Simulation Experiment of Physical Model of Electrical Impedance Scanning Imaging (PMEISI) Based on Bayesian Network Knowledge Synthesis Algorithm

摘要

In the simulation of traditional physical model of electrical impedance scanning imaging (PMEISI), a physical model of electrical impedance scanning imaging (PMEISI) based on Bayesian network knowledge synthesis algorithm is proposed. The physical model uses the threshold as a variable, combines the synthesis threshold, and depends on the maximum between-class variance and the maximum peak signal to noise ratio (PSNR) criteria to establish a PMEISI and take into account the accuracy and noise immunity of the Bayesian network knowledge synthesis algorithm; in order to avoid the increase of the threshold affecting the efficiency of the algorithm, the Bayesian network knowledge synthesis algorithm is introduced into the physical model. Experiments show that the physical model has the advantages of accurate synthesis, strong noise immunity, good robustness, and more universality for the electrical impedance scanning imaging with different noises.