Image Reconstruction of Electrical Impedance Tomography Based on Conv-olutional Neural Network
The image reconstruction of electrical impedance tomography is a highly nonlinear and ill-posed problem,and the traditional image reconstruction method loses important information,which means it cannot achieve high accuracy and real-time imaging.In this paper,an electrical impedance tomography image reconstruction method based on convolutional neural network structure LeNet-5 is proposed.MATLAB and COMSOL were used to obtain samples with dif-ferent representative imaging features,and these samples were divided into training set,valida-tion set and test set.The LeNet-5 network is used to learn the nonlinear relationship between the boundary measurement voltage and conductivity to reconstruct images.The reconstruction re-sults obtained by the network in this paper were compared with the results obtained by other machine learning methods(backpropagation and radial basis function neural networks)to verify the effectiveness of the network based on LeNet-5.
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