Study on 3D Electrical Impedance Imaging of Pulmonary Respiration Based on Laplacian Regularization Algorithm

Electrical impedance tomography (EIT) is used to reconstruct the lung imaging for monitoring the pulmonary breath effectively. Due to the limits of two-dimensional imaging and inability to image the human body adequately, three-dimensional electrical impedance imaging technology was used to image the pulmonary respiration process in this paper. The 3D lung images were reconstructed by Laplacian regularization algorithm and Tikhonov regularization algorithm, then the Lung Regional Ratio (LRR) and the errors of image reconstruction results were evaluated. The results show that Laplacian regularization algorithm could reduce the error of three-dimensional lung EIT imaging by 2.195%, and Lung Regional Ratio (LRR) accuracy by 2.26%. It can be concluded that compared with Tikhonov regularization algorithm, Laplacian regularization algorithm is more suitable for 3D EIT image reconstruction, which proves the feasibility of 3D EIT for human respiratory movement monitoring.