Solving an inverse problem constitutes one of the most challenging tasks in electrical impedance tomography because of the mathematical complexity of the subject. The most commonly used methods include the finite element and boundary element methods. Both are mathematically involved procedures which are rarely taught at undergraduate level. An alternative approach based on a network of resistors is also useful for this type of inversion problem. This paper describes the use of resistance network analogues for electrical imaging. The algorithm is based on the modified Newton-Raphson method.
BarberD. C. and BrownB. H., ‘Applied potential tomography’, J. Phys. E. Sci. Instrum., 17, p. 273 (1984)
2.
HuaP., ‘Effect of the measurement method on noise handling and image quality of EIT imaging’, IEEE 9th Annual Conf. Engng. Med. Biol. Soc., p. 1429 (1987)
3.
YorkeyT. J. and WebsterJ. G.‘A comparison of impedance tomographic reconstruction algorithms’, Clin. Phys. Physiol. Meas., 8, Suppl. A, p. 55 (1987)
4.
YorkeyT. J.‘Electrical impedance tomography with piecewise polynomial conductivities’, J. Comp. Phys., 91/2, p. 344 (1990)
5.
RedshawS. C., ‘An electrical potential analyzer’, Proc. Inst. Mech. Engrs., 159, p. 55 (1948)
6.
LiebmannG., ‘Solution of partial differential equation with resistant network analogues’, Br. J. Appl. Phys., 5, p. 92 (1950)
7.
VidalJ. J., ‘Simulation of field problems using general purpose resistance network analogues’, Simulation, p. 190 (1966)
8.
SkillingH. H., Electric Networks, John Wiley & Sons (1974)
9.
SeagarA. D. and BrownB. H., ‘Limitations in hardware design in impedance imaging’, Clin. Phys. Physiol. Meas., 8, Suppl. A, p. 85 (1987)
10.
MohamedJ. L. and WalshJ., Numerical Algorithms, Oxford Science Publications, p. 10 (1986)
11.
GeselowitzD. B., ‘An application of electrocardiographic lead theory to impedance plethsmography’, IEEE Trans. Biomed. Engng., 18(1), p. 38 (1971)
12.
AbdullahM. Z., Electrical Impedance Tomography For Imaging Conducting Mixtures in Hydrocyclone Separators, PhD Thesis, University of Manchester Institute of Science and Technology, UK, p. 123 (1993)
13.
MaraquardtB. W., ‘An algorithm for least-square estimation of nonlinear parameters’, J. Appl. Math., 11, p. 432 (1963)
14.
HuaP., ‘Iterative reconstruction methods using regularization and optimal current patterns in electrical impedance tomography’, IEEE Trans. Biomed. Engng., 10(4), p. 621 (1991)
