Modified newton-raphson method using a region of interest in electrical impedance tomography

Kim, Chan-Yong; Kang, Jeong-Min; Kim, Jihoon; Choi, Bong-Yeol; Kim, Kyung-Youn

doi:10.3938/jkps.61.1199

Cited by 10 publications

(7 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The CEM mathematical model is defined as Eqs. (1)- (5). This model includes an elliptic partial differential equation and some mixed boundary conditions.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Electrical Impedance Tomography Based on a High-resolution Direction-of-arrival Estimation Algorithm

Wen¹,

Wei²,

Xue³

2020

Sensors and Materials

View full text Add to dashboard Cite

The combination of artificial intelligence and medical imaging technology is profoundly affecting the development of medical imaging technology. Electrical impedance tomography (EIT) is a noninvasive imaging technology for estimating the internal impedance distribution of a body and is becoming a promising technology. In this paper, we focus on improving the EIT resolution by incorporating the direction-of-arrival (DOA) theory into the EIT model and use the DOA estimation algorithm to solve the inverse problem of EIT. The m-Capon algorithm proposed in this paper is based on a beamforming framework, there is no need to estimate the model order from the covariance matrix, and high resolution is obtained. The algorithms are simulated on the eidors platform of MATLAB. We use a resolution function, an image reconstruction quality function, and a correlation function as image evaluation functions. We compare the m-Capon algorithm with the back-projection (BP) algorithm, the Gauss-Newton (GN) algorithm, and a multiple signal classification (MUSIC)-like algorithm under different EIT models and signal-to-noise ratios (SNRs). Simulation results show that the EIT technology based on the DOA estimation algorithm used in this study is feasible, and the m-Capon imaging algorithm proposed in this paper gives higher resolution, stronger anti-jamming ability, and higher image quality than the other algorithms.

show abstract

“…The CEM mathematical model is defined as Eqs. (1)- (5). This model includes an elliptic partial differential equation and some mixed boundary conditions.…”

Section: Methodsmentioning

confidence: 99%

“…One of the main challenges is that the EIT reconstruction process is a typical nonlinear and ill-posed inverse problem. Traditional reconstruction algorithms are the back-projection (BP) algorithm, (3) Gauss-Newton (GN) algorithm, (4) modified Newton-Raphson (MNR) algorithm, (5) Tikhonov regularization (TV) algorithm, (6) and so on.…”

Section: Introductionmentioning

confidence: 99%

Electrical Impedance Tomography Based on a High-resolution Direction-of-arrival Estimation Algorithm

Wen¹,

Wei²,

Xue³

2020

Sensors and Materials

View full text Add to dashboard Cite

show abstract

“…Newton–Raphson method is an iterative algorithm of unconstrained minimization. But this method converges locally and Hessian matrix is seriously ill‐posed, which leads to poor image quality 15 . D‐bar methods are based on a rigorous mathematical analysis and provide robust direct reconstruction by using a low‐pass filtering of the associated nonlinear Fourier data.…”

Section: Introductionmentioning

confidence: 99%

“…But this method converges locally and Hessian matrix is seriously ill-posed, which leads to poor image quality. 15 Dbar methods are based on a rigorous mathematical analysis and provide robust direct reconstruction by using a low-pass filtering of the associated nonlinear Fourier data. During the image reconstruction, low frequency is used, which results in blurred images and causes many sharp features.…”

Section: Introductionmentioning

confidence: 99%

Image reconstruction based on a modified bird swarm optimization algorithm for electrical impedance tomography

Shi

Yuhang

Wang

et al. 2023

Int J Imaging Syst Tech

View full text Add to dashboard Cite

Electrical impedance tomography (EIT) is a potential and promising tomographic technique. It is known that image reconstruction of EIT is mathematically an ill-posed inverse problem that leads to poor reconstruction quality. To improve the quality of reconstructed images, a novel image reconstruction method based on modified bird swarm optimization algorithm is proposed in this paper. An image of conductivity distribution acquired by Newton's onestep error reconstruction algorithm performs as initial population. Then a modified bird swarm optimization algorithm is proposed to optimize the initial conductivity distribution. By introducing a dynamic inertia weight parameter, flight interval of the bird swarm varies with the number of iterations. With the proposed method, a strong global search capability in the initial stage and a strong local search capability in the later stage are ensured during the optimization. To verify the effectiveness of the proposed method, simulation work and experimental validation are carried out. Also, reconstructed images are compared with the results obtained by iterative Landweber method and Newton-Raphson method. Meanwhile, the impact of noise on the reconstruction is investigated. The simulation and experimental results have demonstrated the superior performance of the proposed method in visualizing conductivity distribution.

show abstract

“…Compared with the non-iterative algorithm, iterative Newton–Raphson method improves the quality of image reconstruction. However, the algorithm converges locally and requires a lot of time to calculate the sensitivity matrix for each iteration (Kim et al, 2012). Landweber method has the advantages of fast convergence, high stability, and simple operation.…”

Section: Introductionmentioning

confidence: 99%

Reconstruction of conductivity distribution variation with Tikhonov and wavelet frame combined method for electrical impedance tomography

Shi

Yuhang

Wang

et al. 2023

Transactions of the Institute of Measurement and Control

View full text Add to dashboard Cite

Electrical impedance tomography (EIT) is receiving considerable research interest in a variety of applications. With this technique, it is possible to reconstruct conductivity distribution inside the detected region. Note that reconstruction of conductivity distribution is an ill-posed inverse problem. To deal with this problem, Tikhonov regularization method has been preferred. However, this method suffers from poor reconstruction quality. In this work, a novel approach which combines Tikhonov regularization method with wavelet frame is proposed for image reconstruction of EIT. The proposed method is superior to the popular Tikhonov regularization method in enforcing sparse of the solution and enhancing sharp feature. Simulation work has been conducted to validate the performance of the proposed method. Compared with Landweber method, total variation (TV) regularization method, and Tikhonov regularization method, reconstructions of six different models show that images reconstructed by the proposed method have better quality and are more robust to noise. In addition, image reconstruction is also performed based on phantom experimental data. The results further demonstrate that the proposed method outperforms other three methods since the inclusion has been more accurately reconstructed, and there are almost no artifacts in the reconstructed images.

show abstract

Modified newton-raphson method using a region of interest in electrical impedance tomography

Cited by 10 publications

References 14 publications

Electrical Impedance Tomography Based on a High-resolution Direction-of-arrival Estimation Algorithm

Electrical Impedance Tomography Based on a High-resolution Direction-of-arrival Estimation Algorithm

Image reconstruction based on a modified bird swarm optimization algorithm for electrical impedance tomography

Reconstruction of conductivity distribution variation with Tikhonov and wavelet frame combined method for electrical impedance tomography

Contact Info

Product

Resources

About