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Electrical Capacitance Tomography (ECT) is a well-established industrial process tomography technique. Image reconstruction for the ECT is a nonlinear problem, and the inverse problem is usually ill-posed and ill-conditioned. Hence, the solutions for the ECT are not unique and highly sensitive to the measurement noise. In this paper, a novel tuned fuzzy algorithm is proposed for reconstructing accurate images to monitor the distribution of the multi-phase flow in the industrial process. The proposed algorithm utilizes a Tuned Fuzzy Inference System (TFIS) to overcome the nonlinear characteristics of the ECT system. The optimal parameters of the fuzzy membership functions are obtained using the Particle Swarm Optimization (PSO) technique. In the past few decades, the naturally inspired intelligent swarm algorithms got more attention due to their wide spectrum of research for real-world complex problems optimization. The proposed PSO-tuned fuzzy algorithm is fast since it does not require solving the forward problem to update the sensitivity matrix. Comparing the results with traditional reconstruction algorithms, the proposed algorithm performs better in visual effects and imaging quality, since the image edges and details are better preserved.

Today, in-situ analyzing and monitoring are imperative for ensuring successful and healthy industrial processes in confined environments. With the rapid development of digitization, augmented reality (AR) has been utilized for letting people immersively interact with the necessary information. However, there are still knowledge gaps between AR technique and domain users pertaining to effective analysis of complex data. Hence, new solutions empowering domain users would benefit the whole industry. In this study, we report an initial prototype supporting complex data visualization and analysis in entire 3D surroundings within industrial process tomography (IPT). Microsoft HoloLens 2 is equipped for users to interact with the 3D information characterizing the workflow of the industrial process with high immersion. Our work distinctly improves the performance compared to existing solutions, pointing the way towards how AR should be deployed and developed more efficiently for aiding IPT systems.

Electrical capacitance tomography is an industrial process tomography technology, mainly used to measure and plot two-phase flow and multi-phase flow. The technology is based on the properties of various dielectric constants between the phases of the measured substance. This work focuses on the improvement of particle swarm optimization and intelligent algorithms, especially for the parameter control of particle swarm optimization and intelligent algorithms. The efficiency of group optimization algorithms and intelligent algorithms that solve optimization problems. This paper mainly aims at the image reconstruction process in electrical capacitance tomography system, and proposes an image reconstruction algorithm based on intelligent algorithm and particle swarm algorithm. Combined with the experimental environment of the self-made electrical capacitance tomography system, the actual imaging effect of the algorithm was compared and analyzed with the traditional imaging algorithm, and the verification of the algorithm improvement effect was theoretically completed. According to the finite element analysis method, the internal area of the sensor is subdivided on the entire network, and three flow modes are modeled, which provides conditions for the construction of the following experimental environment. Based on the theory, the principle of the classic Landweber imaging algorithm is discussed in detail. Using the experimental environment with built-in electrical capacitance tomography system, experiments were conducted to visualize the gas–liquid two-phase flow. The traditional Landweber algorithm and imaging algorithm proposed in this paper are used to reconstruct the image using the obtained volume data. Through comparative analysis of the resulting images, the results show that the imaging algorithm proposed in this paper improves the accuracy of flow pattern recognition and image accuracy, which proves the improvement. The feasibility of algorithm and particle swarm algorithm.

Process tomography techniques play an important role in visualizing and monitoring industrial processes, which help to produce high quality product without affecting the work flow in plants. The industrial process tomography techniques, i.e. , electrical tomography and computerized tomography, have been widely applied. Such tomographic tools can be used to investigate various types of multi-phase flows, in which the components may differentiate in density, conductivity, and permittivity. In a gas-liquid-solid flow, however, it is usually difficult for the existing tomographic tools to visualize the distributions of all three phases. In addition, it is necessary to assume some simplifications, i.e. , by viewing two disperse phases as one unified phase. The objective of this research is to provide a dual-modality imaging tool by combining electrical capacitance tomography (ECT) and electromagnetic tomography (EMT). First, an integrated dual-modality sensor was designed and implemented on the same cross-section of the process vessel. Subsequently, dual-modality tomographic measurements were collected by a custom-built multi-channel impedance measurement system. The performance of the dual-modality sensor was verified by numerical simulations and experimental tests, showing that it can produce reliable ECT and EMT measurements at a satisfying signal-to-noise ratio. The complementary tomographic images can be obtained from ECT and EMT, and the distributions of two disperse phases, i.e. , gas and solid phases, can be observed. The preliminary image fusion results were also given by combining the information from both the ECT and EMT images.

Electrical capacitance tomography (ECT) exhibits several attractive features that are important for industrial process tomography applications. These features include low cost, high speed, and nonintrusive nature. However, due to its soft-field character, a relatively low image resolution is an outstanding challenge for ECT. While many efforts have been made to tackle this challenge by improvements in image reconstruction algorithms, relatively less has been done to enhance the basic ECT hardware sensor configuration and data acquisition process. In this paper, a new measurement acquisition strategy is introduced to increase image resolution when using adaptive ECT (AECT). The proposed strategy is based on the manipulation of synthetic electrodes plates (“metaplates”) formed by a set of combined smaller physical electrodes (segments). The synthetic electrodes are sequentially activated with partial overlap of constituent segments to provide a fine-stepped axial and/or azimuthal electronic scan along the entire sensor. Consequently, an increased number of independent capacitance measurements are made available. Reconstruction results using the proposed measurement acquisition strategy (AECT) are shown to illustrate the enhanced resolution and stability in the imaging of objects compared to conventional ECT sensors.

Computed tomography technology uses an electromagnetic radiation source or particulate radiation source, to analyze / study different samples that can range from living organisms to the most diverse objects (rocks, phantoms, etc.). The use of the radioactive materials may cause harm to the operator if he is exposed to the source of radiation, so aiming at the safety of the operator, the objective of this work is to develop an Internet of Things automation system for the opening of the Industrial Process Tomography source port for industrial tomography applications. Thus, this system can drive the stepper motors through this platform can be opened at a safe distance to the operator, avoiding the operator to take radiation dose to perform this operation. For the IPT project, five source ports were made so that each was positioned diametrically opposite each array of detectors. In this project we used 192Ir sources that have activity of 18,500 MBq and that were produced in the reactor IEA-R1, from the neutron bombardment of the pellet containing stable isotope 191Ir. The main characteristics of 192Ir are: half-life of 74.2 days; radiation energy from 0.13 to 0.65 MeV. For the safety of the operator during the opening of the sources, an automated opening system with IoT that can be activated with software installed on the tomography or by a smartphone application by the MQTT protocol, which makes it possible to be monitored in real time at long distance showing the opening and closing status of each source port.

Industrial process tomography (IPT) based process control is an advisable approach in industrial heating processes for improving system efficiency and quality. When using it, appropriate dataflow pipelines and visualizations are key for domain users to implement precise data acquisition and analysis. In this article, we propose a complete data processing and visualizing workflow regarding a specific case—microwave tomography (MWT) controlled industrial microwave drying system. Furthermore, we present the up-to-date augmented reality (AR) technique to support the corresponding data visualization and on-site analysis. As a pioneering study of using AR to benefit IPT systems, the proposed AR module provides straightforward and comprehensible visualizations pertaining to the process data to the related users. Inside the dataflow of the case, a time reversal imaging algorithm, a post-imaging segmentation, and a volumetric visualization module are included. For the time reversal algorithm, we exhaustively introduce each step for MWT image reconstruction and then present the simulated results. For the post-imaging segmentation, an automatic tomographic segmentation algorithm is utilized to reveal the significant information contained in the reconstructed images. For volumetric visualization, the 3D generated information is displayed. Finally, the proposed AR system is integrated with the on-going process data, including reconstructed, segmented, and volumetric images, which are used for facilitating interactive on-site data analysis for domain users. The central part of the AR system is implemented by a mobile app that is currently supported on iOS/Android platforms.

This article describes the implementation of microwave tomography for industrial process applications. Microwave tomography for industrial process imaging has different requirements from that for medical imaging. In addition to spatial resolution, high temporal resolution or real-time imaging is also important for high-speed processes, flows, or rapid reactions. Depending on the specific application, both quantitative imaging and qualitative imaging may be needed. Qualitative imaging would be sufficient to display distributions, patterns, or shapes, which may be adequate for some applications. Quantitative imaging would, however, be more informative, giving images with quantitative dielectric contrast or permittivity values from which other physical parameters, such as density, moisture content, and phase fraction, may be derived. With the microwave tomography approach described, several example applications in industrial processes are demonstrated, and a number of experimental imaging results are presented.

The use of three-dimensional (3D) printing allows for creation of custom models for clinical care, education, and simulation. Medical imaging, given the significant role it plays in both clinical diagnostics and procedures, remains an important area for such education and simulation. Unfortunately, the materials appropriate for use in simulation involving radiographic or ultrasound imaging remains poorly understood. Therefore, our study was intended to explore the characteristics of readily available 3D printing materials when visualized by computed tomography (CT) and ultrasound.Seven 3D printing materials were examined in standard shapes (cube, cylinder, triangular prism) with a selection of printing methods ("open," "whole," and "solid" forms). For CT imaging, these objects were suspended in a gelatin matrix molded to match a standard human CT phantom. For ultrasound imaging, the objects were placed in acrylic forms filled with a gelatin matrix. All images were examined using OsiriX software.Computed tomography imaging revealed marked variation in materials' Hounsfield units as well as patterning and artifact. The Hounsfield unit variations revealed a number of materials suitable for simulation various human tissues. Ultrasound imaging showed echogenicity in all materials, with some variability in shadowing and posterior wall visualization.We were able to demonstrate the potential utility for 3D printing in the creation of CT and ultrasound simulation models. The similar appearance of materials via ultrasound supports their broad utility for select tissue types, whereas the more variable appearance via CT suggests greater potential for simulating differing tissues but requiring multiple printer technologies to do so.

The needs and the feasibility of simultaneous computed tomography (CT) and magnetic resonance imaging (MRI) were recently reported. In this paper, a spiral magnetic resonance X-ray CT (MRX) imaging system is proposed for head and extremities imaging, which serves as a simple, cost-effective solution on the path to a full-scale CT-MRI fusion. While MRI and X-ray radiography were integrated before, we propose novel designs to acquire simultaneous CT and MR views for synchronized radiographic imaging or joint tomographic reconstruction. Our preliminary permanent magnet configurations achieve a magnetic field strength between 0.1 and 0.2 T while keeping weight low enough for portability. We have also shown that a field strength up to 0.35 T is achievable with permanent magnets that maintain a compact profile, though increased weight would hinder ease of transportation. Simulation results of a joint tomographic reconstruction scheme show the advantage of simultaneously acquired images. The proposed MRX system performs double helical scans in CT and MRI mechanisms, and has multiple niche applications, such as medical imaging on disaster sites, in battle fields, and for under-developed regions.

Industrial Process Tomography possesses unique advantages in biphasic medium measurement and has received broad attention in the past decades. Aiming at the widely existed low contrast biphasic medium, this paper proposed a nonlinear Ultrasonic Transmission Tomography (UTT). Approach using continuous wave excitation. Considering the refraction effect at the biphasic interface, the reconstruction method with nonlinear forward problem and the improved Simultaneous Algebraic Reconstruction Technique (SART) is proposed with high reconstruction accuracy and reconstruction speed. The performance of the reconstruction is quantitatively compared with the state-of-art reconstruction algorithms, where the proposed method can reconstruct inclusions with their number, size and position clearly identified. Quantitatively, the average Relative Error (RE) is 0.4835 using the proposed method, which is reduced by 49.34% and 40.57% compared with FBP and SART separately. Under parallel computation, the computing time of the proposed method reduced 16.56 times compared with the existing bent-ray tracing method. The proposed image reconstruction algorithm is proved to be an effective and improved approach to the liquid-liquid two-phase flow ultrasonic tomography.

We investigate the potential of using ultrasonic diffraction tomography technique for characterization of biological tissues. Unlike most of other studies where ultrasonic tomography operates at frequencies higher than 1 MHz, low-frequency tomography uses lower frequencies on the order of 0.3–0.5 MHz. Such a choice is due to low attenuation at these frequencies, resulting in higher precision of input data. In this paper we explore transmission and reflection schemes for both 2D (layer-by-layer) and 3D tomography. We treat inverse tomography problems as coefficient inverse problems for the wave equation. The time-domain algorithms employed for solving the inverse problem of low-frequency tomography focus on the use of GPU clusters. The results obtained show that a spatial resolution of about 2–3 mm can be achieved when operating at the wavelength of about 5 mm even using a stationary 3D scheme with a few fixed sources and no rotating elements. The study primarily focuses on determining the performance limits of ultrasonic tomography devices currently designed for breast cancer diagnosis.

Oil-water biphasic medium widely existed in mining and transportation process of petroleum industry, where visualized measurement processes vital importance in production increase, state monitoring and fault prognosis. Ultrasonic Tomography (UT) is a non-invasive and non-radioactive sensing modality in industrial Process Tomography, which is demonstrated as a competitive monitoring technique with great potential. However, facing the refraction effect of Ultrasound wave at oil-water interfaces, the accuracy of reconstruction algorithm is with large error and serious artifacts. To address the issue, a modified ray-tracing image reconstruction algorithm is proposed. The amplitude attenuation during ultrasound propagation in nonhomogeneous medium is quantitatively modeled to form absolute UT model. With ray tracing strategy applied and improved, the nonlinear refraction effect is characterized in the form of iterative update of sensitivity matrix, followed by which the sound speed mapping transfers reconstructed attenuation images to sound speed distribution for ray tracing computation. Numerical tests indicate that the proposed method significantly improves reconstruction accuracy through projection-based, regularization-based and algebraic-based inverse algorithms, which demonstrate its benefits in conducting oil-water biphasic medium imaging.

Electrical resistance tomography (ERT) and electrical capacitance tomography (ECT) are two established process tomography techniques that can be applied into various indsutries. ERT can monitor the electrical conductivity changes in the process whereas ECT can detect the electrical dielectric materials. Due to their high-speed and low cost features, they are particularly attractive to industrial applications which require real time conditional monitoring. For the past decades, 2D linear back projection (LBP) has been the standard technique for both commercialised ERT and ECT systems because of its simplicity and fast reconstruction speed. In this paper, ITS Plc has released a 'Reconstruction Tool-Suite' software that allows industrial users to utilise different reconstruction algorithms to further understand their processes. Different algorithms are integrated into this software package including the single step Tikhonov method and the iterative Landweber method. In the latest version of the software, the full-field 3D tomography reconstruction scheme is also included, which allows the users to perform 3D reconstruction for their processes. A series of experiments are conducted to validate the pros and cons of different methods.

Tomography is a non-invasive, non-intrusive imaging technique allowing the visualization of phase dynamics in industrial and biological processes. This article reviews progress in Electrical Capacitance Volume Tomography (ECVT). ECVT is a direct 3D visualizing technique, unlike three-dimensional imaging, which is based on stacking 2D images to obtain an interpolated 3D image. ECVT has recently matured for real time, non-invasive 3-D monitoring of processes involving materials with strong contrast in dielectric permittivity. In this article, ECVT sensor design, optimization and performance of various sensors seen in literature are summarized. Qualitative Analysis of ECVT image reconstruction techniques has also been presented.

This chapter focuses on the hardware of current and emerging X-ray computed tomography (CT) systems. First, the basic configuration of industrial cone-beam X-ray CT systems is recalled. Subsequently, individual hardware components, such as sources, detectors and kinematic systems, are described. The chapter continues with an overview of novel developments that expand the application domain of X-ray CT towards, for example, larger objects or fully integrated in-line systems. The chapter is concluded by a description of key safety elements for operation of X-ray CT systems.

We introduce an ultrasonic quantitative imaging method for long bones based on full-waveform inversion. The cost function is defined as the difference in the L 2-norm sense between observed data and synthetic results at a given iteration of the iterative inversion process. For simplicity, and in order to reduce the computational cost, we use a two-dimensional acoustic approximation. The inverse problem is solved iteratively based on a quasi-Newton technique called the Limited-memory Broyden-Fletcher-Goldfarb-Shanno method. We show how the technique can be made to work fine for benchmark models consisting of a single cylinder, and then five cylinders, the latter case including significant multiple diffraction effects. We then show pictures obtained for a tibia-fibula bone pair model. Convergence is fast, typically in 15 to 30 iterations in practice in each frequency band used. We discuss the so-called 'cycle skipping' effect that can occur in such full waveform inversion techniques and make them remain trapped in a local minimum of the cost function. We illustrate strategies that can be used in practice to avoid this. Future work should include viscoelastic materials rather than acoustic, and real data instead of synthetic data.

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.

Since the 1980s, electrical tomographic imaging techniques based on low-frequency capacitance and resistance measurements have been developed for the monitoring of industrial processes and in some cases multiphase flows. Research on microwave tomography for oil and gas multiphase flow imaging began in the mid-1990s, even though the basic principle of microwave tomography was reported a decade earlier for biomedical imaging. In this paper, the development of a microwave tomographic imaging system for such an application since then is overviewed. It is shown by several examples that microwave tomography can effectively reconstruct the images of dielectric objects, moisture distribution inside processed food and oil–gas two-phase flows. It is also shown that the use of higher microwave frequencies would effectively lead to images of higher spatial resolution. Since real-time microwave tomography systems are currently available and ready for industrial applications, the challenges in developing a practical system with higher temporal resolutions suitable for the imaging of high speed multiphase flows in oil industry are highlighted and discussed in both hardware and image reconstruction aspects.

Research Article published by International Journal of Computer Applications Volume 101– No.8, September 2014

Process tomography (PT) techniques have been developed rapidly for visualizing the internal behavior of industrial processes, e.g. multi-phase flow measurement. Most of tomography systems employ a single measurement technique, such as computerized tomography (CT), optical tomography (OT), electrical resistance tomography (ERT) or electrical capacitance tomography (ECT). It is now possible to fit two or more tomographic systems to an industrial process. Detailed information from different modalities can be gained by inspection of separate tomographs, and the advantage of the strongest features provided by each unit can be taken. A combined tomogram can be produced of superior quality to any of the separate tomograms. To maximize the information available from the combined tomographic system, data fusion is the better option. In this paper, a dual-mode tomography system based on capacitance sensor and gamma sensor was developed to capture oil–gas two-phase flow. The two modalities can work at the same time. Two fusion methods, namely image fusion method and data fusion method, are proposed. Both simulation and static experiments for oil–gas two-phase flow were conducted. The reconstruction results of different fusion methods and modalities were compared and discussed.

The image of the current non-destructive testing system using a high energy accelerator is limited to conventional two-dimensional metaphysical information. Requirements for the present manufacturing industry are growing rapidly and include quantitative measurements, high-density component model extraction, reverse process development and precision inspection to meet the needs for the verification of manufactured goods. Therefore, industrial three-dimensional high-penetration tomography has emerged as the most promising method. In this study, in order to evaluate the applicability of a MeV-level high-energy accelerator, we developed a three-dimensional tomography system using a 450 kV X-ray generator. Evaluation of the three-dimensional tomography image is based on measurements of the penetration and the image resolution for high-energy X-rays.

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.

The tomographic imaging of process parameters for oil-gas-water three-phase flow can be obtained through different sensing modalities, such as electrical resistance tomography (ERT) and electrical capacitance tomography (ECT), both of which are sensitive to specific properties of the objects to be imaged. However, it is hard to discriminate oil, gas and water phases merely from reconstructed images of ERT or ECT. In this paper, the feasibility of image fusion based on ERT and ECT reconstructed images was investigated for oil-gas-water three-phase flow. Two cases were discussed and pixel-based image fusion method was presented. Simulation results showed that the cross-sectional reconstruction images of oil-gas-water three-phase flow can be obtained using the presented methods.

As a rather new technology, X-Ray Computed Tomography offers new and promising possibilities in manufacturing metrology in comparison to well-established tactile or optical measurements. The main benefit is the volumetric model which results of each measurement and represents the measurement object holistically with high point density.

Electrical Capacitance Tomography (ECT) is a non- invasive and non-destructive imaging technique that uses electrical capacitance measurements at the periphery of an object to generate map of dielectric permittivity of the object. This visualization method is a relatively mature industrial process tomography technique, especially in 2D imaging mode. Volumetric ECT is a new method that poses major computational challenges in image reconstruction and new challenges in sensor design. This paper shows a nonlinear image reconstruction method for 3D ECT based on a validated forward model. The method is based on the flnite element approximation for the complete sensor model and the solution of the inverse problem with nonlinear iterative reconstruction. The nonlinear algorithm has been tested against some complicated experimental test cases, and it has been demonstrated that by using an improved forward model and nonlinear inversion method, very complex shaped samples can be reconstructed. The reconstruction of very complex geometry with objects in the shape of letters H, A, L and T is extremely promising for the applications of 3D ECT.

Various tomographic techniques such as electrical capacitance, electrical resistivity, MRI, X-ray/gamma-ray tomography have been reviewed with special emphasis on applicability for the industrial set-ups are discussed. It was found that gamma-ray tomography is most suitable technique which could be used for industrial set-ups. Gamma-ray tomography was also applied for variety of industrial equipment, such as paddle bed dryer, packed distillation column, to explore the possibility of their use for diagnosis of unidentified problems. From the preset work it is recommended to undertake tomographic scanning of critical equipments periodically to enhance the efficiency and reduce possible downtime.

Electrical impedance tomography (EIT) seeks to image the electrical conductivity of an object using electrical impedance measurement data at its periphery. Ultrasound reflection tomography (URT) is an imaging modality that is able to generate images of mechanical properties of the object in terms of acoustic impedance changes. Both URT and EIT have the potential to be used in various medical applications. In this paper we focus on breast tumour detection. Both URT and EIT belong to soft field tomography and suffer from the small amounts of available data and the inherently ill-posed nature of the inverse problems. These facts result in limited achievable reconstruction accuracy and resolution. A dual bio-electromechanical tomography system using ultrasound and electrical tomography is proposed in this paper to improve the detection of the small-size tumour. Data fusion techniques are implemented to combine the EIT/URT data. Based on simulations, we demonstrate the improvement of detection of small size anomalies and improved depth detection compared to single modality soft field tomography.

Process tomography (PT) techniques have been developed rapidly for visualising the internal behaviour of industrial processes. Most tomography systems employ a single measurement technique, such as Electrical Resistance Tomography (ERT) or Electrical Capacitance Tomography (ECT). Although single-modality process tomography systems provide sufficient information for some applications, in other applications, e.g. three-phase flow, additional information is required. In fact, many industrial processes are complex and contain multiple components, which require multiple measurement techniques to individually quantify them. To facilitate this process, a multi-modal process tomography system must allow individual modality data to be collected and combined effectively. This paper describes opportunities for rationalisation and sharing of resources that have been exploited to create a dual-modality tomography system.

This article presents and compares analytical and numerical methods for electrical property retrievals that are developed recently in our research group. The methods create electrical property maps of human body only on the basis of typical data from magnetic resonance imaging (MRI) (without using any additional devises or data). Derivations and results are included. Analysis and comparison of the methods are presented.

X-ray computed tomography (XCT) with flat-panel matrix detectors is a promising non-destructive method to scan and characterize external and internal structures of a specimen. Using XCT, both size and topology of different types of heterogeneities may vary largely. The different size scales of the heterogeneities and of the affected material volume require appropriate tomographic methods, scanning geometries and resolutions. In order to quantify features of interest from XCT scans, a major challenge is still found in the analysis and visualization of the generated XCT data: Advanced 3D-image processing techniques are needed for robust extraction and characterization of each single feature of interest. Interactive visualization techniques are needed for further exploration and analysis of these increasingly complex data spaces in order to provide novel insights for domain specialists. As examples of how image processing and visualization complement XCT various application cases are presented.

Electrical tomography technology is a kind of process tomography technology. It is accompanied by the development of computer technology and sensor technology. Electrical resistance tomography is a kind of mode of electrical tomography. It has some excellent characteristics that are non-invasive, portable, l ow cost and fast response etc. In this paper, the system of ERT unit are introduced. Mainly summarized the application of ERT system in the measurement of multiphase flow, medicine, the concrete structure detection and other aspects.

Dual-modality imaging is a technique in which computed tomography (CT) or magnetic resonance imaging is combined with positron emission tomography or single-photon emission CT to acquire structural and functional images with an integated system. The data are acquired in a single procedure; the patient remains on the scanner table while undergoing both x-ray and radionuclide studies to facilitate correlation between the structural and functional images. The resulting data can aid in localization, enabling more specific diagnosis than can be obtained with a conventional imaging study. In addition, the anatomic information can be used to compensate the correlated radionuclide data for physical perturbations such as photon attenuation, scatter radiation, and partial volume errors. Thus, dual-modality imaging provides a priori information that can improve both the visual quality and the quantitative accuracy of the radionuclide images. Dual-modality imaging systems are also being developed for biologic research involving small animals. Small-animal dual-modality systems offer advantages for measurements that currently are performed invasively with autoradiography and tissue sampling. By acquiring data noninvasively, dual-modality imaging permits serial studies in a single animal, enables measurements to be performed with fewer animals, and improves the statistical quality of the data.

Hyperthermia has proven to be beneficial to treating superficial malignancies, particularly chest wall recurrences of breast cancer. During hyperthermia, monitoring the time–temperature profiles in the target and surrounding areas is of great significance for the effect of therapy. An ultrasound-based temperature imaging method has advantages over other approaches. When the temperature around the tumor is calculated by using the propagation speed of ultrasound, there always exist overshoot artifacts along the boundary between different tissues. In this paper, we present a new method combined with empirical mode decomposition (EDM), similarity constraint, and continuity constraint to optimize the temperature images. Simulation and phantom experiment results compared with those from our previously proposed method prove that the EMD-based method can build a better temperature field image, which can adaptively yield better temperature images with less computation for assistant medical treatment control.

In a first pilot study with 3D Ultrasound Computer Tomography especially the speed of sound images of the breast showed promising results for breast cancer detection. Yet, the resolution of transmission tomography in our system is limited in comparison to the reflectivity volumes. In this paper we describe a setup for an improved device overcoming this limitation. An optimized geometry of the transducers in a sparse distribution improves both the contrast in reflection and contrast and resolution in transmission tomography by nearly an order of magnitude. Furthermore data acquisition is accelerated from 10 to less than 2 minutes. The derived methods, simulation, and measuring results are described.

This paper presents a reconstruction method for a conveyor belt X-ray scanning geometry, consisting of a static X-ray source/detector system and an object in uniform motion. Applying conventional reconstruction methods to data acquired in this geometry leads to severe artefacts. We show that by incorporating prior knowledge of the material as well as domain specific knowledge, such artefacts can be largely reduced. This is done by combining concepts of discrete tomography with the expected object domain.

In this chapter, we briefly recall the theory of non-commutative tomography in a pedagogical way. We then consider its applications to signal analysis. The advantages and drawbacks of these techniques to finite samples of data are discussed. Then the method is applied, first to signals originating from reflectometry measurements in magnetized fusion plasmas, and then to data obtained from the advection of tracers in a two-dimensional time-dependent flow generated by three point vortices. In the first case, we show that the tomogram allows to pick a base to represent our signal which has the advantage of isolating the reflection coming from the plasma and then to improve the estimation of the density profile. In the second case, we show how, with a "tricky transformation" the method allows us to detect Lévy flights and extract some of their properties.

Transient three-dimensional multiphase flows are a characteristic feature of many industrial processes. The experimental observations and measurements of such flows are extremely difficult, and industrial process tomography has been developed over the last decade into a reliable method for investigating these complex phenomena. Gas-solids flows, such as those in pneumatic conveying systems, exhibit many interesting features and these can be successfully investigated by using electrical capacitance tomography. This paper discusses the current state of the art in this field, advantages and limitations of the technique and required future developments. Various levels of visualization and processing of tomographic data obtained in a pilot-plant-scale pneumatic conveying system are presented. A case study outlining the principles of measuring the mass flow rate of solids in a vertical channel is shown.

This paper is concerned with the development of a novel light source which aids the study of the optoelectronic properties of amorphous semiconductors as optical sensors for process tomography. The light source is an integral part of a prototype industrial process tomographic system which is being developed for the detection and imaging of multiphase flows. In this paper, the design, assembly and performance of the light source are discussed in detail. Findings of the research into the suitability of amorphous semiconductors for industrial process tomography will be presented at a later stage in a subsequent paper.

This paper describes an investigation into the use of optical-fibre sensors in a tomographic measurement system, designed to measure the flow of dry solids in gravity-drop and pneumatic conveyors. A simple model of the system is provided and used to predict the response of both individual sensors and the full system. Results are provided which show that the model is acceptable. The system is used to provide tomographic images of solid concentration within a gravity conveyor.

This paper focuses on the application of 3D X-ray Computed Tomography (CT) to precisely detect and confirm semiconductor internal physical defects without the need to decapsulate the sample. Equipped with advanced technologies and innovations, today's X-ray machine is capable of reconstructing the two-dimension (2D) sliced images to form 3D images and videos in much shorter time. With the introduction of 3D X-ray CT designed for electronics field, failure mechanisms once only visible after destructive analysis can now be revealed in non-destructive way. The technique not only saves cost, it shortens the turnaround time tremendously and allows customer's response and relevant improvement actions to be taken more efficiently.

Electrical impedance tomography (ET) is a technique for reconstructing conductivity of an inhomogeneous medium by injecting current at the boundary of an object and measuring the resulting voltage changes. ET techniques have been widely adopted for visualizing distributions of materials in industrial processes. In comparison to other tomography modalities, ET's advantages include low cost, rapid response, no radiation and being non-intrusive. In this paper, a group of most widely adopted electrical imaging algorithms are compared based on imaging time, correlation coefficient, the relative error, the objective function value, iterative times and convergence speed in a visualization tool OPTICS. Experiment results show the applicable ranges, limitations and complementary natures of different imaging algorithms.

This paper presents a tomographic system at 100 GHz for imaging based on MST technique. At 100 GHz, a good compromise is obtained between penetration and reso- lution for biomedical and non-destructive testing applications. Moreover, this system just requires low frequency wiring and reduces the RF equipment necessary for performing real-time imaging. The system has been built and successfully validated with a set of measurements for a canonical scenario.

Partial volume effects (PVE) in nuclear imaging blur contours and decrease intensity in small tissues. Among the methodologies considered for PVE correction, a new voxel-wise mutual multi-resolution approach (MMA) was recently introduced. MMA is based on the extraction and transformation of high resolution details from an anatomical image (MR or CT) and their subsequent incorporation into a low-resolution image (PET or SPECT). This voxel-wise approach allows lacking details of the low-resolution image to be reconstructed as well as contours and intensities to be recovered. However, artifacts may be introduced due to the required global linear correlation between both modalities and the current 2D implementation whereas PVE is a 3D phenomenon. The aim of the present study was to assess a new model, designed to overcome these two issues. A 3D wavelet decomposition process was built to replace the 2D global linear model with a 3D local analysis using a moving window. The algorithm was validated on synthetic and simulated images, and its performance was compared to the previous approach. The obtained quantitative correction was found to be similar to the 2D global correction in correlated cases whereas in the uncorrelated cases such as whole body or brain analysis, the new model outperforms the 2D approach without artefacts and with improved visual and quantitative correction.

With the advent of more sophisticated and powerful imaging instruments using a variety of radiant energy forms, numerous improvements have been made to the basic tomographic techniques. These improvements enable greater specificity and sensitivity in clinical diagnostic and basic investigative imaging procedures. Modern medical imaging modalities, which include magnetic resonance imaging (MRI), positron emission tomography (PET), single photon emission computed tomography (SPECT), ultrasound, and x-ray CT, have revolutionized diagnostic capabilities. Medical professionals are now provided with significant capabilities for noninvasive and accurate examination of internal anatomy. These modern imaging modalities can capture not only anatomical information but also physiological, metabolic, and functional information. Keywords: magnetic resonance imaging (MRI); X ray ultrasound; computed tomography (CT); positron emission tomography; single photon emission computed tomography (SPECT)

This paper proposes 4-D EIT image reconstuction for functional EIT measurements. The approach directly accounts for 3-D interslice spatial correlations and temporal correlations between images in successive data frames. Image reconstruction is posed in terms of an augmented image ~ and measurement vector ~, which concatenate the values from the d previous and future frames. Images reconstruction is then based on an augmented regularization matrix ~, which accounts for a model with 4-D correlations of image elements, interslices and temporal frames. The temporal correlation matrix is objectively calculated from measurement data. Results of simulations are compared by reconstruction algorithms based on conventional 3-D and proposed 4-D priors.