DocumentCode :
1616345
Title :
MNR Method with Self-Determined Regularization Parameters for Solving Inverse Resistivity Problem
Author :
Ying Li ; Guizhi Xu ; Liyun Rao ; Renjie He ; Jianjun Zhang ; Weili Yan
Author_Institution :
Key Lab. of Electromagn. Field & Electr. Apparatus Reliability of Hebei Province, Hebei Univ. of Tech., Tianjin
fYear :
2006
Firstpage :
2652
Lastpage :
2655
Abstract :
The modified Newton-Raphson (MNR) method is used to solve the inverse resistivity problem in this paper. Using Tikhonov regularization method, comparisons among the L-curve method, the zero-crossing (ZC) method and the generalized cross validation (GCV) method are carried out for determining the regularization parameters of MNR method. By these criterions the appropriate regularization parameters are self-determined and adjusted with the reconstruction iterations. Our simulation experiments on 2D circle model showed that the GCV method can provide the best reconstruction quality with the fastest speed in inverse resistivity problem using MNR method
Keywords :
Newton-Raphson method; electric impedance imaging; image reconstruction; inverse problems; medical image processing; 2D circle model; L-curve method; MNR method; Tikhonov regularization method; electrical impedance tomography; generalized cross validation method; inverse resistivity problem; modified Newton-Raphson method; reconstruction iterations; self-determined regularization parameters; zero-crossing method; Conductivity; Current measurement; Electromagnetic fields; Helium; Impedance measurement; Laboratories; Laplace equations; Surface impedance; Tomography; Voltage;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
Conference_Location :
Shanghai
Print_ISBN :
0-7803-8741-4
Type :
conf
DOI :
10.1109/IEMBS.2005.1617015
Filename :
1617015
Link To Document :
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