Research On Biological Electrical Impedance Tomography

Biological electrical impedance tomography ( BEIT ) is a new non-invasive functional imaging technology. The principle of BEIT is that different tissues and organs have different electrical impedance properties in different physiological or pathological conditions. A set of electrodes are positioned around the periphery of the body with low amplitude safe currents being applied into the body through a pair of electrodes, and the resulting voltages on the other electrodes are subsequently collected. Based on the measured data, the internal conductivity distribution and its change can be estimated. Therefore, the electrical properties related to different physiological or pathological conditions can be explored. BEIT has the advantages of non-radiation, safe, non-invasive, low cost, portability, and visualization, etc. It can be used for continuous dynamic monitoring at bedside. The research work is focused on EIT technique applied for lung ventilation monitoring.1. Image reconstruction methods are studied. In order to improve the accuracy of reconstructed image, stability of the reconstruction, and the imaging speed, respectively, different methods are introduced based on the generalized Tikhononv regularization. The maximum entropy regularization method can effectively reduce the artefacts of reconstructed images and improve the accuracy. By incorporating prior information into Tikhonov regularization matrix, the differentiability and quality of the lung are improved. The hybrid method can overcome the phenomenon of slow convergence or semi-convergence in single-iteration algorithms and enhance the stability. Pre-conditioned hybrid method can further improve the algorithm in real time without losing accuracy and stability.2. To obtain the information of three-dimensional (3D) spatial distribution, 3D electrode structure and drive pattern are investigated. Two different structures of electrode array are proposed and four drive patterns are compared. Moreover, a new image reconstruction algorithm is put forward for 3D image reconstruction, in order to ensure the real-time property, accuracy and stability.3. The experiments for monitoring lung ventilation are carried out based on the digital system of MEIT_TJU. Measuremed data and corresponding image sequences of reconstruction are analysed to explore effective information.4. 3D human thorax models are established for simulation. Based on CT images of human thorax, true 3D thorax models with conductivity distribution or complex conductivity distribution under different ARDS conditions are built up in comparison with the 2.5D ones, and EIT-derived numeric indices are also employed for evaluation of the lung ventilation. The purpose of the research is to study different effects of different thorax models with either conductivity or complex conductivity on the reconstructed images and ventilation indices.