Electrical capacitance tomography: image reconstruction along electrical field lines

Abstract

For image reconstruction in electrical capacitance tomography (ECT) various implementations of the linear backprojection (LBP) algorithm and iterative reconstruction techniques have become the standard in most applications. Most implementations suffer from a smoothing effect and lack of accuracy due to their smooth sensitivity maps and the so-called 'soft' field problem in ECT, respectively. Therefore it is usually difficult in capacitance tomography to reconstruct objects with sharp contours. In the present paper a novel reconstruction model based on a finite-element-method (FEM) calculation is introduced. The model is derived directly from linear (x-ray) tomography, wherein weighting matrices along the rays are calculated. By analogy, weighting matrices in ECT are calculated numerically along the paths of the electrical field lines, which are influenced by the distribution of the various permittivities in the measurement plane. Finally the image reconstruction is done by implementing these new weighting matrices within standard iteration techniques (ART and LBP). With the new algorithm even objects with sharp contours can be reconstructed. The results are more detailed and accurate tomograms.

Use of X-ray Tomography to Map Crystalline and Amorphous Phases in Frozen Biomaterials

“…are applied both in medical and in industrial applications. 21,22,32 All imaging for this study was performed with an X-ray computer tomography (CT) device at the Institute of Process Engineering at the University of Hannover, Germany. The CT, which can be broadly used for both biomedical and industrial applications, was manufactured by Bio-Imaging Research, Inc. (BIR, Lincolnshire, IL).…”

In-Situ Real Time Monitoring and Control of Mold Making and Filling Processes: Final Report

“…The softfiled nature of the ECT sensor imposes a critical challenge in calculating the solution of the inverse problem. The soft-filed nature means that the electric field distribution inside the imaging area is non-linearly dependent on the property distribution (Isaksen 1996, Loser et al 2001. The ill-posed characteristic of the inverse problem and hence the ill-conditioned of the discrete form is another major challenge associated with the inverse problem .…”

“…However the entire performance of the reconstruction process is mainly dependent on the solution of the forward problem; it has less attention from researchers compared by the inverse problem solution. Three methods have been used to solve the forward problem: 1) linearization methods (Huang et al 1989), 2) analytical methods (Munck et al 2000), and numerical methods such as finite difference method , finite element method (Loser et al 2001), and boundary value method , Yang 1999). Large computational time and limit resources are the main problems associated with the numerical methods, while the analytical methods usually work with symmetric sensor structures.…”

A Novel Image Reconstruction Algorithm based on Population Entropy and Adaptive Differential Evolution for Electrical Capacitance Tomography

“…It also has many advantages, such as simple structure, low cost, non-contact measurement etc. It is widely used in the industrial process of multiphase nondestructive testing [1][2].…”