scholarly journals A Novel GUI-Based Image Reconstruction Algorithm of EIT Imaging Technique

2021 ◽  
Vol 15 (3) ◽  
pp. 31-46
Author(s):  
Ramesh Kumar ◽  
Shashank Tripathi
Keyword(s):  
Image Reconstruction ◽  
Reconstruction Algorithm ◽  
Forward Problem ◽  
Invasive Technique ◽  
Impedance Tomography ◽  
Imaging Algorithm ◽  
Image Reconstruction Algorithm ◽  
Non Invasive ◽  
Impedance Parameters ◽  
Phantom Experiments

Electrical impedance tomography (EIT) is a non-invasive technique that is used to estimate the electrical properties of a medical or non-medical object through the boundary data of the object. It used to achieve functional imaging of different objects by measuring electrical conductivity and impedance parameters. In this paper, a novel image reconstruction algorithm is presented, which is based on graphical user interface (GUI) developed on MATLAB software platform. EIT imaging algorithm consists of a forward problem and an inverse problem. The forward problem is formulated with the conductance matrix, and a non-iterative inverse method is used to estimate the conductivity distribution. Image display and data analysis are implemented and controlled directly in the GUI. The numerical simulations and phantom experiments have been carried out to evaluate the performance of the proposed algorithm and other previous research data through quantitative parameters. The obtained result shows satisfactory and comparable results to other EIT imaging algorithm.

An Image Reconstruction Algorithm with Experimental Validation for Electrical Impedance Tomography Imaging Applications

2020 ◽  
Vol 18 (5) ◽  
pp. 410-418
Author(s):  
Ramesh Kumar ◽  
H. S. Mewara ◽  
Shashank Tripathi ◽  
Aditya Kumar Singh Pundir
Keyword(s):  
Image Reconstruction ◽  
Current Pulse ◽  
Tikhonov Regularization ◽  
Reference Electrode ◽  
Reconstruction Algorithm ◽  
Impedance Tomography ◽  
Non Invasive ◽  
Impedance Technique ◽  
Conductivity Medium ◽  
Acquisition Method

In the Non-Invasive Bio Impedance Technique (NIBIT) a low current pulse with high frequency inserted between two electrodes of the object while measuring voltages from the other remaining electrodes with respect to the reference electrode. The electrode arrangement is defined in the form of cylindrical shapes of the surface of the phantom. After these arrangements, it inserts the current pulse and measures the voltages according to the selected data acquisition method of bio impedance. The presented algorithm analyzes and defines each obtained data sample from the used phantoms and also allows Image Reconstruction (IR) based on developed Graphical User interface (GUI) on MATLAB. The used IR approach is based on Tikhonov regularization and FEM. The FEM and Tikhonov regularization are mathematical approaches that deal with Forward Problem (FP) and Inverse Problem (IP) of images. In our approach, the FP solution is identified first in order to reconstruct the conductivity distribution through the EIT inverse solution. Thereafter, This FP is solved through the known current pulse of a given conductivity medium. Likewise, the IP is identified and solved through the boundary potential of the object. The end of the obtained result provides a comparable result for the used phantom according to its internal structure. This proposed technique is still reliable despite having some standardization issue according to the procedure.

A Fast Image Reconstruction Algorithm for EIT Based on Wavelet Analysis and LSQR

2014 ◽  
Vol 654 ◽  
pp. 341-345
Author(s):  
Ying Zhi Sun ◽  
Jian Ming Wang ◽  
Qi Wang
Keyword(s):  
Image Reconstruction ◽  
Electrical Impedance ◽  
Reconstruction Algorithm ◽  
Scale Space ◽  
Least Square ◽  
Qr Factorization ◽  
Impedance Tomography ◽  
Image Reconstruction Algorithm ◽  
Low Dimension ◽  
2D And 3D

The LSQR algorithm is always used to solve the inverse problem of electrical impedance tomography (EIT). However, it always has relatively low reconstruction speed. In this paper, WALSQR (wavelet multi-resolution based Least Square QR-factorization) algorithm is proposed for EIT imaging. With the aid of wavelet transformation, the LSQR solution is obtained in the low-dimension scale space, where important information on the reconstructed image is contained. Hence the computational complexity of reconstruction is reduced without affecting the image quality. In order to verify the effectiveness of the new method, experiments of 2D and 3D EIT imaging are conducted. It lays the foundation for the study of 3D dynamic EIT image reconstruction algorithm.

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