Computation of a 3-D Model for Lung Imaging With Electrical Impedance Tomography

The electrical impedance tomography (EIT) has been developed and evolved over the past 30 years, which has the great potential for clinical diagnosis in lung imaging and detection of thorax ventilation; however, EIT possesses the difficult problems in terms of developing hardware for data acquisition and the image reconstruction. In this paper, a cylinder geometry 3-D model for human thorax has been constructed with finite element method (FEM). A nodal-based total variation regularization algorithm has been evaluated with phantom tests which have been implemented by our EIT system in a salt-water tank. The in vivo experiments on the subject have been carried out, and then the lung images have been reconstructed during breath with the nodal total variation regularization algorithm. The result shows that the resistivity distribution of the lung is well reconstructed with the 3-D model and gives high contrast images. It also verifies that the nodal total variation regularization algorithm has the potential capability to become a useful algorithm for lung imaging with EIT.