Supershape Augmented Reconstruction Method Based on Boolean Operations in Electrical Impedance Tomography

This article presents a supershape augmented shape reconstruction algorithm for electrical impedance tomography, aiming at high-quality reconstructions with respect to multiphase conductivity distributions. Within the proposed algorithm, the reconstructed inclusions are composed of basic shape primitives expressed through a supershape formula. To allow automatic topological evolution, multiple Boolean operations, including three basic Boolean operations and compound Boolean operations, are employed so that the candidate shape primitives can be intersected, subtracted, and merged to form different shapes. The proposed algorithm is tested using simulations and water tank experimental data. Moreover, robustness studies considering varying initial guesses and differing signal-to-noise ratios are performed. It is demonstrated that the proposed algorithm is able to preserve detailed features of inclusions under detection and provide reliable estimates of unknown conductivity values and the interface properties.