Magnetic induction tomography (MIT) is an imaging method for reconstructing the electrical conductivity of biological tissues.Gauss-Newton method aims at nonlinear reconstruction by iterating continuously and re-calculating sensitivity matrix

which has a high precision but is time-consuming.Gauss-Newton one-step dynamic algorithm in combination with regularization technique was proposed and used to experiment for obtaining optimized solutions of relative parameters.MIT measurement model based on forward mathematical model is set up and solved by the finite element method.The obtained sensitivity matrix and magnetic vector potential are applied in the inverse problem and the method presented in the paper realized the reconstruction of the absolute conductivity.Uncorrelated Gaussian noise with different signal-noise-ratio (SNR) is added in the measurement voltage to simulate the real measurement value and the simulated results are compared.The results prove that the algorithm in the paper gets better effect in precision and speed than others.