Nonlinear Difference Imaging Approach to Three-Dimensional Electrical Impedance Tomography in the Presence of Geometric Modeling Errors

Objective: To evaluate the recently proposed nonlinear difference imaging approach to electrical impedance tomography (EIT) in realistic 3-D geometries. Methods: In this paper, the feasibility of nonlinear difference approach-based EIT is tested using simulation studies in 3-D geometries of thorax and larynx, and with an experimental study of a thorax-shaped water tank. All test cases exhibit severe modeling errors due to uncertainty in the boundary shape of the body. Results: In all test cases, the conductivity change reconstructed with nonlinear difference imaging outperforms the conventional reconstructions qualitatively and quantitatively. Conclusion: The results demonstrate that the nonlinear difference reconstructions tolerate geometrical modeling errors at least to the same extent as the conventional linear approach and produce quantitatively more accurate information on the conductivity change. Significance: Physiological processes that produce changes in the electrical conductivity of the body can be monitored with difference imaging based on EIT. The wide popularity of linearized difference imaging in EIT is mainly based on its good tolerance for the ubiquitous modeling errors, which are predominantly caused by inexact knowledge of the body geometry. However, the linearized difference imaging produces only qualitative information on the conductivity change, and the feasibility of the estimates also depends on the selection of the linearization point which ideally should be equal to the conductivity of the initial state. Based on the findings of this paper, these problems can be avoided by nonlinear difference imaging, and potentially the approach can enable quantitative imaging of conductivity change in medical applications.

[1]  S Abboud,et al.  Parametric EIT for monitoring cardiac stroke volume , 2006, Physiological measurement.

[2]  A Hartov,et al.  Sensitivity study of an ultrasound coupled transrectal electrical impedance tomography system for prostate imaging , 2010, Physiological measurement.

[3]  B. Brown,et al.  Applied potential tomography. , 1989, Journal of the British Interplanetary Society.

[4]  Andy Adler,et al.  The impact of electrode area, contact impedance and boundary shape on EIT images , 2011, Physiological measurement.

[5]  Dong Liu,et al.  Estimation of conductivity changes in a region of interest with electrical impedance tomography , 2014, 1403.6587.

[6]  J C Newell,et al.  Imaging cardiac activity by the D-bar method for electrical impedance tomography , 2006, Physiological measurement.

[7]  Jari P. Kaipio,et al.  Randomize-Then-Optimize for Sampling and Uncertainty Quantification in Electrical Impedance Tomography , 2015, SIAM/ASA J. Uncertain. Quantification.

[8]  C. Gabriel,et al.  Electrical conductivity of tissue at frequencies below 1 MHz , 2009, Physics in medicine and biology.

[9]  Dong Liu,et al.  A nonlinear approach to difference imaging in EIT; assessment of the robustness in the presence of modelling errors , 2015 .

[10]  Zhenyu Guo,et al.  A review of electrical impedance techniques for breast cancer detection. , 2003, Medical engineering & physics.

[11]  D C Barber,et al.  Fast reconstruction of resistance images. , 1987, Clinical physics and physiological measurement : an official journal of the Hospital Physicists' Association, Deutsche Gesellschaft fur Medizinische Physik and the European Federation of Organisations for Medical Physics.

[12]  Marko Vauhkonen,et al.  Simultaneous reconstruction of electrode contact impedances and internal electrical properties: II. Laboratory experiments , 2002 .

[13]  G Hahn,et al.  Imaging pathologic pulmonary air and fluid accumulation by functional and absolute EIT , 2006, Physiological measurement.

[14]  J P Kaipio,et al.  Assessment of errors in static electrical impedance tomography with adjacent and trigonometric current patterns. , 1997, Physiological measurement.

[15]  V. Cherepenin,et al.  Three-dimensional EIT imaging of breast tissues: system design and clinical testing , 2002, IEEE Transactions on Medical Imaging.

[16]  Gerhard Hellige,et al.  Detection of local lung air content by electrical impedance tomography compared with electron beam CT. , 2002, Journal of applied physiology.

[17]  Samuli Siltanen,et al.  Linear and Nonlinear Inverse Problems with Practical Applications , 2012, Computational science and engineering.

[18]  L. Rudin,et al.  Nonlinear total variation based noise removal algorithms , 1992 .

[19]  Ville Kolehmainen,et al.  Experimental evaluation of 3D electrical impedance tomography with total variation prior , 2016 .

[20]  M. Soleimani,et al.  Imaging of conductivity changes and electrode movement in EIT , 2006, Physiological measurement.

[21]  Andy Adler,et al.  Shape Deformation in Two-Dimensional Electrical Impedance Tomography , 2012, IEEE Transactions on Medical Imaging.

[22]  E. Somersalo,et al.  Existence and uniqueness for electrode models for electric current computed tomography , 1992 .

[23]  K. W. Wang,et al.  Damage detection and conductivity evolution in carbon nanofiber epoxy via electrical impedance tomography , 2014 .

[24]  B H Brown,et al.  Electrical impedance tomography (EIT): a review , 2003, Journal of medical engineering & technology.

[25]  D S Holder,et al.  Use of polyacrylamide gels in a saline-filled tank to determine the linearity of the Sheffield Mark 1 electrical impedance tomography (EIT) system in measuring impedance disturbances. , 1994, Physiological measurement.

[26]  Ryan Halter,et al.  Excitation patterns in three-dimensional electrical impedance tomography , 2005, Physiological measurement.

[27]  J.P. Kaipio,et al.  Three-dimensional electrical impedance tomography based on the complete electrode model , 1999, IEEE Transactions on Biomedical Engineering.

[28]  Marko Vauhkonen,et al.  Suitability of a PXI platform for an electrical impedance tomography system , 2008 .

[29]  Malte Kob,et al.  A system for parallel measurement of glottis opening and larynx position , 2009, Biomed. Signal Process. Control..

[30]  A. Adler,et al.  Impedance imaging of lung ventilation: do we need to account for chest expansion? , 1996, IEEE Transactions on Biomedical Engineering.

[31]  I Frerichs,et al.  Electrical impedance tomography (EIT) in applications related to lung and ventilation: a review of experimental and clinical activities. , 2000, Physiological measurement.

[32]  Richard H. Bayford,et al.  Electrical impedance tomography of human brain function using reconstruction algorithms based on the finite element method , 2003, NeuroImage.

[33]  Karen Willcox,et al.  Parameter and State Model Reduction for Large-Scale Statistical Inverse Problems , 2010, SIAM J. Sci. Comput..

[34]  Jari P. Kaipio,et al.  Electrical impedance tomography imaging with reduced-order model based on proper orthogonal decomposition , 2013, J. Electronic Imaging.

[35]  D. Isaacson,et al.  Electrode models for electric current computed tomography , 1989, IEEE Transactions on Biomedical Engineering.

[36]  Gregory Boverman,et al.  Robust Linearized Image Reconstruction for Multifrequency EIT of the Breast , 2008, IEEE Transactions on Medical Imaging.

[37]  Andrea Aliverti,et al.  Respiratory muscle activation and action during cough , 2013 .