Two New Detection Field Partitioning Methods for Electrical Impedance Tomography Based on Intersection Line Model

Electrical Impedance Tomography (EIT) is a powerful technique for reconstructing internal electrical parameter distributions within a detection field. The partitioning of the detection field plays a crucial role in the quality of the EIT imaging. However, existing partitioning methods often fail to fully utilize the available measurements, leading to suboptimal imaging results. In this paper, two novel detection field partitioning models are proposed, incorporating both direct lines and current flow curves among all electrodes. These models aim to improve the efficiency of the measurement data usage. Based on the proposed partitioning methods, the sensitivity matrices are reconstructed, and experimental results demonstrate the superior imaging quality and stability of the models, particularly in fields with high-contrast and complex conductivity distributions. These findings provide a new approach to enhance the practical application of EIT.