Studying the resistivity imaging of chicken tissue phantoms with different current patterns in Electrical Impedance Tomography (EIT)

A current injection pattern in Electrical Impedance Tomography (EIT) has its own current distribution profile within the domain under test. Hence, different current patterns have different sensitivity, spatial resolution and distinguishability. Image reconstruction studies with practical phantoms are essential to assess the performance of EIT systems for their validation, calibration and comparison purposes. Impedance imaging of real tissue phantoms with different current injection methods is also essential for better assessment of the biomedical EIT systems. Chicken tissue paste phantoms and chicken tissue block phantoms are developed and the resistivity image reconstruction is studied with different current injection methods. A 16-electrode array is placed inside the phantom tank and the tank is filled with chicken muscle tissue paste or chicken tissue blocks as the background mediums. Chicken fat tissue, chicken bone, air hole and nylon cylinders are used as the inhomogeneity to obtained different phantom configurations. A low magnitude low frequency constant sinusoidal current is injected at the phantom boundary with opposite and neighboring current patterns and the boundary potentials are measured. Resistivity images are reconstructed from the boundary data using EIDORS and the reconstructed images are analyzed with the contrast parameters calculated from their elemental resistivity profiles. Results show that the resistivity profiles of all the phantom domains are successfully reconstructed with a proper background resistivity and high inhomogeneity resistivity for both the current injection methods. Reconstructed images show that, for all the chicken tissue phantoms, the inhomogeneities are suitably reconstructed with both the current injection protocols though the chicken tissue block phantom and opposite method are found more suitable. It is observed that the boundary potentials of the chicken tissue block phantoms are higher than the chicken tissue paste phantom. SNR of the chicken tissue block phantoms are found comparatively more and hence the chicken tissue block phantom is found more suitable for its lower noise performance. The background noise is found less in opposite method for all the phantom configurations which yields the better resistivity images with high PCR and COC and proper IRMean and IRMax neighboring method showed higher noise level for both the chicken tissue paste phantoms and chicken tissue block phantoms with all the inhomogeneities. Opposite method is found more suitable for both the chicken tissue phantoms, and also, chicken tissue block phantoms are found more suitable compared to the chicken tissue paste phantom. (C) 2012 Elsevier Ltd. All rights reserved.

[1]  D S Holder,et al.  Some practical biological phantoms for calibrating multifrequency electrical impedance tomography. , 1996, Physiological measurement.

[2]  Tushar Kanti Bera,et al.  A study of practical biological phantoms with simple instrumentation for Electrical Impedance Tomography (EIT) , 2009, 2009 IEEE Instrumentation and Measurement Technology Conference.

[3]  Philippe Renaud,et al.  Cell Culture Imaging Using Microimpedance Tomography , 2008, IEEE Transactions on Biomedical Engineering.

[4]  Tushar Kanti Bera,et al.  Resistivity imaging of a reconfigurable phantom with circular inhomogeneities in 2D-electrical impedance tomography , 2011 .

[5]  Tushar Kanti Bera,et al.  Gold electrode sensors for electrical impedance tomography (EIT) studies , 2011, 2011 IEEE Sensors Applications Symposium.

[6]  Robert Plonsey,et al.  Bioelectromagnetism: Principles and Applications of Bioelectric and Biomagnetic Fields , 1995 .

[7]  L M Heikkinen,et al.  A MATLAB package for the EIDORS project to reconstruct two-dimensional EIT images. , 2001, Physiological measurement.

[8]  T. Bera,et al.  Studying the Elemental Resistivity Profile of Electrical Impedance Tomography (EIT) Images to Assess the Reconstructed Image Quality , 2011 .

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

[10]  Tushar Kanti Bera,et al.  A FEM-Based Forward Solver for Studying the Forward Problem of Electrical Impedance Tomography (EIT) with A Practical Biological Phantom , 2009, 2009 IEEE International Advance Computing Conference.

[11]  Tushar Kanti Bera,et al.  A Simple instrumentation calibration technique for Electrical Impedance Tomography (EIT) using a 16-electrode phantom , 2009, 2009 IEEE International Conference on Automation Science and Engineering.

[12]  David S. Holder,et al.  Clinical and physiological applications of electrical impedance tomography , 1993 .

[13]  D. Isaacson,et al.  Errors due to measuring voltage on current-carrying electrodes in electric current computed tomography , 1990, IEEE Transactions on Biomedical Engineering.

[14]  Tushar Kanti Bera,et al.  Improving Image Quality in Electrical Impedance Tomography (EIT) Using Projection Error Propagation-Based Regularization (PEPR) Technique: A Simulation Study , 2011 .

[15]  William R B Lionheart,et al.  A Matlab toolkit for three-dimensional electrical impedance tomography: a contribution to the Electrical Impedance and Diffuse Optical Reconstruction Software project , 2002 .

[16]  R H Bayford,et al.  Bioimpedance tomography (electrical impedance tomography). , 2006, Annual review of biomedical engineering.

[17]  Mi Wang,et al.  Electrical resistance tomography for process applications , 1996 .

[18]  David Barber,et al.  Three dimensional electrical impedance tomography of the human thorax , 1996, Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[19]  J. Boone,et al.  Comprar Essential Physics Of Medical Imaging, International Edition | Jerrold T. Bushberg | 9781451118100 | Lippincott Williams & Wilkins , 2012 .

[20]  C. J. Kotre,et al.  Subsurface electrical impedance imaging: measurement strategy, image reconstruction and in vivo results. , 1996, Physiological measurement.

[21]  Denyer Cwl.  Electronics for real-time and three-dimensional electrical impedance tomographs. , 1996 .

[22]  William R B Lionheart.  EIT reconstruction algorithms: pitfalls, challenges and recent developments. , 2004, Physiological measurement.

[23]  J. Newell,et al.  Current topics in impedance imaging. , 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.

[24]  Tushar Kanti Bera,et al.  Studying the Boundary Data Profile of a Practical Phantom for Medical Electrical Impedance Tomography with Different Electrode Geometries , 2009 .

[25]  David S. Holder,et al.  Electrical Impedance Tomography : Methods, History and Applications , 2004 .

[26]  D S Holder,et al.  An electrode addressing protocol for imaging brain function with electrical impedance tomography using a 16-channel semi-parallel system , 2009, Physiological measurement.

[27]  G Malandain,et al.  Model-based respiratory motion compensation for emission tomography image reconstruction , 2007, Physics in medicine and biology.

[28]  B H Brown,et al.  The Sheffield data collection system. , 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.

[29]  J. Bushberg.  The Essential Physics of Medical Imaging , 2001 .

[30]  Tushar Kanti Bera,et al.  Improving Conductivity Image Quality Using Block Matrix-based Multiple Regularization (BMMR) Technique in EIT: A Simulation Study , 2011 .