Carlos F Tolmasky and Andreas Wiegmann 1999 Inverse Problems 15 465 doi:10.1088/0266-5611/15/2/008
Carlos F Tolmasky
and Andreas Wiegmann![]()
Electrical impedance tomography (EIT) is used to find the conductivity distribution inside a region using electrostatic measurements collected on the boundary of the region. We study a simple version of the general EIT problem, in which the medium has constant conductivity but might contain a buried object of unknown shape and different, but also constant, conductivity.
Our linearization about an approximate shape of the buried object follows Kaup and Santosa and has the advantage that it is valid for large contrast in the conductivity. We present a procedure to reconstruct the object boundary in the case where we know the conductivities and the centre and radius of a good circular approximation of the object boundary, using analytic solutions to the forward problem for circular objects with known conductivity. Assuming that the unknown object boundary is star-shaped with respect to the centre of the circle and a small perturbation of the approximating circle, we develop a linearized relation between the output voltage data that result from fixed input currents, entering as parameters, and the interface, entering as variables. This relation is used to find the Fourier coefficients of the perturbation of the interface.
At least two measurements are needed to determine all coefficients, and more can be used for a least-squares fit. The quality of the recovered perturbation depends on the input frequency and the frequencies of the perturbation. Low frequencies work best as input, and are most easily recovered, in that case even where the amplitude of the perturbation is not very small. Several dipoles, corresponding to very close pairs of electrodes to induce the current, can be used successfully as input as well.
02.60.Lj Ordinary and partial differential equations; boundary value problems
35R30 Inverse problems (undetermined coefficients, etc.) for PDE
92C55 Biomedical imaging and signal processing (See also 44A12, 65R10)
Issue 2 (April 1999)
Carlos F Tolmasky and Andreas Wiegmann 1999 Inverse Problems 15 465
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