IMPEDANCE IMAGE RECONSTRUCTION WITH ARTIFICIAL NEURAL NETWORK IN ELECTRICAL IMPEDANCE TOMOGRAPHY

Yıl 2019, , 137 - 144, 30.12.2019

Beyhan Kilic

https://doi.org/10.36222/ejt.650616

Cited By: 1

Öz

Electrical
impedance tomography views the electrical properties of the objects by
injecting current with surface electrodes and measuring voltages. Then using a
reconstructing algorithm, from the measured voltage-current values,
conductivity distribution of the object calculated. Finding internal
conductivity from surface voltage-current measurements is a reverse and
ill-posed problem.

Therefore,
high error sensitivity, and making approximations in conceiving complex
computations cause to limited spatial resolution. The classic iterative image
reconstruction algorithms have reconstruction errors. Accordingly, Electrical
impedance tomography images suffer low accuracy. It is necessary to evaluate
the collected data from the object surface with a new approach. In this paper,
the forward problem solved with the finite element method to reconstruct the
conductivity distribution inside the object, 
the reverse problem solved by the neural network approach. Image reconstruction
speed, conceptual simplicity, and ease of implementation maintained by  this approach.

Anahtar Kelimeler

: electrical impedance tomography, finite element methods, biomedical image reconstruction, neural network

Kaynakça

• [1] Adler, A., Guardo, R., (1994). A Neural Network Image Reconstruction Technique for Electrical Impedance Tomography. IEEE Transactions on Medical Imaging, 13(4).
• [2] Martin, S., Choi, C.T.M., Electrical Impedance Tomography: A Reconstruction Method Based on Neural Networks and Particle Swarm Optimization, Springer, Cham, Switzerland, 2015.
• [3] Khan, T.A., Ling, S.H., (2019). Review On Electrical Impedance Tomography. Artificial Intelligence Methods and its Applications Algorithms,12(5), 88, 1-18.
• [4] Webster, J. G., Electrical Impedance Tomography, Adam Hilger Series of Biomedical Engineering, Adam Hilger, New York, USA, 1990.
• [5] Hikmah, A. (2019). Two-Dimensional Electrical Impedance Tomography (EIT) For Characterization of Body Tissue Using a Gauss-Newton Algorithm, OP Conf. Series: Journal of Physics: Conf. Series, 1248
• [6] Miller, A., Blott, S., et al. (1992). Review of Neural Network Applications in Medical Imaging and Signal Processing. Medical and Biological Engineering and Comp., 30(5), 449–464
• [7] Malmivuo, J., Plonsey, R., Bioelectromagnetism Principles and Applications of Bioelectric and Biomagnetic Fields, Oxford Scholarship,1995.
• [8] Uhunmwangho, R., Ibo, A.O., Introduction To Electrical Engineering, Odus Press, 2017
• [9] Graham, B.M., Enhancements in Electrical Impedance Tomography (EIT) Image Reconstruction for Three-Dimensional Lung Imaging, Ph.D. thesis, University of Ottawa, 2007
• [10] Ankara Standard Data Set, European Community Concerned Action in Impedance Imaging, Image Reconstruction Meeting, Oxford, UK, 14-17, 1994
• [11] Pursiainen, S., Hakula, H., (2006). A High-order Finite Element Method for Electrical Impedance Tomography, Progress In Electromagnetics Research Symposium, Cambridge, 57-62.
• [12] Garnadi, A.D., (1997). Electrical Impedance Tomography Based on Mixed Finite Element Model, Proceedings CMSE'97, Bandung, 4, 6-7.
• [13] Woo, E.J., Hua, P., et al. (1994). Finite-Element Method in Electrical Impedance Tomography, Medical and Biological Engineering and Computing, 32(5), 530-536.
• [14] Irons, B.M., (1970) A Frontal Solution Program for Finite Element Analysis, International Journal for Numerical Methods in Engineering, 2, 25-32.
• [15] Ider,Y.Z., Gencer, N., et al. (1990). Electrical Impedance Tomography of translationally uniform cylindrical objects with general cross-sectional boundaries, IEEE Medical Imaging, 9(1), 49-59.
• [16] Ider, Y.Z., Nakiboğlu, B., et al. (1992). Determination of The Boundary of an Object Inserted Into a Water-filled Cylinder, Clinical Physics and Physiological Measurement 13(A), 151-154.
• [17] Kılıç, B., Elektrik Empedans Tomografisinde Sonlu Eleman Yöntemi ile Modelleme ve Görüntü Oluşturma Agoritmaları, Doktora Tezi (Ph.D. thesis), Yıldız Teknik Üniversitesi, 1998.