正则化一步动态重建算法在磁感应成像中的应用

磁感应成像是对生物组织的电导率进行图像重建的一种方法,高斯牛顿方法通过不断迭代并重新计算灵敏度矩阵进行非线性图像重建,精度高但耗时较长.结合正则化技术,提出高斯牛顿一步动态重建算法,通过实验获得了相关参数的最优解.基于正问题的数学模型,建立磁感应成像测量模型,利用有限元方法求解,所得到的灵敏度矩阵和磁矢势应用于逆问题中...

Regularized One-Step Dynamic Image Reconstruction in Magnetic Induction Tomography

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.