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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.

As a generic 'tool' electrical impedance tomography (EIT) is useful in improving the modelling and design of many complex processes and for process control (Williams R A and Beck M S 1995 Process Tomography: Principles, Techniques and Applications (Woburn, MA: Butterworth Heinemann) pp 11?25, Neuffer D, Alvarez A, Owens D H, Ostrowski K L, Luke S P and Williams R A 1999 Proc. 1st World Congr. on Industrial Process Tomography (Buxton, UK) pp 71?7). However, existing developments of the EIT technique are only applicable to aqueous-based fluids that possess continuous admittance property (Xie C G, Reinecke N, Beck M S, Mewes D and Williams R A 1994 Process Tomography?A Strategy for Industrial Exploitation ed M S Beck pp 25?32). For example, it would not be suitable for a stratified flow or an intermittent flow in a horizontal channel or large bubble formation and foams since some of the electrodes may lose contact with the conductive fluid. The paper reports a preliminary study of a novel sensor and apparatus, which seeks to address some significant shortcomings in EIT application through use of a new sensing strategy and apparatus for measuring complex multiphase flows, such as oil/gas/water flow or bubble formation and foams. The major feature of the sensing system is to employ a single conductive ring as a tomographic sensor instead of a number of electrodes as in conventional EIT. The strategy facilitates a more homogeneous sensitivity distribution throughout the sensing domain of the conductive ring, which is less affected by the contact area or geometry of electrodes than in previous EIT systems. The sensor can be conveniently constructed as a flange-based flow sensor, if required, without the need to drill holes in the pipe wall. Therefore, it provides a realistic way to measure the dynamic changes of flowing fluids. The novel methodology is believed to offer a significant advance in enabling a more flexible and robust EIT system to be devised for on-line measurement and control of flow in oil, pharmaceuticals and food industries.

Methods of optical tomography of biological tissues are considered, which include pulse-modulation and frequency-modulation tomography, diffusion tomography with the use of cw radiation sources, optical coherent tomography, speckle-correlation tomography of nonstationary media, and optoacoustic tomography. The method for controlling the optical properties of tissues is studied from the point of view of increasing a probing depth in optical coherent tomography. The modern state and prospects of the development of optical tomography are discussed.

Electromagnetic flow meters have succesfully been used in many industries to measure the mean flow velocity of conductive liquids. This technology works reliably in single phase flows with axisymmetric flow profiles but can be inaccurate with asymmetric flows, which are encountered, for example, in multiphase flows, pipe elbows and T-junctions. Some computational techniques and measurement devices with multiple excitation coils and measurement electrodes have recently been proposed to be used in cases of asymmetric flows. In earlier studies, we proposed a computational approach for electromagnetic flow tomography (EMFT) for estimating velocity fields utilizing several excitation coils and a set of measurement electrodes attached to the surface of the pipe. This approach has been shown to work well with simulated data but has not been tested extensively with real measurements. In this paper, an EMFT system with four excitation coils and 16 measurement electrodes is introduced. The system is capable of using both square wave and sinusoidal coil current excitations and all the coils can be excited individually, also enabling parallel excitations with multiple frequencies. The studies undertaken in the paper demonstrate that the proposed EMFT system, together with the earlier introduced velocity field reconstruction approach, is capable of producing reliable velocify field estimates in a laboratory environment with both axisymmetric and asymmetric single phase flows.

International audience; Magnetic resonance electric properties tomography is a non-destructive imaging modality that maps the spatial distribution of the electrical conductivity and permittivity of the human body using standard clinical magnetic resonance imaging systems. From the B+1 magnetic field maps and the local form of the Maxwell equations, several schemes have been derived to provide direct approximated formulas but they suffer from instabilities. In this paper, we propose to address it as an inverse problem solved by a constrained optimization algorithm where we exploit the weak formulation of the electric Helmholtz equation and a Lagrangian approach. We derive the associated adjoint field equation and employ a quasi-Newton minimization scheme. We also take advantage of a regularisation strategy based on geometrical a priori information for defining large zones into which the electric parameters are known to be piece-wise constant.

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.

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.

The aim of medical imaging is to provide in an non - invasive way morphological information about a human patient. The information is obtained by performing an ” experiment ” where the interaction of a source of radiation anf the tissue under consideration is measured. From the measured data the desired information has to be computed, hence we face an inverse problem. It is always ill - posed in the sense that small errors in the data can be amplified to large changes in the reconstruction. For developing efficient and stable software we have to study the mathematical model; i. e., the description of the experiment based on physical and engeneering knowledge. In optimal situations it is possible to derive” inversion formulas” which relate in a constructive way the data to the searched - for information. Reconstruction algorithms can be found by discretisizing these formulas. But of course we have to perform a stability analysis in order to design the software such that the influence of the data noise is reduced as much as possible. If such inversion formulas are unknown or cannot be discretisized in an accurate way direct discretization and iterative methods are used for the computation.

Industrial process tomography remains a multidisciplinary field with considerable interest for many varied participants. Indeed this adds greatly to its appeal. It is a pleasure and a privilege to once again act as guest editor for a special feature issue of Measurement Science and Technology on industrial process tomography, the last being in December 2002. Those involved in the subject appreciate the efforts of Measurement Science and Technology in producing another issue and I thank the journal on their behalf. It can be seen that there are considerable differences in the composition of material covered in this issue compared with previous publications. The dominance of electrical impedance and electrical capacitance techniques is reduced and there is increased emphasis on general utility of tomographic methods. This is encompassed in the papers of Hoyle and Jia (visualization) and Dierick et al (Octopus). Electrical capacitance tomography has been a core modality for industrial applications. This issue includes new work in two very interesting aspects of image reconstruction: pattern matching (Takei and Saito) and simulated annealing (Ortiz-Aleman et al). It is important to take advantage of knowledge of the process such as the presence of only two components, and then to have robust reconstruction methods provided by pattern matching and by simulated annealing. Although crude reconstruction methods such as approximation by linear back projection were utilized for initial work on electrical impedance tomography, the techniques published here are much more advanced. The paper by Kim et al includes modelling of a two-component system permitting an adaption-related approach; the paper by Tossavainen et al models free surface boundaries to enable the estimation of shapes of objects within the target. There are clear improvements on the previous crude and blurred reconstructions where boundaries were merely inferred rather than estimated as in these new developments. Interest in magnetic induction tomography has evolved recently and I am pleased to note the inclusion of new work in that modality by Casanova et al. Note that this work also makes full use of prior information to improve reconstruction results. A modality that is relatively new to industrial applications is featured by Holstein et al, namely acoustic tomography. The novelty is provided by using measurements of the speed of sound in gas (air) to identify temperature distributions. Two well chosen applications illustrate the technique. Hard-field tomography, that is the modalities of x-ray and gamma-ray tomography, has always been of interest for some industrial applications. Often this has been for the high resolution of reconstructions available with these techniques, but there application has been restricted due to concerns about use of ionizing radiation. Cattle et al include an application to a process where the material to be imaged is a gamma emitter, i.e. only passive sources are used. The novelty here is that both source and attenuation information is used concurrently to obtain reconstructions. I thank the authors for a fascinating collection of papers that reflect current interest in the subject of industrial process tomography.

We are pleased to publish this special feature on the Sixth World Congress on Industrial Process Tomography (WCIPT6) in Measurement Science and Technology. The international congress was successfully held in the campus of Beihang University, Beijing, China, from 6–9 September 2010. It was jointly organized by International Society for Industrial Process Tomography (ISIPT), North China Electric Power University (NCEPU) and Beihang University (BUAA). Process tomography is a tangible tool to visualize and determine the material distribution inside a process non-intrusively in real time. The internal features that can be monitored by process tomography are frequently encountered and required in the design of processes and industrial plants in the fields of chemical, oil, power and metallurgical engineering as well as many other activities such as food, material handling and combustion systems. One of the key characteristics of process tomography is to provide a direct impression and instant and clear understanding of a complex phenomenon. From the viewpoint of practical applications, industries all over the world are currently facing a number of daunting challenges including many wide-range and complex technical problems. The innovative technology of process tomography consistently contributes to providing better and better solutions to the problems as 'seeing is believing'. As a regular event, WCIPT is playing a more and more important role in addressing the challenges to overcome these problems. We are glad to see that this special feature provides a great opportunity for world-wide top-level researchers to discuss and make further developments in process tomography and its applications. The 20 articles included in this issue cover a wide range of relevant topics including sensors and sensing mechanisms, data acquisition systems and instrumentation, electrical, optical, acoustic and hybrid systems, image reconstruction and system evaluation, data and sensor fusion, data processing, other emerging technologies, and their industrial applications such as in multi-phase systems, combustion and chemical reaction, etc. The Seventh World Congress on Industrial Process Tomography (WCIPT7) will take place in Krakow, Poland, from 2–5 September 2013. We look forward to meeting you in Poland!

Analysis of electrical resistance tomography (ERT) data using least-squares regression modelling in industrial process tomographs has been tested. Potential differences measured between electrodes in rings have been used to carry out the regression modelling to investigate the location and size of a disturbance present in the system. Extensive experiments have been carried out with ERT to test a suitable regression algorithm to extract the disturbance. Current analysis has been performed for a single disturbance known to be present in the system. For the environment considered, the least-squares regression reported in this paper demonstrates an alternative approach for analysis of tomography data in industrial applications. The position (concentric or off-centre) and the size of the disturbance (in concentric cases) can be well defined by the reported regression modelling approach. However, it is still a challenge to define the size of the off-centre disturbance.

There are many different electrical impedance tomography (EIT) systems which are either non-commercial (in-house products) or commercial products. However, these systems are usually designed for specific applications and therefore the functionality of the systems might be limited. Nowadays there are commercially available many low-cost, efficient and accurate multifunctional components for data acquisition and signal processing. Therefore, it should be possible to construct an EIT system which is mainly built from commercially available components. The main goal of this work was to study the performance of a PXI-based EIT system. In this work, a PXI-based EIT system with 16 independent current injection channels and 80 independent measurement channels was constructed and tested. The results indicate that an EIT system can be constructed using a PXI platform which decreases the construction time of the system. Moreover, the system is efficient, accurate, modular, and it is not limited to any predetermined measurement protocols.

There has been tremendous development within measurement science and technology over the past couple of decades. New sensor technologies and compact versatile signal recovery electronics are continuously expanding the limits of what can be measured and the accuracy with which this can be done. Miniaturization of sensors and the use of nanotechnology push these limits further. Also, thanks to powerful and cost-effective computer systems, sophisticated measurement and reconstruction algorithms previously only accessible in advanced laboratories are now available for in situ online measurement systems. The process industries increasingly require more process-related information, motivated by key issues such as improved process control, process utilization and process yields, ultimately driven by cost-effectiveness, quality assurance, environmental and safety demands. Industrial process tomography methods have taken advantage of the general progress in measurement science, and aim at providing more information, both quantitatively and qualitatively, on multiphase systems and their dynamics. The typical approach for such systems has been to carry out one local or bulk measurement and assume that this is representative of the whole system. In some cases, this is sufficient. However, there are many complex systems where the component distribution varies continuously and often unpredictably in space and time. The foundation of industrial tomography is to conduct several measurements around the periphery of a multiphase process, and use these measurements to unravel the cross-sectional distribution of the process components in time and space. This information is used in the design and optimization of industrial processes and process equipment, and also to improve the accuracy of multiphase system measurements in general. In this issue we are proud to present a selection of the 145 papers presented at the 5th World Congress on Industrial Process Tomography in Bergen, September 2007. Interestingly, x-ray technologies, one of the first imaging modalities available, keep on moving the limits on both spatial and temporal measurement resolution; experimental results of less than 100 nm and several thousand frames/s are reported, respectively. Important progress is demonstrated in research and development on sensor technologies and algorithms for data processing and image reconstruction, including unconventional sensor design and adaptation of the sensors to the application in question. The number of applications to which tomographic methods are applied is steadily increasing, and results obtained in a representative selection of applications are included. As guest editors we would like express our appreciation and thanks to all authors who have contributed and to IOP staff for excellent collaboration in the process of finalizing this special feature.

A large number of non-invasive measurement techniques have been developed and some have reached high levels of sophistication particularly in the medical field. The author reviews these techniques with a brief explanation of basic principles followed by examples from a broad spectrum of applications. The methods covered include ultrasonic, thermal, optical, radiation and nuclear methods, nuclear magnetic resonance and various imaging techniques based on them. The latter include computer-aided tomography, NMR imaging and positron emission tomography.