scholarly journals Multifrequency electrical impedance tomography with total variation regularization

2015 ◽  
Vol 36 (9) ◽  
pp. 1943-1961 ◽  
Author(s):  
Zhou Zhou ◽  
Thomas Dowrick ◽  
Emma Malone ◽  
James Avery ◽  
Nan Li ◽  
...  
Keyword(s):  
Total Variation ◽  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Total Variation Regularization ◽  
Impedance Tomography

scholarly journals Comparison of total variation algorithms for electrical impedance tomography

2015 ◽  
Vol 36 (6) ◽  
pp. 1193-1209 ◽  
Author(s):  
Zhou Zhou ◽  
Gustavo Sato dos Santos ◽  
Thomas Dowrick ◽  
James Avery ◽  
Zhaolin Sun ◽  
...  
Keyword(s):  
Total Variation ◽  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Impedance Tomography

Experimental evaluation of 3D electrical impedance tomography with total variation prior

2015 ◽  
Vol 24 (8) ◽  
pp. 1411-1431 ◽  
Author(s):  
G. González ◽  
J. M. J. Huttunen ◽  
V. Kolehmainen ◽  
A. Seppänen ◽  
M. Vauhkonen
Keyword(s):  
Total Variation ◽  
Electrical Impedance Tomography ◽  
Experimental Evaluation ◽  
Electrical Impedance ◽  
Impedance Tomography

Statistical inversion in electrical impedance tomography using mixed total variation and non-convex ℓp regularization prior

2015 ◽  
Vol 23 (5) ◽  
Author(s):  
Thilo Strauss ◽  
Taufiquar Khan
Keyword(s):  
Inverse Problem ◽  
Total Variation ◽  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Bayesian Framework ◽  
Electromagnetic Properties ◽  
Impedance Tomography ◽  
Conductivity Distribution ◽  
Ill Posed

AbstractElectrical impedance tomography (EIT) is a well-known technique to estimate the conductivity distribution γ of a body Ω with unknown electromagnetic properties. EIT is a severely ill-posed inverse problem. In this paper, we formulate the EIT problem in the Bayesian framework using mixed total variation (TV) and non-convex ℓ

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