Simulative Study of Two-Phase Homogenous and Isotropic Media Imaging using Magnetic Induction Tomography
DOI:
https://doi.org/10.11113/jt.v69.3298Abstract
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.
References
Soleimani, M. 2008. Computational Aspects of Low Frequency Electrical and Electromagnetic Tomography: A Review Study. International Journal of Numerical Analysis and Modelling. 5: 407–440
Zakaria, Z., Rahim, R.A., Mansor, M.S.B.,Yaacob, S., Ayob, N. M. N., Muji, S.Z.M., Rahiman, M.H.F. and Aman, S. M. K. S. 2012. Advancements in Transmitters and Sensors for Biological Tissue Imaging in Magnetic Induction Tomography. Sensors. 12: 7126–7156
Tian, G. Y., Al-Qubaa, A. & Wilson, J. 2012. Design of an Electromagnetic Imaging System for Weapon Detection Based on GMR Sensor Arrays. Sensors and Actuators A: Physical. 174: 75–84.
Griffiths, H. 2001. Magnetic Induction Tomography. Measurement Science and Technology. 12: 1126–1131.
Griffiths, H. 2005. Magnetic Induction Tomography. Electrical Impedance Tomography: Methods, History and Applications. 213–238
Terzija, N., Yin, W., Gerbeth, G., Stefani, F., Timmel, K., Wondrak, T., Peyton, A. J. 2011. Use of Electromagnetic Induction Tomography for Monitoring Liquid Metal/Gas Flow Regimes on a Model of an Industrial Steel Caster. Measurement Science and Technology. 22: 1–8.
Nor Ayob, N. M., Zakaria, Z., Fazalul Rahiman, M. H., Abdul Rahim, R. & Yaacob, S. 2011. Initial Development on Magnetic Induction Tomography Imaging. Jurnal Teknologi. 55: 11–14.
Soleimani, M. 2006. Sensitivity Maps in Three-dimensional Magnetic Induction Tomography. Insight-Non-Destructive Testing and Condition Monitoring. 48: 39–44.
Yin, W. & Peyton, A. J. 2010. Sensitivity Formulation Including Velocity Effects for Electromagnetic Induction System. IEEE Transactions on Magnetics. 46: 1172–1176.
Fazalul Rahiman, M. H., Abdul Rahim, R. & Zakaria, Z. 2008. Design and Modelling of Ultrasonic Tomography for Two-component High-acoustic Impedance Mixture. Sensors and Actuators A: Physical. 147: 409–414.
Nor Ayob, N. M., Fazalul Rahiman, M. H., Zakaria, Z., Abdul Rahim, R. & Yaacob, S. 2011. Eminent Pixel Reconstruction Algorithm For Ultrasonic Tomography. Jurnal Teknologi. 55: 15–22.
Ritman, E. L. 2004. Micro-computed Tomography-current Status and Developments. Annual Review of Biomedical Engineering. 6: 185–208.
Haff, R. P. & Toyofuku. 2008. N. X-ray detection of defects and contaminants in the food industry. Sensing and Instrumentation for Food Quality and Safety. 2: 262–273.
Gore, J. C., Manning, H. C., Quarles, C. C., Waddell, K. W. & Yankeelov, T. E. 2011. Magnetic Resonance in the Era of Molecular Imaging of Cancer. Magnetic Resonance Imaging. 29: 587–600.
Thybo, A. K., Jespersen, S. N., Laerke, P. E. & Stødkilde-Jørgensen, H. J. 2004. Nondestructive Detection of Internal Bruise and Spraing Disease Symptoms in Potatoes Using Magnetic Resonance Imaging. Magnetic Resonance Imaging. 22: 1311–7.
Downloads
Published
Issue
Section
License
Copyright of articles that appear in Jurnal Teknologi belongs exclusively to Penerbit Universiti Teknologi Malaysia (Penerbit UTM Press). This copyright covers the rights to reproduce the article, including reprints, electronic reproductions, or any other reproductions of similar nature.
