Electrical Impedance Imaging Algorithm

Electrical Impedance Tomography (EIT) is a new type of non-invasive medical imaging technology developed in recent years. In the biology, different tissues have different electric parameters, such as conductance and capacitivity. When a small altering current is injected to an object, corresponding voltages can be measured via some electrodes attached to the object. Using above data, an approximation for the internal impedance distribution can be obtained by some EIT imaging reconstruction algorithms.Through the electrode array distributed in the body's surface, EIT can extract the electrical potentials related to physiological information of tissue or organs. Using these electrical potentials, EIT can offer a functional image. Without using nuclide and radial, EIT is innocuous to human's bodies. So it can be used repeatedly. Having the merits of non-invasion, EIT have become one of the hot-button questions in the research fields of biomedical engineering.Currently, the main problem of EIT is that the collected data have poor information, which makes the reconstruction images have very low spatial resolution, or even the reconstruction process be extraordinary ill-conditioned. To solve these problems, an EIT imaging algorithm based on RBF artificial nerve network was proposed in this dissertation. First, we analyzed the target region using finite element method, and built the mathematical models to solve the problems of EIT. And then realized the EIT image reconstruction using artificial nerve network. Finally, enhanced EIT image quality via wavelet theory. Based on above ideas, this dissertation mainly studied the methods to solve the EIT problems using finite element theory, the electrical impedance tomography algorithm based on RBF neural network, and the factors affecting the...