Image reconstruction in electrical impedance tomography based on genetic algorithm.
- Author:
Weidong HOU
1
;
Yulong MO
Author Information
1. Department of Communication Engineering, Shanghai University, Shanghai 200072.
- Publication Type:Journal Article
- MeSH:
Algorithms;
Electric Impedance;
Image Processing, Computer-Assisted;
methods;
Nonlinear Dynamics;
Tomography;
methods
- From:
Journal of Biomedical Engineering
2003;20(1):107-110
- CountryChina
- Language:Chinese
-
Abstract:
Image reconstruction in electrical impedance tomography (EIT) is a highly ill-posed, non-linear inverse problem. The modified Newton-Raphson (MNR) iteration algorithm is deduced from the strictest theoretic analysis. It is an optimization algorithm based on minimizing the object function. The MNR algorithm with regularization technique is usually not stable, due to the serious image reconstruction model error and measurement noise. So the reconstruction precision is not high when used in static EIT. A new static image reconstruction method for EIT based on genetic algorithm (GA-EIT) is proposed in this paper. The experimental results indicate that the performance (including stability, the precision and space resolution in reconstructing the static EIT image) of the GA-EIT algorithm is better than that of the MNR algorithm.
