IEEE Transactions on, 1999, 46(9): 1150-1160.
[166]A. D. Leathard, B. H. Brown, J. Campbell, et al., A comparison of ventilatory and cardiac related changes in EIT images of normal human lungs and of lungs with pulmonary emboli, Physiological Measurement, 1994, 15(2A): A137-A146.
[167]D. P. Berrar ,W. Dubitzky,M. Granzow, A Practical Approach to Microarray Data Analysis Springer, 2002.
[168]董秀珍,生物电阻抗成像研究的现状与挑战,中国生物医学工程学报2008, 27(5): 641-643.
[169]罗辞勇,陈民铀,王平,等,电阻抗成像交叉测量模式的抗噪声性能研究,仪器仪表学报, 2009, 30(1): 14-19.
[170]徐管鑫,王平,何为,实时电阻抗成像系统及实验研究,仪器仪表学报, 2005, 26(9): 886-891.
[171]A. Andy, H. A. John, B. Richard, et al., GREIT: a unified approach to 2D linear EIT reconstruction of lung images, Physiological Measurement, 2009, 30(6): S35-S55.
[172]A. Fagerberg, O. Stenqvist, A. Aneman, Electrical impedance tomography applied to assess matching of pulmonary ventilation and perfusion in a porcine experimental model, Critical Care, 2009, 13(2): R34.
[173]A. Borsic, B. M. Graham, A. Adler , et al., In vivo Impedance Imaging with Total Variation Regularization, IEEE Transaction on Medical Imaging, 2010, 29(1): 44-54.
[174]J. Bikowski, J. L. Mueller, 2D EIT reconstrutions using Calderon's method, Inverse Problem and imaging, 2008, 2(1): 43-61.
[175]G. Mehran, B. Mark-John, J. Aravinthan, et al., A novel approach for EIT regularization via spatial and spectral principal component analysis, Physiological Measurement, 2007, 28(9): 1001-1016.
[176]B. M. Graham, A. Adler, Electrode placement configurations for 3D EIT, Physiological Measurement, 2007, 28(7): S29-S44.
[177]F Kleinermann, N. J. Avis and F. A. Alhargan, Analytical solution to the three-dimensional electrical forward problem for an elliptical cylinder, Physiological Measurement, 2002, 23(1): 141-147.
[178]A. P. Bagshaw, A. D. Liston, R. H. Bayford, et al., Electrical impedance tomography of human brain function using reconstruction algorithms based on the finite element method, NeuroImage, 2003, 20(2): 752-764.
[179]A. Adler,R. Guardo,Y. Berthiaume, Impedance imaging of lung ventilation: do we need to account for chest expansion?, Biomedical Engineering, IEEE Transactions on, 1996, 43(4): 414-420.