Research On Brain Electrical Characteristics And Function Imaging Based On EIT Technique

Brain research is very important subject to life science in the 21st century. The electrical characteristic of brain tissue is a basis for analyzing brain electrical and magnetic active and clinical diagnosis. Electrical impedance tomography (EIT) is a new type of technique with the feature of harmless, non-invasive and convenience, developed in recent years. In this paper, combining the technique with electromagnetic forward problem and inverse problem, the author has studied the numerical computation methods, hardware and software design of EIT system, reconstruction algorithm and brain electrical characteristic. The main research work is following:1. Development of the software package of EIT systemThe forward and inverse problems of EIT system have been analyzed and the software package has been developed based on Matlab and Fortran. This software can be used to construct automatically 16 electrodes and 32 electrical electrodes finite element method (FEM) division model. The equi-potential lines in any drive pattern can be plotted and the boundary potential changes in its forward problem can be obtained. Using back projection method, the impedance imaging in simulation and real measurement can be reconstructed.2. Study on brain electrical characteristics for two dimentional (2D) real head modelsThe brain electrical characteristics have been analyzed for 2D four layers concentric sphere head model, axial real and sagittal real head models from MRI pictures. The equi-potential lines can be gotten in different drive patterns and it shows that the sensitivity for the resolution region, especially the center region in opposite drive pattern is more than others because the head bone has very low conductivity. The potential distributions change with conductivity increase and reduce within head. And the change is the biggest when the bone conductivity changes.3. Computing brain resistivity parameters by using the wavelet neural network methodThe EIT inverse resolution is a non-linear mapping problem. Here it is presented that the brain resistivity parameters is computed by using the wavelet neural network method. Not only can it resolve non-linear mapping problem, but also overcome the shortage of non-convergence and expending long CPU time in other reconstruction algorisms.4. Research of the testing system for BIT and the reconstruction of impedance imagingA hardware system for EIT technique was made in this paper and the physical model with 16 electrodes was obtained. Real time collection, process for data and imaging reconstruction are done by a computer. The affection on sensitivity by differential drive patterns is analyzed. And the test for consistency of testing channels shows that the characteristics of every testing channel of the system are identical generally. Good impedance imaging reconstruction can be gotten for models with various shapes and differential conductivity. The system has stable, real time, convenient and extended features.