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Simulative study of two-phase homogenous and isotropic media imaging using magnetic induction tomography
Zulkarnay Zakaria1, Ibrahim Balkhis2, Lee, Pick Yern3, Nor Muzakkir Nor Ayob4, Mohd Hafiz Fazalul Rahiman5, Mohd Zikrillah Zawahirah6, Ruzairi Abdul Rahim7.
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.
Affiliation:
- Universiti Malaysia Perlis, Malaysia
- Universiti Malaysia Perlis, Malaysia
- Universiti Malaysia Perlis, Malaysia
- Universiti Teknologi Malaysia, Malaysia
- Universiti Malaysia Perlis, Malaysia
- Universiti Malaysia Perlis, Malaysia
- Universiti Teknologi Malaysia, Malaysia
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Indexation |
Indexed by |
MyJurnal (2021) |
H-Index
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6 |
Immediacy Index
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0.000 |
Rank |
0 |
Indexed by |
Scopus 2020 |
Impact Factor
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CiteScore (1.4) |
Rank |
Q3 (Engineering (all)) |
Additional Information |
SJR (0.191) |
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