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A MATLAB-Based Boundary Data Simulator for Studying the Resistivity Reconstruction Using Neighbouring Current Pattern

DOI: 10.1155/2013/193578

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Abstract:

Phantoms are essentially required to generate boundary data for studying the inverse solver performance in electrical impedance tomography (EIT). A MATLAB-based boundary data simulator (BDS) is developed to generate accurate boundary data using neighbouring current pattern for assessing the EIT inverse solvers. Domain diameter, inhomogeneity number, inhomogeneity geometry (shape, size, and position), background conductivity, and inhomogeneity conductivity are all set as BDS input variables. Different sets of boundary data are generated by changing the input variables of the BDS, and resistivity images are reconstructed using electrical impedance tomography and diffuse optical tomography reconstruction software (EIDORS). Results show that the BDS generates accurate boundary data for different types of single or multiple objects which are efficient enough to reconstruct the resistivity images for assessing the inverse solver. It is noticed that for the BDS with 2048 elements, the boundary data for all inhomogeneities with a diameter larger than 13.3% of that of the phantom are accurate enough to reconstruct the resistivity images in EIDORS-2D. By comparing the reconstructed image with an original geometry made in BDS, it would be easier to study the inverse solver performance and the origin of the boundary data error can be identified. 1. Introduction Electrical impedance tomography (EIT) [1, 2] reconstructs the spatial distribution of electrical conductivity or resistivity of a closed conducting domain ( ) from the surface potentials developed by a constant current injection through the surface electrodes surrounding the domain to be imaged. Before carrying out the practical measurements on patients, it is advised to test an EIT system with a tissue mimicking model of known properties [3] called practical phantoms [4–10]. Hence, phantoms are often required to assess the performance of EIT systems for their validation, calibration, and comparison purposes. Two-dimensional (2D) EIT (2D-EIT) assumes that the electrical current flows in a 2D space which is actually three-dimensional inside real volume conductors. Hence, the development of a perfect 2D practical phantom is a great challenge as the real electrodes always have a definite surface area, and hence the injected current signal cannot be confined in a 2D plane in bathing solution [5]. Researchers have developed a number of practical phantoms which are three-dimensional objects, and those phantoms are designed and developed, generally, for their own EIT systems. Practical phantoms containing

References

[1]  J. G. Webster, Electrical Impedance Tomography, Adam Hilger Series of Biomedical Engineering, Adam Hilger, New York, NY, USA, 1990.
[2]  D. S. Holder, Electrical Impedance Tomography: Methods, History and Applications, Series in Medical Physics and Biomedical Engineering, Institute of Physics Publishing Ltd., Bristol, UK, 1st edition, 2005.
[3]  H. Griffiths and Z. Zhang, “A dual-frequency electrical impedance tomography system,” Physics in Medicine and Biology, vol. 34, no. 10, pp. 1465–1476, 1989.
[4]  T. K. Bera and J. Nagaraju, “A multifrequency constant current source suitable for Electrical Impedance Tomography (EIT),” in Proceedings of the IEEE International Conference on Systems in Medicine and Biology (ICSMB '10), pp. 278–283, Kharagpur, India, December 2010.
[5]  T. K. Bera and J. Nagaraju, “A reconfigurable practical phantom for studying the 2D Electrical Impedance Tomography (EIT) using a FEM based forward solver,” in Proceedings of the 10th International Conference on Biomedical Applications of Electrical Impedance Tomography (EIT '09), School of Mathematics, The University of Manchester, Manchester, UK, June 2009.
[6]  D. S. Holder, Y. Hanquan, and A. Rao, “Some practical biological phantoms for calibrating multifrequency electrical impedance tomography,” Physiological Measurement, vol. 17, no. 4, pp. A167–A177, 1996.
[7]  T. K. Bera and J. Nagaraju, “Studying the 2D-Image Reconstruction of Non Biological and Biological Inhomogeneities in Electrical Impedance Tomography (EIT) with EIDORS,” in Proceedings of the International Conference on Advanced Computing, Networking and Security (ADCONS’ 11), pp. 132–136, NITK-Surathkal, Mangalore, India.
[8]  T. K. Bera and J. Nagaraju, “A stainless steel electrode phantom to study the forward problem of Electrical Impedance Tomography (EIT),” Sensors & Transducers Journal, vol. 104, no. 5, pp. 33–40, 2009.
[9]  H. Griffiths, “A phantom for electrical impedance tomography,” Clinical Physics and Physiological Measurement, vol. 9, supplement A, pp. 15–20, 1988.
[10]  T. K. Bera and J. Nagaraju, “Resistivity imaging of a reconfigurable phantom with circular inhomogeneities in 2D-electrical impedance tomography,” Measurement, vol. 44, no. 3, pp. 518–526, 2011.
[11]  H. Griffiths, Z. Zhang, and M. Watts, “A constant-perturbation saline phantom for electrical impedance tomography,” Physics in Medicine and Biology, vol. 34, no. 8, pp. 1063–1071, 1989.
[12]  H. Gagnon, A. E. Hartinger, A. Adler, and R. Guardo, “A resistive mesh phantom for assessing the performance of EIT systems,” in Proceedings of the International Conference on Biomedical Applications of Electrical Impedance Tomography (EIT '09), Manchester, UK, 2009.
[13]  H. Gagnon, Y. Sigmen, A. E. Hartinger, and R. Guardo, “An active phantom to assess the robustness of EIT systems to electrode contact impedance variations,” in Proceedings of the International Conference on Biomedical Applications of Electrical Impedance Tomography (EIT '09), Manchester, UK, 2009.
[14]  G. Hahn, A. Just, and G. Hellige, “Determination of the dynamic measurement error of EIT systems,” in Proceedings of the 13th International Conference on Electrical Bioimpedance and the 8th Conference on Electrical Impedance Tomography (ICEBI '07), IFMBE Proceedings 17, pp. 320–323, September 2007.
[15]  W. R. B. Lionheart, “EIT reconstruction algorithms: pitfalls, challenges and recent developments,” Physiological Measurement, vol. 25, pp. 125–142, 2004.
[16]  T. K. Bera, S. K. Biswas, K. Rajan, and J. Nagaraju, “Improving image quality in Electrical Impedance Tomography (EIT) using projection error propagation-based regularization (PEPR) technique: a simulation study,” Journal of Electrical Bioimpedance, vol. 2, pp. 2–12, 2011.
[17]  T. K. Bera, S. K. Biswas, K. Rajan, and J. Nagaraju, “Improving conductivity image quality using block matrix-based multiple regularization (BMMR) technique in EIT: a simulation study,” Journal of Electrical Bioimpedance, vol. 2, pp. 33–47, 2011.
[18]  J. N. Reddy, An Introduction to the Finite Element Method, TATA McGraw-Hill Publishing Company Ltd., New Delhi, India, 3rd edition, 2006.
[19]  T. J. Yorkey, Comparing reconstruction methods for electrical impedance tomography [Ph.D. thesis], University of Wisconsin at Madison, Madison, Wis, USA, 1986.
[20]  Vauhkonen Marko Electrical Impedance Tomography and Prior Information, Kuopio University Publications, Natural and Environmental Sciences, 1997.
[21]  T. J. Yorkey, J. G. Webster, and W. J. Tompkins, “Comparing reconstruction algorithms for electrical impedance tomography,” IEEE Transactions on Biomedical Engineering, vol. 34, no. 11, pp. 843–852, 1987.
[22]  C. J. Grootveld, Measuring and modeling of concentrated settling suspensions using electrical impedance tomography [Ph.D. thesis], Delft University of Technology, Delft, The Netherlands, 1996.
[23]  B. M. Graham, Enhancements in Electrical Impedance Tomography (EIT) image reconstruction for 3D lung imaging [Ph.D. thesis], University of Ottawa, 2007.
[24]  M. C. Kim, K. Y. Kim, S. Kim, H. J. Lee, and Y. J. Lee, “Electrical impedance tomography technique for the visualization of the phase distribution in an annular tube,” Journal of Industrial and Engineering Chemistry, vol. 8, no. 2, pp. 168–172, 2002.
[25]  T. K. Bera, S. K. Biswas, K. Rajan, and J. Nagaraju, “Improving the image reconstruction in Electrical Impedance Tomography (EIT) with block matrix-based Multiple Regularization (BMMR): a practical phantom study,” in Proceedings of the IEEE World Congress on Information and Communication Technologies, pp. 1346–1351, Mumbai, India, 2011.
[26]  T. K. Bera, S. K. Biswas, K. Rajan, and J. Nagaraju, “Image reconstruction in Electrical Impedance Tomography (EIT) with projection error propagation-based regularization (PEPR): a practical phantom study,” in Advanced Computing, Networking and Security, vol. 7135 of Lecture Notes in Computer Science, pp. 95–105, Springer, 2012.
[27]  MATLAB: The Language of Technical Computing, Version R2010a, The MathWorks, Inc., Natick, Mass, USA, 2010.
[28]  J. Malmivuo and R. Plonsey, Bioelectromagnetism: Principles and Applications of Bioelectric and Biomagnetic Fields, chapter 26, section 26.2.1, Oxford University Press, New York, NY, USA, 1995.
[29]  T. K. Bera and J. Nagaraju, “Studying the resistivity imaging of chicken tissue phantoms with different current patterns in Electrical Impedance Tomography (EIT),” Measurement, vol. 45, pp. 663–682, 2012.
[30]  T. K. Bera and J. Nagaraju, “Studying the 2D resistivity reconstruction of stainless steel electrode phantoms using different current patterns of Electrical Impedance Tomography (EIT), biomedical engineering,” in Proceeding of the International Conference on Biomedical Engineering (ICBME '11), pp. 163–169, Narosa Publishing House, Manipal, India, 2011.
[31]  T. K. Bera and J. Nagaraju, “A FEM-based forward solver for studying the forward problem of Electrical Impedance Tomography (EIT) with a practical biological phantom,” in Proceedings of the IEEE International Advance Computing Conference (IACC '09), pp. 1375–1381, Patiala, India, March 2009.
[32]  T. K. Bera and J. Nagaraju, “A study of practical biological phantoms with simple instrumentation for Electrical Impedance Tomography (EIT),” in Proceedings of the IEEE Instrumentation and Measurement Technology Conference (I2MTC '09), pp. 511–516, Singapore, May 2009.
[33]  E. Kreyszig, Advanced Engineering Mathematics, chapter 18, section 18.2, John Wiley & Sons, 8th edition, 1999.
[34]  T. K. Bera and J. Nagaraju, “Studying the boundary data profile of a practical phantom for medical electrical impedance tomography with different electrode geometries,” in Proceedings of the World Congress on Medical Physics and Biomedical Engineering, IFMBE Proceedings 25/II, pp. 925–929, Munich, Germany, September 2009.
[35]  B. H. Brown and A. D. Segar, “The Sheffield data collection system,” Clinical Physics and Physiological Measurement, vol. 8, supplement A, pp. 91–97, 1987.
[36]  K. S. Cheng, S. J. Simske, D. Isaacson, J. C. Newell, and D. G. Gisser, “Errors due to measuring voltage on current-carrying electrodes in electric current computed tomography,” IEEE Transactions on Biomedical Engineering, vol. 37, no. 1, pp. 60–65, 1990.
[37]  N. Polydorides and 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, vol. 13, no. 12, pp. 1871–1883, 2002.
[38]  M. Vauhkonen, W. R. B. Lionheart, L. M. Heikkinen, P. J. Vauhkonen, and J. P. Kaipio, “A MATLAB package for the EIDORS project to reconstruct two-dimensional EIT images,” Physiological Measurement, vol. 22, no. 1, pp. 107–111, 2001.
[39]  M. Kuzuoplu, M. Moh'dSaid, and Y. Z. Ider, “Analysis of three-dimensional software EIT (electrical impedance tomography) phantoms by the finite element method,” Clinical Physics and Physiological Measurement, vol. 13, supplement A, pp. 135–138, 1992.
[40]  R. P. Patterson and J. Zhang, “Evaluation of an EIT reconstruction algorithm using finite difference human thorax models as phantoms,” Physiological Measurement, vol. 24, no. 2, pp. 467–475, 2003.
[41]  R. Davalos and B. Rubinsky, “Electrical impedance tomography of cell viability in tissue with application to cryosurgery,” Journal of Biomechanical Engineering, vol. 126, no. 2, pp. 305–309, 2004.

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