An image reconstruction algorithm based on L(P)-norm for magnetic induction tomography.
- Author:
Yuyan CHEN
1
;
Xu WANG
;
Dan YANG
;
Yi LU
Author Information
1. College of Information Science and Engineering, Northeastern University, Shenyang 110004, China. joy_chen77@sohu.com
- Publication Type:Journal Article
- MeSH:
Algorithms;
Image Processing, Computer-Assisted;
methods;
Magnetics;
Models, Theoretical;
Tomography;
methods
- From:
Journal of Biomedical Engineering
2013;30(1):162-165
- CountryChina
- Language:Chinese
-
Abstract:
Magnetic induction tomography (MIT) image reconstruction is a typical ill-posed problem, and its numerical solution is unstable. A new image reconstruction algorithm based on the L(P)-norm, which solves the ill-posed inverse problem of MIT and improves the quality of reconstructed image, is presented in this paper. The new algorithm not only overcomes the problem of numerical instability of the MIT image reconstruction, but also improves the quality of the reconstructed image and enhances the spatial resolution of the reconstructed image. Simulation results showed that the quality of the reconstructed image obtained using the presented algorithm was better than that using Tikhonov regularization algorithm and that using the variation regularization algorithm, so it could be an effective method for the MIT.
