Manuchehr Soleimani

Four-dimensional electrical capacitance tomography imaging using experimental data

Electrical capacitance tomography (ECT) is a relatively mature non-invasive imaging technique that attempts to map dielectric permittivity of materials. ECT has become a promising monitoring technique in industrial process tomography especially in fast flow visualization. One of the most challenging tasks in further development of ECT for real applications are the computational aspects of the ECT imaging. Recently, 3D ECT has gained interest because of its potential to generate volumetric images. Computation time of image reconstruction in 3D ECT makes it more difficult for real time applications. In this paper we present a robust and computationally efficient 4D image reconstruction algorithm applied to real ECT data. The method takes advantage of the temporal correlation between 3D ECT frames to reconstruct movies of dielectric maps. Image reconstruction results are presented for the proposed algorithms for experimental ECT data of a rapidly moving object.

Medical Imaging and Physiological Modelling: Linking Physics and Biology

Medical image analysis is increasingly providing a sophisticated set of tools for processing measurement inputs into clinically relevant outputs, although this is, on the whole, completed without consideration of the underlying physiology. In contrast, physiological modelling provides a predictive tool based on a physical and biological understanding of the underlying processes. In this editorial, we discuss the possibility of integrating physiological modelling data with medical images and measurements with the goal of providing new types of physiologically meaningful information with increased clinical relevance.

Simultaneous Reconstruction of Permeability and Conductivity in Magnetic Induction Tomography

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. It has been shown that the MIT data contain information that can be used to reconstruct all PEP parameters. In general PEP includes complex conductivity and permeability. This paper presents an image reconstruction technique in which conductivity and permeability are calculated by an inverse edge finite element scheme. The simultaneous reconstruction presented here will enhance scope of application of MIT technique.

Three-Dimensional Magnetic Induction Tomography Imaging Using a Matrix Free Krylov Subspace Inversion Algorithm

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 flnite 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 beneflts in computational times and memory requirements have been observed.

A trust region subproblem for 3D electrical impedance tomography inverse problem using experimental data

Image reconstruction in electrical impedance tomography (EIT) is an ill-posed nonlinear inverse problem. Regularization methods are needed to solve this problem. The results of the ill- posed EIT problem strongly depends on noise level in measured data as well as regularization parameter. In this paper, we present trust region subproblem (TRS), with the use of L-curve maximum curvature criteria to flnd a regularization parameter. Currently Krylov subspace methods especially conjugate gradient least squares (CGLS) are used for large scale 3D problem. CGLS is an e-cient technique when the norm of measured noise is exactly known. This paper demonstrates that CGLS and TRS converge to the same point on the L-curve with the same noise level. TRS can be implemented e-ciently for large scale inverse EIT problem as CGLS with no need a priori knowledge of the noise level.

Volumetric magnetic induction tomography

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.

Electromagnetic Tomography for Medical and Industrial Applications: Challenges and Opportunities [Point of View]

MITs (magnetic induction tomography) low-cost and noninvasive features can offer great excitement and potential to address many challenging problems that exist in the current industrial/medical applications. The foundation development of MIT has been made in the past ten years. Many more advancements can be expected in the next decade, including the first commercialized MIT system for industrial or medical application. It will certainly contribute some impact to the current imaging technology.

Hardware and software design for a National Instrument-based magnetic induction tomography system for prospective biomedical applications

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.

Unscented Kalman filter approach to tracking a moving interfacial boundary in sedimentation processes using three-dimensional electrical impedance tomography

The monitoring of solid–fluid suspensions under the influence of gravity is widely used in industrial processes. By considering sedimentation layers with different electrical properties, non-invasive methods such as electrical impedance tomography (EIT) can be used to estimate the settling curves and velocities. In recent EIT studies, the problem of estimating the locations of phase interfaces and phase conductivities has been treated as a nonlinear state estimation problem and the extended Kalman filter (EKF) has been successfully applied. However, the EKF is based on a Gaussian assumption and requires a linearized measurement model. The linearization (or derivation of the Jacobian) is possible when there are no discontinuities in the system. Furthermore, having a complex phase interface representation makes derivation of the Jacobian a tedious task. Therefore, in this paper, we explore the unscented Kalman filter (UKF) as an alternative approach for estimating phase interfaces and conductivities in sedimentation processes. The UKF uses a nonlinear measurement model and is therefore more accurate. In order to justify the proposed approach, extensive numerical experiments have been performed and a comparative analysis with the EKF is provided.

Pipeline inspection using magnetic induction tomographybased on a narrowband pass filtering method

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 flltering 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 indentifles these damages. The method has been verifled using experimental data from very challenging test samples. It is well known that using a coil array with an imaging region of 100mm the PBRM based MIT can retrieve information with accuracy of about 10mm (about 10%). With proposed NPFM the information on a resolution of 2mm (which is about 2%) can be detected using the same measurement data.