Back-Projection Reconstruction Algorithm for Magnetic Induction Tomography Based on Magnetic Field Lines Distribution

2012 ◽  
Author(s):  
Li Ke ◽  
Xiao Lin ◽  
Qiang Du
Keyword(s):  
Magnetic Field ◽  
Magnetic Induction ◽  
Reconstruction Algorithm ◽  
Back Projection ◽  
Projection Reconstruction ◽  
Field Lines ◽  
Magnetic Induction Tomography

Simulation Analysis of the Sensitivity in Magnetic Induction Tomography Based on Perturbation Theory

2013 ◽  
Vol 749 ◽  
pp. 371-376
Author(s):  
Yang Xuan ◽  
Xu Wang ◽  
Cheng An Liu ◽  
Dan Yang
Keyword(s):  
Perturbation Theory ◽  
Salt Solution ◽  
Magnetic Induction ◽  
Imaging Modality ◽  
Reconstruction Algorithm ◽  
Target Object ◽  
Back Projection ◽  
Filtered Back Projection ◽  
Projection Reconstruction ◽  
Magnetic Induction Tomography

Magnetic induction tomography (MIT) is a noninvasive and contactless imaging modality which aims at the reconstruction of the electrical conductivity in objects from alternating magnetic fields. Filtered back projection reconstruction algorithm is widely used in biomedical imaging field, and tried to use in MIT. Finite element analysis model has been established based on Scharfetter coil-coil model and perturbation theory, then simulated coaxial coil system by ANSYS software, the perturbation aroused by a target object moving on vertical coil axis. The sensitivity of a target object moves in vacuum and a salt solution were calculated respectively, the characteristics of the perturbation sensitivity in a salt solution were analyzed. The conditions of filtered back projection reconstruction algorithm in MIT were discussed.

An Improved Back-Projection Algorithm for Magnetic Induction Tomography Image Reconstruction

2013 ◽  
Vol 647 ◽  
pp. 630-635 ◽  
Author(s):  
Li Ke ◽  
Xiao Lin ◽  
Qiang Du
Keyword(s):  
Magnetic Field ◽  
Image Reconstruction ◽  
Magnetic Induction ◽  
Projection Algorithm ◽  
Projection Area ◽  
Homogeneous Field ◽  
Back Projection ◽  
Field Lines ◽  
Magnetic Induction Tomography ◽  
The Magnetic Field

Magnetic induction tomography (MIT) acted as a contactless and non-invasive medical imaging technology has aroused wide concern, while a large amount of calculation and a series of convergence problems in the solution of the inverse problem become technical difficulties for MIT. In order to solve these problems, an improved back-projection image reconstruction algorithm based on the magnetic field lines distribution is presented in this paper. Firstly, the eddy current problem of MIT was solved by the finite element method to obtain the magnetic field distribution. Secondly, the back-projection areas were divided according to the magnetic field lines distribution in the homogeneous field. Finally, image reconstruction was realized by projecting the phase shifts back along the corresponding projection area. The reconstruction results for perturbations with different conductivities appearing at different locations reveal that the improved back-projection algorithm for MIT owning the character of high speed performs well in reflecting location and shape information of the perturbation.

Simulative Study of Two-Phase Homogenous and Isotropic Media Imaging using Magnetic Induction Tomography

2014 ◽  
Vol 69 (8) ◽  
Author(s):  
Zulkarnay Zakaria ◽  
Ibrahim Balkhis ◽  
Lee Pick Yern ◽  
Nor Muzakkir Nor Ayob ◽  
Mohd Hafiz Fazalul Rahiman ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Magnetic Induction ◽  
Optical Tomography ◽  
Reconstruction Algorithm ◽  
Projection Algorithm ◽  
Back Projection ◽  
Two Phase ◽  
Excitation Coil ◽  
Magnetic Induction Tomography ◽  
Linear Back Projection

Magnetic induction tomography is a new non-invasive technology, based on eddy current discovery of electromagnetic induction by Michael Faraday. Through this technique, the passive electrical properties distribution of an object can be obtained by the use of image reconstruction algorithm implemented in this system. There are many types of image reconstruction that have been developed for this modality, however in this paper only two algorithms discussed, Linear Back Projection and Eminent Pixel Reconstruction. Linear Back Projection algorithm is the most basic type of image reconstruction. It is the simplest and fast algorithm out of all types of algorithms, whereas Eminent Pixel Reconstruction algorithm is an improved algorithm which provided better images and has been implemented in other modalities such as optical tomography. This paper has implemented Eminent Pixel Reconstruction in magnetic induction tomography applications and the performance is compared to Linear Back Projection based on the simulation of the fourteen types of simulated phantoms of homogenous and isotropic conductivity property. It was found that Eminent Pixel Reconstruction has produced better images relative to Linear Back Projection, however the images are still poor when the objects are located near to the excitation coil or sensor and it is worse when the distance between objects are near to each other.

Image Reconstruction with the Fourier Coefficients for Magnetic Induction Tomography

2020 ◽  
Vol 16 (2) ◽  
pp. 156-163
Author(s):  
Jingwen Wang ◽  
Xu Wang ◽  
Dan Yang ◽  
Kaiyang Wang
Keyword(s):  
Inverse Problem ◽  
Image Reconstruction ◽  
Magnetic Induction ◽  
Fourier Coefficients ◽  
Signal Reconstruction ◽  
Reconstruction Algorithm ◽  
Reconstruction Method ◽  
Measurement Equation ◽  
Image Reconstruction Method ◽  
Magnetic Induction Tomography

Background: Image reconstruction of magnetic induction tomography (MIT) is a typical ill-posed inverse problem, which means that the measurements are always far from enough. Thus, MIT image reconstruction results using conventional algorithms such as linear back projection and Landweber often suffer from limitations such as low resolution and blurred edges. Methods: In this paper, based on the recent finite rate of innovation (FRI) framework, a novel image reconstruction method with MIT system is presented. Results: This is achieved through modeling and sampling the MIT signals in FRI framework, resulting in a few new measurements, namely, fourier coefficients. Because each new measurement contains all the pixel position and conductivity information of the dense phase medium, the illposed inverse problem can be improved, by rebuilding the MIT measurement equation with the measurement voltage and the new measurements. Finally, a sparsity-based signal reconstruction algorithm is presented to reconstruct the original MIT image signal, by solving this new measurement equation. Conclusion: Experiments show that the proposed method has better indicators such as image error and correlation coefficient. Therefore, it is a kind of MIT image reconstruction method with high accuracy.

scholarly journals A Simulation Magnetic Induction Tomography (MIT) for Agarwood using COMSOL Multiphysics

2021 ◽  
Vol 10 (3) ◽  
pp. 67-71
Author(s):  
Nurfarahin Ishak ◽  
Chua King Lee ◽  
Siti Zarina Mohd Muji
Keyword(s):  
Magnetic Field ◽  
Magnetic Induction ◽  
Electromagnetic Properties ◽  
Induced Current ◽  
Solenoid Coil ◽  
Agriculture Industry ◽  
Eddy Current Effect ◽  
Coil Diameter ◽  
Great Performance ◽  
Magnetic Induction Tomography

Magnetic induction tomography is an imaging technique used to image electromagnetic properties of an object by using the eddy current effect. (MIT) is a non-destructive method that greatly is used in the agriculture industry. This method provided an opportunity to improve the quality of agricultural products. MIT simulation was used for agarwood existence detection. This paper presented for the simulation system contains 7 channel coils receiver and a channel transmitter which is a sensing detector. This experiment aims to demonstrate the reaction of induced current density and magnetic field at 10 MHz frequency. Then, it also determines the optimal solenoid coil to be used for a better outcome for the magnetic induction system. The simulation result shows that coil diameter, coil length, and coil layer have a crucial role in the great performance of the induced current and magnetic field. The more coil turns, the greater the strength of the permanent magnetic field around the solenoid coil. The result of the simulation is important and needs to be considered to verify the effectiveness of the system for developing the magnetic induction circuit design.

A Data Standardization and Reconstruction Method for Magnetic Induction Tomography

2013 ◽  
Vol 647 ◽  
pp. 560-565 ◽  
Author(s):  
Qiang Du ◽  
Bao Dong Bai ◽  
Li Ke
Keyword(s):  
Eddy Current ◽  
Magnetic Induction ◽  
Impedance Measurement ◽  
Reconstruction Algorithm ◽  
Biological Tissues ◽  
Measured Data ◽  
Image Resolution ◽  
Reconstruction Method ◽  
Data Standardization ◽  
Magnetic Induction Tomography

Magnetic induction tomography (MIT) is a biologic tomography technology, which is to obtain the conductivity distribution by detecting the data on the boundary of the imaging area based on the eddy current principle. The small impedance difference between biological tissues makes the eddy current weak, and it leads to a direct effect on the biological impedance measurement and imaging sensitivity. A measured data standardization method is presented in this paper for enhancing the measured data sensitivity, and combined with the back-projection reconstruction algorithm to get reconstruction image. It is applied to a variety of measurement and the simulation experiment based on the calculation results of finite-element methods. The reconstructed images indicate that the method can improve the image resolution and sensitivity, and which provides an effective data standardization and reconstruction algorithm for the magnetic induction tomography.

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