Tikhonov regularization and prior information in electrical impedance tomography

1998 ◽  
Vol 17 (2) ◽  
pp. 285-293 ◽  
Author(s):  
M. Vauhkonen ◽  
D. Vadasz ◽  
P.A. Karjalainen ◽  
E. Somersalo ◽  
J.P. Kaipio
Keyword(s):  
Electrical Impedance Tomography ◽  
Tikhonov Regularization ◽  
Electrical Impedance ◽  
Prior Information ◽  
Impedance Tomography

scholarly journals Detection of Outdated Structural Priors in the Discrete Cosine Transformation-based Electrical Impedance Tomography Algorithm

2021 ◽  
Vol 7 (2) ◽  
pp. 676-679
Author(s):  
Rongqing Chen ◽  
Knut Moeller
Keyword(s):  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Prior Information ◽  
Simulated Data ◽  
Treatment Decision ◽  
Simulation Models ◽  
Discrete Cosine Transformation ◽  
Impedance Tomography ◽  
Cosine Transformation ◽  
Structural Prior

Abstract Morphological prior information incorporated with the discrete cosine transformation (DCT) based electrical impedance tomography (EIT) algorithm can improve the interpretability of EIT reconstructions in clinical applications. However, an outdated structural prior can yield a misleading reconstruction compromising the accuracy of the clinical diagnosis and the appropriate treatment decision. In this contribution, we propose a redistribution index scaled between 0 and 1 to quantify the possible error in a DCT-based EIT reconstruction influenced by structural prior information. Two simulation models of different tissue atelectasis and collapsed ratios were investigated. Outdated and updated structural prior information were applied to obtain different EIT reconstructions using this simulated data, with which the redistribution index was calculated and compared. When the difference between prior and reality (the redistribution index) became larger and exceeded a threshold, this was considered as an indicator of an outdated prior information. The evaluation result shows the potential of the redistribution index to detect outdated prior information in a DCT-based EIT algorithm.

A COMBINED REGULARIZATION ALGORITHM FOR ELECTRICAL IMPEDANCE TOMOGRAPHY SYSTEM USING RECTANGULAR ELECTRODES ARRAY

2012 ◽  
Vol 24 (04) ◽  
pp. 313-322 ◽  
Author(s):  
Wei He ◽  
Bing Li ◽  
Zheng Xu ◽  
Haijun Luo ◽  
Peng Ran
Keyword(s):  
Inverse Problem ◽  
Electrical Impedance Tomography ◽  
Tikhonov Regularization ◽  
Electrical Impedance ◽  
Regularization Parameter ◽  
Impedance Tomography ◽  
Regularization Algorithm ◽  
Tomography System ◽  
One Step ◽  
Mean Square Distance

A novel Electrical Impedance Tomography system with rectangular electrodes array and back electrode is proposed. This system could reconstruct a deeper target and is easy to operate. By studying different reconstructed algorithms: Tikhonov regularization and the Newton's One-step Error Reconstructor (NOSER), a combined regularization algorithm is proposed. The L-curve and posteriori method are used to choose Tikhonov and NOSER regularization parameter. Two evaluation parameters of reconstructed algorithm: normalization mean square distance criterion (NMSD), normalized mean absolute distance criterion (NMAD) are used to evaluate the result's precision of inverse problem quantificationally. The comparison among Tikhonov regularization, NOSER and the combined regularization shows that the ill-condition and the error of inverse problem are reduced. This new algorithm can decrease condition number by 70%, NMSD by 51%, and NMAD by 41% at least. Simulate results show that the combined regularization algorithm could reconstructed the target image in the depth from 10–40 mm. The experimental results show that a 15 mm × 9 mm × 9 mm cuboids whose depth is 35 mm could be distinguished. The performance of this system and the combined regularization algorithm demonstrate significantly better spatial resolution and minor reconstructed error.

Sign in / Sign up

Export Citation Format

Share Document