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Magnetic Induction Tomography (MIT) is a newly developing technique of electrical tomography that in principle is able to map the electrical conductivity distribution in the volume of objects. The image reconstruction problem in MIT is similar to electrical impedance tomography (EIT) in the sense that both seek to recover the conductivity map, but differ remarkably in the fact that data being inverted in MIT is derived from induction theory and related sources of noise are different. Progress in MIT image reconstruction is still limited, and so far mainly linear algorithms have been implemented. In difference imaging, step inversion was demonstrated for recovering perturbations within conductive media, but at the cost of producing qualitative images, whilst in absolute imaging, linear iterative algorithms have mostly been employed but mainly offering encouraging results for imaging isolated high conductive targets. In this paper, we investigate the possibility of absolute imaging in 3D MIT of a target within conductive medium for low conductivity application (σ < 5Sm-1). For this class of problems, the MIT image reconstruction exhibits non-linearity and ill-posedness that cannot be treated with linear algorithms. We propose to implement for the first time in MIT two effective inversion methods known in non-linear optimization as Levenberg Marquardt (LMM) and Powell's Dog Leg (PDLM) methods. These methods employ damping and trust region techniques for controlling convergence and improving minimization of the objective function. An adaptive version of Gauss Newton is also presented (AGNM), which implements a damping mechanism to the regularization parameter. Here, the level of penalty is varied during the iterative process. As a comparison between the methods, different criteria are examined from image reconstructions using the LMM, PDLM and AGNM. For test examples, volumetric image reconstruction of a perturbation within homogeneous cylindrical background is considered. For inversion, an independent finite element FEM software package Maxwell by Ansys is employed to generate simulated data using a model of a 16 channel MIT system. Numerical results are employed to show different performance characteristics between the methods based on convergence, stability and sensitivity to the choice of the regularization parameter. To demonstrate the effect of scalability of absolute imaging in MIT for more realistic problems, a human head model with an internal anomaly is used to produce reconstructions for different finer resolutions. AGNM is adopted here and employs the Krylov subspace method to replace the computationally demanding direct inversion of the regularized Hessian. [ABSTRACT FROM AUTHOR]

A completely contactless flow measurement technique based on the principle of EM induction measurements-contactless inductive flow tomography (CIFT)-has been previously reported by a team based at Forschungszentrum Dresden-Rossendorf (FZD). This technique is suited to the measurement of velocity fields in high conductivity liquids, and the possible applications range from monitoring metal casting and silicon crystal growth in industry to gaining insights into the working of the geodynamo. The forward problem, i.e. calculating the induced magnetic field from a known velocity profile, can be described as a linear relationship when the magnetic Reynolds number is small. Previously, an integral equation method was used to formulate the forward problem; however, although the sensitivity matrices were calculated, they were not explicitly expressed and computation involved the solution of an ill-conditioned system of equations using a so-called deflation method. In this paper, we present the derivation of the sensitivity matrix directly from electromagnetic field theory and the results are expressed very concisely as the cross product of two field vectors. A numerical method based on a finite difference method has also been developed to verify the formulation. It is believed that this approach provides a simple yet fast route to the forward solution of CIFT. Furthermore, a method for sensor design selection based on eigenvalue analysis is presented. [ABSTRACT FROM AUTHOR]

The flow structure in the mold of a continuous caster has a great influence on the quality of the produced steel. Conventional flow measurement techniques are prevented by the high temperature of the liquid steel. For a physical model of the continuous casting process using a low-melting point liquid metal, we present combined measurements of the flow in the mold by contactless inductive flow tomography (CIFT), and of the conductivity distribution in the submerged entry nozzle (SEN) by mutual inductance tomography. In addition, we summarize experiments with a magnetic stirrer around the SEN and its effects on the flow in the mold. Some new developments towards a robust implementation of CIFT at a real caster, including the use of pickup coils and gradiometric probes, are also discussed. [ABSTRACT FROM AUTHOR]

This paper presents a method for the numerical computation of 3-D sensitivity coefficients of a target object in magnetic induction tomography (MIT). The sensitivity coefficient at a point is defined as the dot product of electromagnetic fields produced by unit current flowing in the excitation and the detector coil. In this paper, the fields are governed by a set of boundary integral equations (BIEs). Numerical results demonstrate that the fields on the boundary and interior volume domain of the target can be accurately represented by radial basis functions (RBFs). The paper compares numerical solutions of the BIEs based on RBFs with analytical solutions and boundary element solutions. [ABSTRACT FROM AUTHOR]

We propose a new formulation for the forward problem in magnetic induction tomography (MIT). We formulate the problem in terms of interior and exterior boundary integral equations (BIEs), subject to appropriate boundary conditions. We then transform a standard exterior BIE involving the magnetic vector potential to a BIE involving the electric fields. This transformation eliminates two boundary conditions involving the magnetic vector potential and its normal derivative. This greatly reduces the computational complexity of the model. Here, we compare numerical solutions of the model to analytical solutions. [ABSTRACT FROM AUTHOR]

Eddy-current techniques can be used to create electrical conductivity mapping of an object. The eddy-current imaging system in this paper is a magnetic induction tomography (MIT) system. MIT images the electrical conductivity of the target based on impedance measurements from pairs of excitation and detection coils. The inverse problem here is ill-posed and nonlinear. Current state-of-the-art image reconstruction methods in MIT are generally based on linear algorithms. In this paper, a regularized Gauss-Newton scheme has been implemented based on an edge finite-element forward solver and an efficient formula for the Jacobian matrix. Applications of Tikhonov and total variation regularization have been studied. Results are presented from experimental data collected from a newly developed MIT system. The paper also presents further progress in using an MIT system for molten metal flow visualization in continuous casting by applying the proposed algorithm in a real experiment in a continuous casting pilot plant of Corus RD&T, Teesside Technology Centre. [ABSTRACT FROM AUTHOR]

Electromagnetic tomography is a process detection technology based upon the principles of electromagnetic induction. The forward problem model and sensitivity distribution matrix of electromagnetic tomography are introduced as the basis of the inverse problem. The search direction and iterative parameters of the conjugate gradient algorithm are modified to improve the quality and convergence of image reconstruction. A new spectral parameter conjugate gradient algorithm is described to modify the search direction, which is used to control the angle between the old and new search directions. The search direction is determined according to the iteration of each step in order to find the optimal solution. Combining the advantages of the Fletcher-Reeves and Polak-Ribiere-Polyak algorithms in the nonlinear conjugate gradient algorithm, they are mixed in a specific proportion to obtain a new hybrid conjugate gradient algorithm. In order to verify the effectiveness of the modified conjugate gradient algorithm, three physical models of electromagnetic tomography system are constructed, and the modified conjugate gradient algorithm is compared with the traditional algorithm. The experimental results show that the reconstructed image quality of the modified spectral conjugate gradient algorithm is higher and has better numerical performance. The hybrid conjugate gradient algorithm highlights the advantages of the Fletcher-Reeves and Polak-Ribiere-Polyaks algorithms. The convergence speed is faster than the Polak-Ribiere-Polyak method, and the imaging quality is higher than the other algorithms. [ABSTRACT FROM AUTHOR]

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. Because of its non-invasive feature, it becomes a suitable technique for many industries, such as metal processing and mining. This paper presents a volumetric MIT (VMIT) system based on an existing measurement setup in our 2D system (MIT Mk-I). By increasing the number of sensors in the axial direction, volumetric imaging can be realized and hence can improve the spatial resolution of the reconstructed images. All of the system control, data acquisition and signal demodulation are accomplished by a commercial data acquisition card and the National Instruments graphical programming language. In this paper, both the system architecture and the forward 3D sensitivity model will be presented. The image reconstruction scheme is modified by introducing a 3D sensitivity map to replace the previous 2D sensitivity map used for the MIT Mk-I system. The iterative Landweber technique was implemented as the inverse solver to reconstruct the images. Several laboratory-based experimental results are demonstrated in this paper, with different shapes of imaging objects. The reconstructed images are satisfactory showing for the first time volumetric conductivity reconstruction using a multi-layer MIT system. The results indicate the high-quality image reconstruction using our novel VMIT system for potential use in industrial applications, such as metal flow imaging. [ABSTRACT FROM AUTHOR]

Image reconstruction of electromagnetic tomography (EMT) is often ill-posed due to the limited prior information about imaging features, leading to low reconstruction accuracy. In this paper, a novel image reconstruction method based on frequency domain feature extraction for EMT is proposed to improve the reconstruction accuracy. The two-dimensional EMT image is first modeled as a one-dimensional finite-length streams of Dirac signal, which is a typical signal with finite rate of innovation (FRI). Then the reconstruction results of the recent algorithms, such as the LBP, Landweber and TV algorithms, can be also modeled as FRI signals. The frequency domain feature of such signals can be extracted with a distributed FRI sampling system. Based on the obtained FRI samples, a new EMT measurement equation is established, and a joint image reconstruction algorithm is proposed, to improve the quality of the reconstructed image. Finally, simulation results have shown that the proposed method outperforms the related methods with better indicators such as image error and correlation coefficient. [ABSTRACT FROM AUTHOR]

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The solidification process in continuous casting is a critical part of steel production. The speed and quality of the solidification process determines the quality of the final product. Computational fluid dynamics (CFD) simulations are often used to describe the process and to design its control system but, so far, there has been no tool that provides an online measurement of the solidification front of hot steel during the continuous casting process. This paper presents a novel magnetic induction tomography (MIT) solution, developed in the EU-funded SHELL-THICK project, to work in a real casting setting and to provide a real-time and reliable measurement of the shell thickness in a cross section of the strand. The new MIT system was installed at the end of the secondary cooling chamber of a casting unit and tested over several days in a real production process. MIT is able to create an internal map of the electrical conductivity of hot steel deep inside the billet. The image of electrical conductivity is then converted to a temperature profile that allows the measurement of the solid, mushy and liquid layers. In this study, such a conversion is done by synchronizing in one time step the MIT measurement and the thermal map generated with the actual process parameters available at that time. The MIT results were then compared with the results obtained with the CFD and thermal modelling of the industrial process. This is the first time in situ monitoring of the interior structure has been carried out during a real continuous casting. [ABSTRACT FROM AUTHOR]

Magnetic induction tomography (MIT) is a tomographic technique capable of imaging the passive electromagnetic properties of an object. It has the advantages of being contact-less and non-invasive, as the process involves interrogating the electromagnetic field of the imaging subject. As such, the potential applications of MIT are broad, with various domains of operation including biomedicine, industrial process tomography and non-destructive evaluation. Consequently, there is a rich—yet underexplored—research landscape for the practical applications of MIT. The aim of this review is to provide a non-exhaustive overview of this landscape. The fundamental principles of MIT are discussed, alongside the instrumentation and techniques necessary to obtain and interpret MIT measurements. [ABSTRACT FROM AUTHOR]

Carbon fibre reinforced polymer (CFRP) materials pose new challenges to the non-destructive evaluation (NDE) techniques. This study addresses the issue of large defect identification in CFRP plates using electromagnetic measurements. A dual plane magnetic induction tomography (MIT) technique is proposed as a method for damage localization in composite parts, where two arrays of planar sensors are utilized to measure the changes in induced voltages due to the changes in electrical conductivity properties. This geometry meets the requirements of damage inspection in plate structures and thus makes the imaging process feasible. The electrical voltage measurements are used as input to inversely map the spatial resolution of the samples in the region of interest. The stability and detectability of the dual plane system is examined using small metallic cubes. Both individual and multiple instances of damage embedded in CFRP samples are created as a representation of the possible manufacturing defects. Experimental study shows that the presence of damage can be identified in both cases using the dual plane MIT system. With advanced sensing design, rapid data collection unit and improvement in resolution, MIT could become a rapid NDE technique for the integrity inspection of composite structures. [ABSTRACT FROM AUTHOR]

Magnetic induction tomography (MIT) is a tomographic technique utilising inductive coils and eddy currents to map the passive electromagnetic properties of an object. Eddy current methods are widely used for non-destructive testing (NDT) in inspection of metallic structures. Eddy current based NDT uses a single coil or a pair of coils to scan the samples. As an emerging NDT technique, MIT scans the sample with a coil array through an eddy current based tomographic approach. In this paper, a planar array MIT system (PMIT) is proposed for 3D near subsurface imaging. This is of great importance as there are large numbers of potential applications for MIT that allow limited access to the materials under testing. The system development, practical implication, capability and limitations of PMIT are discussed. The fundamental principles are demonstrated through simulations. Experimental data are used to evaluate the capability and detectability this system has as a potential 3D subsurface imaging tool. [ABSTRACT FROM AUTHOR]

Magnetic induction tomography (MIT) is an imaging technique based on the measurement of the magnetic field perturbation due to eddy currents induced in conducting objects exposed to an external magnetic excitation field. In MIT, current-carrying coils are used to induce eddy currents in the object and the induced voltages are sensed with the receiving coils. When the driving frequency is significantly high relative to the frequency range in which MIT normally operates, metallic targets with high conductivity between the coils can be treated as perfect electric conductors (PEC) with negligible errors. In this scenario, the penetration depth of the magnetic field into the target is extremely small and the traditional versions of the finite element method (FEM) are not efficient for the calculation of the sensitivity and the forward problem due to the requirement for large number of elements to reach an acceptable computational precision. Other versions of FEMs (such as Hp-FEM), which have higher discretization efficiency and more advanced elements to satisfy the requirement, are exceptions. Nevertheless, the discretization regions for all FEMs have to extend beyond the region that contains the conducting object and volumetric elements are generally required for 3D problems. In contrast, the boundary element method (BEM) based on integral formulations becomes an effective way to analyze this kind of scattering problem since meshes are only required on the surface of the object. By point collocation, the boundary integral equations can be transformed into linear equations. Numerical methods are used to solve the linear equations and the solution of the original integral equations can be obtained. In this paper, we compute four typical sensitivity maps between the coil pairs in high-frequency MIT system due to a PEC perturbation. The magnetic scalar potential is used to improve the efficiency. Five PEC objects of different shapes are used in the simulation. The results have been compared with the experimental results and that obtained from the H · H formulations. We can know that the sensitivity maps derived by BEM are in good agreement with that from the experiment and theoretical solution. Overall, BEM is an effective way to calculate the sensitivity distributions of a high-frequency MIT system. [ABSTRACT FROM AUTHOR]

Magnetic Induction Tomography (MIT) is a relatively new and emerging type of tomography techniques that is able to map the distribution of all three passive electrical properties (PEPs). Its non-invasive and contactless features make it an attractive technique for many applications compared to the traditional contact electrode based electrical impedance tomography. Recently, MIT has become a promising monitoring technique in industrial process tomography, and the area of the research interest has moved from 2D to 3D because of the volumetric nature of electromagnetic field. Three dimensional MIT images provide more information on the conductivity distribution, especially in the axial direction. However, it has been reported that the reconstructed 3D images can be distorted when the imaging object is located at a less sensitive region. Although this distortion can be compensated by adjusting the regularisation criteria, this is not practical in real life applications as the prior information about the object's location is often unavailable. This paper presents a memory efficient 4D MIT algorithm which can maintain the image quality under the same regularisation circumstances. Instead of solving each set of measurement individually, the 4D algorithm takes advantage of the correlations between the image and its neighboring data frames to reconstruct 4D of conductivity movements. The 4D algorithm improves the image qualities by increasing the temporal resolution. It also overcomes some sensitivity issues of 3D MIT algorithms and can provide a more stable result in terms of the size consistency of the reconstructed image. Several experimental results using real laboratory data are presented for validating the proposed algorithms. [ABSTRACT FROM AUTHOR]

Pipelines are the most common apparatus in industries; therefore, the need for inspection during the manufacturing, construction and the operation stage is inevitable and invaluable. Magnetic Induction Tomography (MIT) is a new type of tomography technique that is sensitive to the electrical conductivity of objects. It has been shown that the MIT technique is appropriate for imaging materials with high electrical conductivity contrasts; hence, the majority of the MIT systems were designed for detecting metallic objects. In this paper, MIT technique was proposed for pipeline inspection. Structural damages of the outer surface of the pipe were considered in this study. Nonetheless, it is challenging to use the traditional MIT pixel based reconstruction method (PBRM) as a suitable pipelines inspection tool because of the limited resolution. A narrowband pass filtering method (NPFM) of imaging pipe geometry was developed as a suitable image reconstruction method. The proposed method can overcome the resolution limitations and produce useful information of the pipe structure. This paper shows the comparative results from the novel NPFM and from traditional PBRM. While the PBRM fails to detect damages in outer structure of the pipe the NPFM successfully identifies these damages. The method has been verified using experimental data from very challenging test samples. It is well known that using a coil array with an imaging region of 100 mm the PBRM based MIT can retrieve information with accuracy of about 10 mm (about 10%). With proposed NPFM the information on a resolution of 2 mm (which is about 2%) can be detected using the same measurement data. [ABSTRACT FROM AUTHOR]

In magnetic induction tomography (MIT), an array of excitation coils is typically used to apply time-varying magnetic fields to induce eddy currents in the material to be studied. The magnetic fields from the eddy currents are then detected by an array of sensing coils to form an image of passive electromagnetic properties (i.e. conductivity, permittivity and permeability). Increasing the number of transmitters and receivers can provide a better image quality at the expense of a larger and more expensive MIT system. Instead of increasing the number of coils, this study investigates the possibility of rotating a single transmit-receive coil to image the electrical properties of the sample, by emulating an array of 200 transmit-receive coils by time-division multiplexing. Engineering details on the electromechanical design and development of a rotating MIT system are presented. The experimental results indicate that representative images of conductive samples can be obtained at 5 MHz by rotating a single transmit-receive coil. [ABSTRACT FROM AUTHOR]

Magnetic induction tomography (MIT) attempts to image the passive electromagnetic properties (PEP) of an object by measuring the mutual inductances between pairs of coils placed around its periphery. In recent years, there has been an increase in applications of non-contact magnetic induction tomography. When finite element-based reconstruction methods are used, that rely on the inversion of a derivative operator, the large size of the Jacobian matrix poses a challenge since the explicit formulation and storage of the Jacobian matrix could be in general not feasible. This problem is aggravated further in applications for example when the number of coils is increased and in three-dimension. Krylov subspace methods such as conjugate gradient (CG) methods are suitable for such large scale inverse problems. However, these methods require use of the Jacobian matrix, which can be large scale. This paper presents a matrix-free reconstruction method, that addresses the problems of large scale inversion and reduces the computational cost and memory requirements for the reconstruction. The idea behind the matrix-free method is that information about the Jacobian matrix could be available through matrix times vector products so that the creation and storage of big matrices can be avoided. Furthermore the matrix vector multiplications were performed in multiple core fashion so that the computational time can decrease even further. The method was tested for the simulated and experimental data from lab experiments, and substantial benefits in computational times and memory requirements have been observed. [ABSTRACT FROM AUTHOR]

Magnetic induction tomography is an imaging modality which aims to reconstruct the conductivity distribution of the human body. It uses magnetic induction to excite the body and an array of sensor coils to detect the perturbations in the magnetic field. Up to now, much effort has been expended with the aim of finding an efficient coil configuration to extend the dynamic range of the measured signal. However, the merits of different sensor orientations on the imaging performance have not been studied in great detail so far. Therefore, the aim of the study is to fill the void of a systematic investigation of coil orientations on the reconstruction quality of the designs. To this end, a number of alternative receiver array designs with different coil orientations were suggested and the evaluations of the designs were performed based on the singular value decomposition. A generalized class of quality measures, the subclasses of which are linked to both the spatial resolution and uncertainty measures, was used to assess the performance on the radial and axial axes of a cylindrical phantom. The detectability of local conductivity perturbations in the phantom was explored using the reconstructed images. It is possible to draw the conclusion that the proper choice of the coil orientations significantly influences the number of usable singular vectors and accordingly the stability of image reconstruction, although the effect of increased stability on the quality of the reconstructed images was not of paramount importance due to the reduced independent information content of the associated singular vectors. [ABSTRACT FROM AUTHOR]

Magnetic induction tomography (MIT) is an imaging technology that measures changes in the electric properties of a sample located within the imaging region. Measurement of low conductivity contrasts such as biological tissue or ionized water flow in pipelines requires highly accurate systems due to the small amplitude of the measured signals. Optimisation of the sensors results in enhanced MIT performance. Geometric characteristics of MIT sensors impact the intensity of the electromagnetic field, and the inductive coupling between (a) the sensors and (b) the sensors and the medium. Three correlation models are derived to help developers predict the relative performance of MIT systems for a given set of coil characteristics. Bivariate and multiple regression analyses are performed on a dataset from finite element method simulations to validate the relationship between the sensor geometry and three performance parameters for a given set of uniform background distributions. Correlation models are provided for prediction of induced voltage level, eddy currents and system sensitivity relative to the geometric characteristics of the sensors. The performance of the computed models is validated using a dataset of 180 coil designs and four uniform electrical conductivity distributions. Predictions from the developed correlations are compared to reference data from simulations and experiments. Errors estimated for the predicted performance parameters together with the variance for each correlation are presented. The predicted data fitted the reference values within  ±15%, showing reasonable accuracy of the models and a balanced variance-bias trade-off. It was found that the performance of MIT systems is largely affected by the coil dimensions and the number of turns, as well as by the coil shape and wire diameter to a lesser degree. [ABSTRACT FROM AUTHOR]

A magnetic catalyst could be applied in a fluidized bed to improve the catalytic efficiency in the methanation and selective hydrogenation processes. Its distributions play an important role in accelerating the reactions. Electromagnetic tomography (EMT) provides an effective solution for online monitoring of the distribution of a magnetic catalyst. However, most of the EMT systems were developed to investigate the conductivity distribution. A novel EMT for the reconstruction of permeability distribution is presented in this paper. The coils, of which the sensitivity are related to frequency and coil size, were used as receivers in conventional EMT systems. In this paper, a tunneling magnetoresistance (TMR) sensor is applied to take the place of the coil. Compared with coils, the advantages of a TMR sensor on the frequency-independence and spatial resolution were investigated. A coil-TMR array was designed, in which the coil geometry was optimized and the TMR sensor was selected. The sensitivity matrix of the novel system was calculated by the perturbation method in a 3D simulation model. A FPGA-based system was designed. The reconstruction results of the magnetic catalyst validated the practicability of the permeability EMT based on TMR sensors. [ABSTRACT FROM AUTHOR]

Alternative coil designs for single coil magnetic induction tomography are considered in this work, with the intention of improving upon the standard design used previously. In particular, we note that the blind spot associated with this coil type, a portion of space along its axis where eddy current generation can be very weak, has an important effect on performance. The seven designs tested here vary considerably in the size of their blind spot. To provide the most discerning test possible, we use laboratory phantoms containing feature dimensions similar to blind spot size. Furthermore, conductivity contrasts are set higher than what would occur naturally in biological systems, which has the effect of weakening eddy current generation at coil locations that straddle the border between high and low conductivity features. Image reconstruction results for the various coils show that coils with smaller blind spots give markedly better performance, though improvements in signal-to-noise ratio could alter that conclusion. [ABSTRACT FROM AUTHOR]

Magnetic induction tomography (MIT) is a promising technique for continuous monitoring of intracranial hemorrhage due to its contactless nature, low cost and capacity to penetrate the high-resistivity skull. The inter-tissue inductive coupling increases with frequency, which may lead to errors in multi-frequency imaging at high frequency. The effect of inter-tissue inductive coupling was investigated to improve the multi-frequency imaging of hemorrhage. An analytical model of inter-tissue inductive coupling based on the equivalent circuit was established. A set of new multi-frequency decomposition equations separating the phase shift of hemorrhage from other brain tissues was derived by employing the coupling information to improve the multi-frequency imaging of intracranial hemorrhage. The decomposition error and imaging error are both decreased after considering the inter-tissue inductive coupling information. The study reveals that the introduction of inter-tissue inductive coupling can reduce the errors of multi-frequency imaging, promoting the development of intracranial hemorrhage monitoring by multi-frequency MIT. [ABSTRACT FROM AUTHOR]

To improve the image quality of electromagnetic tomography (EMT), a new image reconstruction method of EMT based on a particle filtering algorithm is presented. Firstly, the principle of image reconstruction of EMT is analyzed. Then the search process for the optimal solution for image reconstruction of EMT is described as a system state estimation process, and the state space model is established. Secondly, to obtain the minimum variance estimation of image reconstruction, the optimal weights of random samples obtained from the state space are calculated from the measured information. Finally, simulation experiments with five different flow regimes are performed. The experimental results have shown that the average image error of reconstruction results obtained by the method mentioned in this paper is 42.61%, and the average correlation coefficient with the original image is 0.8706, which are much better than corresponding indicators obtained by LBP, Landweber and Kalman Filter algorithms. So, this EMT image reconstruction method has high efficiency and accuracy, and provides a new method and means for EMT research. [ABSTRACT FROM AUTHOR]

In this paper the shape derivative of an objective depending on the solution of an eddy current approximation of Maxwell’s equations is obtained. Using a Lagrangian approach in the spirit of Delfour and Zolésio, the computation of the shape derivative of the solution of the state equation is bypassed. This theoretical result is applied to magnetic impedance tomography, which is an imaging modality aiming at the contactless mapping (identification) of the unknown electrical conductivities inside an object given measurements recorded by receiver coils. [ABSTRACT FROM AUTHOR]

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. Because of its non-invasive and contactless feature, it becomes an attractive technique for many applications (especially in biomedical area) compared to traditional contact electrode-based electrical impedance tomography. Due to the low contrast in conductivity between biological tissues, an accurate and stable hardware system is necessary. Most MIT systems in the literature employ external signal generators, power amplifiers and highly stable down-conversion electronics to obtain a satisfactory phase measurement. However, this would increase design complexity substantially. In this paper, a National Instrument-based MIT system is developed at the University of Bath, aiming for biomedical applications. The system utilizes National Instrument products to accomplish all signal driving, switching and data acquisition tasks, which ease the system design whilst providing satisfactory performance. This paper presents a full-scaled medical MIT system, from the sensor and system hardware design, eddy current model verification to the image reconstruction software: the performance of this MIT instrumentation system is characterized in detail, including the system accuracy and system stability. The methods of solving eddy current problem are presented. The reconstructed images of detecting the presence of saline solutions are also included in this paper, which show the capability of national instrument products to be developed into a full-scaled biomedical MIT system, by demonstrating the practical experimental results. [ABSTRACT FROM AUTHOR]