The goal in electrical impedance tomography is to obtain the electrical properties of different materials by applying an electricalcurrent and measuring the resulting potential difference at the boundaries of the domain. While the numerical accuracy is technicallylimited by the size of the elements within the finite-element (FE) mesh, using a fine mesh will result in a computationally demandingreconstruction, especially when the region of interest (ROI) is not known. However, this situation is different when the location isknown, when one can easily refine the FE model around the target, aiming for greater accuracy around the ROI. In this paper,an innovative approach estimates the location of the target object before solving the inverse problem, so that it becomes possible torefine only a specific area of the FE model. A powerful artificial intelligence method is used to obtain this region.
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