Abstract
Electrical impedance tomography (EIT) is an imaging modality that provides cross-sectional images of objects that carry contrasts in electrical conductivity. EIT is suitable for example for monitoring industrial processes involving multiple phases with different conductivities. This paper presents a parametric level set (PLS) based reconstruction scheme for an EIT-imaging of conductivity distributions within multiphase systems. The proposed scheme involves applying a multiphase level set model to solve the inverse problem of finding interfaces between the regions having different conductivity values and estimating the conductivities of phases. The unknown conductivity to be reconstructed is assumed to be piecewise constant while the interface between the regions are represented by the two PLS functions employing Gaussian radial basis functions (GRBF). The level set-based scheme handles topological merging and breaking naturally during the evolution process. It also offers several advantages compared to the traditional pixel-based approaches. For example, the representation of the PLS function by using GRBF provides flexibility in describing a large class of shapes with fewer unknowns. Numerical simulations and phantom experiments are performed to validate the proposed method.
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