Sensitivity maps reconstruction of Magnetic Induction Tomography real data measurement technique
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Sensitivity maps reconstruction of Magnetic Induction Tomography through real data measurement technique
Zulkarnay Zakaria Hafizi Suki
1.1Introduction
Magnetic induction tomography (MIT) is a new non-contacting technique for visualization of the electrical impedance distribution inside a media. In any tomography system, the image is reconstructed using image reconstruction algorithm which requires sensitivity maps. There are three methods of acquiring sensitivity maps; finite element technique, analytically or experimentally. During reconstruction both the forward solution and the Jacobian matrix need to be calculated.[1]
1.2
Overview
For industrial tomography, the emphasis is usually on high speed data acquisition, rather than resolution. This lends itself to electrical tomography techniques, which although lacking the resolution of x-ray and MRI tomography, are nearly instantaneous. Examples of electrical tomographic imaging methods are Magnetic Induction Tomography (MIT), in which multiple measurements of coupling between magnetic excitation
Sensitivity maps reconstruction of Magnetic Induction Tomography real data measurement technique
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and sensing coils are used to determine the internal resistivity of an object.
Object
Image
Figure 1.1: Object and imaged with electrical capacitance tomography
Sensitivity maps reconstruction of Magnetic Induction Tomography real data measurement technique
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1.2.1 Magnetic Induction Tomography (MIT) Magnetic induction tomography (MIT) is a new and emerging type of tomography technique that is able to map the passive electromagnetic properties (in particular conductivity) of an object. Excitation coils are used to induce eddy currents in the medium, and the magnetic field produced by the induced eddy current is then sensed by the receiver coils. Figure 4.2 shows a schematic MIT coil configuration with rectangular coils as receivers and a cylindrical object space. The excitation coils are distributed on two different rings in order to obtain a true 3-Darrangement.[2][3]
Figure 1.2: Schematic of a possible coil system for MIT with 16 excitation coils and 32 receiver coils. This paper is organized as follows: First the inverse eddy current problem in medical MIT is described and the generic mathematical approach for its solution is outlined. Then the current
Sensitivity maps reconstruction of Magnetic Induction Tomography real data measurement technique
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experimental possibilities are sketched so as to impose some important practical boundary conditions for the solution. Then it is shown that technical reasons make differential imaging the method of choice in the case of in-vivo MIT. Two different linear approaches are presented: state-differential and frequencydifferential MIT. Relative differential MIT spectroscopy is presented as a special extension of frequency-differential MIT. Finally reconstruction results from both simulated and experimental data are shown for low-contrast objects with conductivities near the physiological range.[3]
1.3
1.3.1
Literature review
Introduction
Magnetic induction tomography (MIT) is a kind of electromagnetic detecting and imaging technology, which is considered to be useful for diagnoses of the intracranial hemorrhage. The forward problem is the eddy current problem which is useful for improving the resolution of the measurement system and provides basic data for the inverse problem of image reconstruction. 1.3.2 Background Magnetic induction tomography (MIT) is a technique for imaging the internal conductivity distribution of an object. In MIT current-carrying coils are used to induce eddy currents in the object and the induced voltages are sensed with other coils. From these measurements, the internal conductivity distribution of the object can be reconstructed. MIT system consists of three components that are sensors, data acquisition and image reconstruction algorithm. Image reconstruction in magnetic induction tomography is a non-linear, ill-conditioned, inverse problem.[1]
Sensitivity maps reconstruction of Magnetic Induction Tomography real data measurement technique
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The famous image reconstruction is using linear backprojection due to its better speed but the drawback is blurry images. One way to improve the quality of reconstructed images is through improve the quality of sensitivity maps which is use in the image reconstruction algorithm. Compare to finite element technique and analytical way of reconstruct the sensitivity maps, experimental methods is prefer as it is based on the real prototype of the MIT system.[4] 1.3.3 Literature Review on previous work It has been known before this blur reconstructed images is a drawback of noise exist in the tomography system as well as poor sensitivity maps used in the image reconstruction algorithm. In most researchers, sensitivity map is generates using finite element technique or analytical technique that usually ignore certain parameters in real setup which in turn contribute to errors. Thus experimental technique needs to explore as a way of improvement. [4]
1.3.4
Summary of the Literature reviews
To study the experimental technique for generating of sensitivity maps in MIT modality. MIT applies a magnetic field from an excitation coil to induce eddy currents in the material to be studied, and the magnetic field from these is then detected by sensing coils. The technique has been variously named mutual inductance tomography (also MIT) and electromagnetic tomography (EMT). MIT is sensitive to all three passive electromagnetic properties such as conductivity, permittivity and permeability.
Sensitivity maps reconstruction of Magnetic Induction Tomography real data measurement technique
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Many related measurement methods applied on the electromagnetic excitation field to measure the response of the object and give information in the output A number of experimental systems exist but so far no MIT system has reached routine use either industrially or medically. There is a need for the two research communities to work more closely together to further their joint aim in making MIT a successful imaging modality.[6]
1.4 Methodology
1.4.1 Introduction An electrical impedance tomography (EIT) device for pressure mapping imaging. The medium to be imaged is made of conductive fabric. A map of the pressure/deformation applied to the fabric can be obtained. We can constructed an electrical impedance tomography (EIT) device. The medium to be imaged is surrounded by a ring of electrodes, and by measuring the resistance between different combinations of electrodes, an image of the object's resistivity can be obtained. Currently, 3D EIT is being developed. 1.4.2 Measurement Principle In MIT current-carrying coils are used to induce eddy currents in the object and the induced voltages are sensed with other coils. From these measurements, the internal conductivity distribution of the object can be reconstructed. MIT system consists of three components that are sensors, data acquisition and image reconstruction algorithm. Image reconstruction in magnetic induction tomography is a non-linear, ill-conditioned, inverse problem. The famous image reconstruction is using linear backprojection due to its better speed but the drawback is blurry images.[2][]
Sensitivity maps reconstruction of Magnetic Induction Tomography real data measurement technique
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Figure 1.3.1: The principle of induction tomography. The tube of magnetic lines as analog of beam in classic tomography
Figure 1.3.2: The coil system of induction tomograph. 1 inductors and detectors, 2 - screen
Sensitivity maps reconstruction of Magnetic Induction Tomography real data measurement technique
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Figure 1.3.3: Experimental measuring system for magnetic induction tomography with 16 inductors and detectors. The bottle filled with saline solution inside the system is used as test object.
Figure 1.3.4: Image reconstructed from the data measured with the system. The dark spot corresponds to the test object (plastic bottle 10 cm in diameter filled with 5% saline). The outward circle is drawn with diameter on which the coils are placed.
Sensitivity maps reconstruction of Magnetic Induction Tomography real data measurement technique
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Figure 1.4: The flow chart of MIT
Sensitivity maps reconstruction of Magnetic Induction Tomography real data measurement technique
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4.5 Discussion
This experiment will involve a study on the fundamental theory of magnetic fields, its challenges and constraint, weakness and opportunity in steel detection inside a concrete structure. Study on the suitable image reconstruction algorithm which is find the suitable high speed image reconstruction algorithm will be studies as this part is important in producing a high speed imaging system .
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Figure 1.5: Prototype magnetic induction tomography device.
Sensitivity maps reconstruction of Magnetic Induction Tomography real data measurement technique
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Several steel samples at different sizes available for the used in reinforced concrete will be tested in air medium. This experiment will determine the best resolution of the system. At this stage, the steel samples will be embedded in concrete and will be located in different mediums such as mud, water and concrete to further investigate its imaging performance at multiple boundary interfaces.
4.7
Conclusion
The hardware will be designed and develop based on the selected parameter. First stage of the development will be on the breadboard for the ease of modification, while at second stage it will be fabricated on the PCB board. The testing and verification of the developed hardware is carried out and the analysis and discussion of the results is done. Therefore, Linear and nonlinear algorithm base on will be developed and tested in producing the best image with higher frame rate based on the study. Analysis of the result will be done to make sure that the degree of accuracy has reached the acceptable value based on the reconstructed images produced. Evaluation on the system performance will be done based on the result analysis. References [1] M. Soleimani and K. Jersey-Willuhn, “IMAGE RECONSTRUCTION FOR MAGNETIC INDUCTION TOMOGRAPHY,” in 26th Annual International Conference of the IEEE EMBS, 2004, vol. 2007, pp. 631–634.
Sensitivity maps reconstruction of Magnetic Induction Tomography real data measurement technique
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[2]
Hsin-Yu Wei and Manuchehr Soleimani 2012 Physiol. Meas. 33 863. doi:10.1088/0967-3334/33/5/863 Received 11 November 2011, accepted for publication 13 March 2012. Published 24 April 2012. . Adler A. Accounting for erroneous electrode data in electrical impedance tomography Physiol Meas H. SCHARFETTER, P. BRUNNER AND R. MERWA 60525: 227–238, 2004. R. M. Lewitt, S. Member, and S. Matej, “Overview of Methods for Image Reconstruction From Projections in Emission Computed Tomography,” Proc. IEEE, vol. 91, no. 10, pp. 1588–1611, 2003. A J Peyton et al 1996 Meas. Sci. Technol. 7 261. doi:10.1088/0957-0233/7/3/006 Received 27 July 1995, accepted for publication 16 January 1996. H Griffiths 2001 Meas. Sci. Technol. 12 1126. doi:10.1088/0957-0233/12/8/319 Received 14 February 2001, accepted for publication 15 June 2001, in final form 31 May 2001. Cohen-Bacrie C., Y. Goussard and R. Guardo R, Regularized reconstruction in electrical impedance tomography using a variance uniformization constraint IEEE Trans Med Imaging, 16: 562-571, 1997. H. Griffiths, “Magnetic induction tomography,” Meas. Sci. Technol., vol. 12, no. 2, pp. 1126–1131, May 2001. I. J. Won, D. a. Keiswetter, and T. H. Bell, “Electromagnetic induction spectroscopy for clearing landmines,” IEEE Trans. Geosci. Remote Sens., vol. 39, no. 4, pp. 703–709, Apr. 2001.
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Sensitivity maps reconstruction of Magnetic Induction Tomography real data measurement technique
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M. P. Christian, S. L. Firebaugh, and A. N. Smith, “COMSOL Thermal Model for a Heated Neural MicroProbe,” 2012. P. Gaydecki, S. Quek, G. Miller, B. T. Fernandes, and M. A. M. Zaid, “Design and evaluation of an inductive Q -detection sensor incorporating digital signal processing for imaging of steel reinforcing bars in concrete,” Meas. Sci. Technol., vol. 13, no. 8, pp. 1327–1335, 2002. A. J. Peyton, Z. Z. Yu, S. Al-Zeibak, N. H. Saunders, and A. R.Borges, “Electromagnetic imaging using mutual inductance tomography:Potential for process applications,” Part. Syst. Charact., vol.12, pp. 68–74, 1995
