Regular Article: A Shape Decomposition Technique in Electrical Impedance Tomography

Consider a two-dimensional domain containing a medium with unit electrical conductivity and one or more non-conducting objects. The problem considered here is that of identifying shape and position of the objects on the sole basis of measurements on the external boundary of the domain. An iterative technique is presented in which a sequence of solutions of the direct problem is generated by a boundary element method on the basis of assumed positions and shapes of the objects. The key new aspect of the approach is that the boundary of each object is represented in terms of Fourier coefficients rather than a point-wise discretization. These Fourier coefficients generate the fundamental ''shapes'' mentioned in the title in terms of which the object shape is decomposed. The iterative procedure consists in the successive updating of the Fourier coefficients at every step by means of the Levenberg-Marquardt algorithm. It is shown that the Fourier decomposition-which, essentially, amounts to a form of image compression-enables the algorithm to image the embedded objects with unprecedented accuracy and clarity. In a separate paper, the method has also been extended to three dimensions with equally good results.

[1]  C. Boulay,et al.  An experimental study in electrical impedance tomography using backprojection reconstruction , 1991, IEEE Transactions on Biomedical Engineering.

[2]  Brian H. Brown,et al.  Imaging spatial distributions of resistivity using applied potential tomography , 1983 .

[3]  D. Isaacson,et al.  Electrode models for electric current computed tomography , 1989, IEEE Transactions on Biomedical Engineering.

[4]  M. A. Jaswon,et al.  Integral equation methods in potential theory and elastostatics , 1977 .

[5]  Kevin Paulson,et al.  Electrode modelling in electrical impedance tomography , 1992 .

[6]  Boundary element iterative techniques for determining the interface boundary between two Laplace domains—a basic study of impedance plethysmography as an inverse problem , 1986 .

[7]  Steven L. Ceccio,et al.  A review of electrical impedance techniques for the measurement of multiphase flows , 1991 .

[8]  Willis J. Tompkins,et al.  Comparing Reconstruction Algorithms for Electrical Impedance Tomography , 1987, IEEE Transactions on Biomedical Engineering.

[9]  Tadakuni Murai,et al.  Electrical Impedance Computed Tomography Based on a Finite Element Model , 1985, IEEE Transactions on Biomedical Engineering.

[10]  Steven L. Ceccio,et al.  Validation of Electrical-Impedance Tomography for Measurements of Material Distribution in Two-Phase Flows , 2000 .

[11]  F. J. Dickin,et al.  Determination of composition and motion of multicomponent mixtures in process vessels using electrical impedance tomography-I. Principles and process engineering applications , 1993 .

[12]  Michael Vogelius,et al.  A backprojection algorithm for electrical impedance imaging , 1990 .

[13]  D. Mewes,et al.  Multielectrode capacitance sensors for the visualization of transient two-phase flows , 1997 .

[14]  C. Pozrikidis Boundary Integral and Singularity Methods for Linearized Viscous Flow: Index , 1992 .

[15]  Ramani Duraiswami,et al.  Boundary element techniques for efficient 2-D and 3-D electrical impedance tomography , 1997 .