Dual-Modal Electrical Imaging of Two-Phase Flow-Experimental Evaluation of the State Estimation Approach.

Accurate measurement of two-phase flow quantities is essential for managing production in many industries. However, the inherent complexity of two-phase flow often makes estimating these quantities difficult, necessitating the development of reliable techniques for quantifying two-phase flow. In this paper, we investigated the feasibility of using state estimation for dynamic image reconstruction in dual-modal tomography of two-phase oil-water flow. We utilized electromagnetic flow tomography (EMFT) to estimate velocity fields and electrical tomography (ET) to determine phase fraction distributions. In state estimation, the contribution of the velocity field to the temporal evolution of the phase fraction distribution was accounted for by approximating the process with a convection-diffusion model. The extended Kalman filter (EKF) and fixed-interval Kalman smoother (FIKS) were used to reconstruct the temporally evolving velocity and phase fraction distributions, which were further used to estimate the volumetric flow rates of the phases. Experimental results on a laboratory setup showed that the FIKS approach outperformed the conventional stationary reconstructions, with the average relative errors of the volumetric flow rates of oil and water being less than 4%. The FIKS approach also provided feasible uncertainty estimates for the velocity, phase fraction, and volumetric flow rate of the phases, enhancing the reliability of the state estimation approach.

A Review on Fast Tomographic Imaging Techniques and Their Potential Application in Industrial Process Control.

With the ongoing digitalization of industry, imaging sensors are becoming increasingly important for industrial process control. In addition to direct imaging techniques such as those provided by video or infrared cameras, tomographic sensors are of interest in the process industry where harsh process conditions and opaque fluids require non-intrusive and non-optical sensing techniques. Because most tomographic sensors rely on complex and often time-multiplexed excitation and measurement schemes and require computationally intensive image reconstruction, their application in the control of highly dynamic processes is often hindered. This article provides an overview of the current state of the art in fast process tomography and its potential for use in industry.

Model reduction in acoustic inversion by artificial neural network.

In ultrasound tomography, the speed of sound inside an object is estimated based on acoustic measurements carried out by sensors surrounding the object. An accurate forward model is a prominent factor for high-quality image reconstruction, but it can make computations far too time-consuming in many applications. Using approximate forward models, it is possible to speed up the computations, but the quality of the reconstruction may have to be compromised. In this paper, a neural network-based approach is proposed that can compensate for modelling errors caused by the approximate forward models. The approach is tested with various different imaging scenarios in a simulated two-dimensional domain. The results show that with fairly small training datasets, the proposed approach can be utilized to approximate the modelling errors, and to significantly improve the image reconstruction quality in ultrasound tomography, compared to commonly used inversion algorithms.

System Identification of Conveyor Belt Microwave Drying Process of Polymer Foams Using Electrical Capacitance Tomography.

The microwave drying process has a wide application in industry, including drying polymer foams after the impregnation process for sealings in the construction industry. The objective of the drying process is to reach a certain moisture in the foam by adjusting the power levels of the microwave sources. A moisture controller can be designed to achieve this goal; however, a process model is required to design model-based controllers. Since complex physics governs the microwave drying process, system identification tools are employed in this paper to exploit the process input and output information and find a simplified yet accurate model of the process. The moisture content of the foam that is the process output is measured using a designed electrical capacitance tomography (ECT) sensor. The ECT sensor estimates the 2D permittivity distribution of moving foams, which correlates with the foam moisture. Experiments are conducted to collect the ECT measurements while giving different inputs to the microwave sources. A state-space model is estimated using one of the collected datasets and is validated using the other datasets. The comparison between the model response and the actual measurements shows that the model is accurate enough to design a controller for the microwave drying process.

An Electromagnetic Time-Reversal Imaging Algorithm for Moisture Detection in Polymer Foam in an Industrial Microwave Drying System.

Microwave tomography (MWT) based control is a novel idea in industrial heating systems for drying polymer foam. In this work, an X-band MWT module is designed and developed using a fixed antenna array configuration and integrated with the HEPHAISTOS industrial heating system. A decomposition of the time-reversal operator (DORT) algorithm with a proper Green's function of multilayered media is utilized to localize the moisture location. The derived Green's function can be applied to the media with low or high contrast layers. It is shown that the time-reversal imaging (TRI) with the proposed Green's function can be applied to the multilayered media with a moderately rough surface. Moreover, a single frequency TRI is proposed to decrease the measurement time. Numerical results for different moisture scenarios are presented to demonstrate the efficacy of the proposed method. The developed method is then tested on the experimental data for different moisture scenarios from our developed MWT experimental prototype. Image reconstruction results show promising capabilities of the TRI algorithm in estimating the moisture location in the polymer foam.

Microwave Tomography Using Neural Networks for Its Application in an Industrial Microwave Drying System.

The article presents an application of microwave tomography (MWT) in an industrial drying system to develop tomographic-based process control. The imaging modality is applied to estimate moisture distribution in a polymer foam undergoing drying process. Our Leading challenges are fast data acquisition from the MWT sensors and real-time image reconstruction of the process. Thus, a limited number of sensors are chosen for the MWT and are placed only on top of the polymer foam to enable fast data acquisition. For real-time estimation, we present a neural network-based reconstruction scheme to estimate moisture distribution in a polymer foam. Training data for the neural network is generated using a physics-based electromagnetic scattering model and a parametric model for moisture sample generation. Numerical data for different moisture scenarios are considered to validate and test the performance of the network. Further, the trained network performance is evaluated with data from our developed prototype of the MWT sensor array. The experimental results show that the network has good accuracy and generalization capabilities.

Data-Driven Regularization Parameter Selection in Dynamic MRI.

In dynamic MRI, sufficient temporal resolution can often only be obtained using imaging protocols which produce undersampled data for each image in the time series. This has led to the popularity of compressed sensing (CS) based reconstructions. One problem in CS approaches is determining the regularization parameters, which control the balance between data fidelity and regularization. We propose a data-driven approach for the total variation regularization parameter selection, where reconstructions yield expected sparsity levels in the regularization domains. The expected sparsity levels are obtained from the measurement data for temporal regularization and from a reference image for spatial regularization. Two formulations are proposed. Simultaneous search for a parameter pair yielding expected sparsity in both domains (S-surface), and a sequential parameter selection using the S-curve method (Sequential S-curve). The approaches are evaluated using simulated and experimental DCE-MRI. In the simulated test case, both methods produce a parameter pair and reconstruction that is close to the root mean square error (RMSE) optimal pair and reconstruction. In the experimental test case, the methods produce almost equal parameter selection, and the reconstructions are of high perceived quality. Both methods lead to a highly feasible selection of the regularization parameters in both test cases while the sequential method is computationally more efficient.

Effect of data conserving respiratory motion compensation on left ventricular functional parameters assessed in gated myocardial perfusion SPECT.

BACKGROUND: Respiratory motion compromises image quality in myocardial perfusion (MP) single-photon emission computed tomography (SPECT) imaging and may affect analysis of left ventricular (LV) functional parameters, including phase analysis-quantified mechanical dyssynchrony parameters. In this paper, we investigate the performance of two algorithms, respiratory blur modeling (RBM) and joint motion-compensated (JMC) ordered-subsets expectation maximization (OSEM), and the effects of motion compensation on cardiac-gated MP-SPECT studies. METHODS: Image acquisitions were carried out with a dual-detector SPECT/CT system in list-mode format. A cardiac phantom was imaged as stationary and under respiratory motion. The images were reconstructed with OSEM, RBM-OSEM, and JMC-OSEM algorithms, and compared in terms of mean squared error (MSE). Subsequently, MP-SPECT data of 19 patients were binned into dual-gated (respiratory and cardiac gating) projection images. The images of the patients were analyzed with Quantitative Gated SPECT (QGS) 2012 program (Cedars-Sinai Medical Center, USA). The parameters of interest were LV volumes, ejection fraction, wall motion, wall thickening, phase analysis, and perfusion parameters. RESULTS: In phantom experiment, compared to the stationary OSEM reconstruction, the MSE values for OSEM, RBM-OSEM, and JMC-OSEM were 8.5406·10-5,2.7190·10-5, and 2.0795·10-5, respectively. In the analysis of LV function, use of JMC had a small but statistically significant (p < 0.05) effect on several parameters: it increased LV volumes and standard deviation of phase angle histogram, and it decreased ejection fraction, global wall motion, and lateral, septal, and apical perfusion. CONCLUSIONS: Compared to standard OSEM algorithm, RBM-OSEM and JMC-OSEM both improve image quality under motion. Motion compensation has a minor effect on LV functional parameters.

Time-modified OSEM algorithm for more robust assessment of left ventricular dyssynchrony with phase analysis in ECG-gated myocardial perfusion SPECT.

BACKGROUND: In ordered subsets expectation maximization (OSEM) reconstruction of electrocardiography (ECG)-gated myocardial perfusion single-photon emission computed tomography (SPECT), it is often assumed that the image acquisition time is constant for each projection angle and ECG bin. Due to heart rate variability (HRV), this assumption may lead to errors in quantification of left ventricular mechanical dyssynchrony with phase analysis. We hypothesize that a time-modified OSEM (TOSEM) algorithm provides more robust results. METHODS: List-mode data of 44 patients were acquired with a dual-detector SPECT/CT system and binned to eight ECG bins. First, activity ratio (AR)-the ratio of total activity in the last OSEM-reconstructed ECG bin and first five ECG bins-was computed, as well as standard deviation SDR-R of the accepted R-R intervals; their association was evaluated with Pearson correlation analysis. Subsequently, patients whose AR was higher than 90% were selected, and their list-mode data were rebinned by omitting a part of the acquired counts to yield AR values of 90%, 80%, 70%, 60% and 50%. These data sets were reconstructed with OSEM and TOSEM algorithms, and phase analysis was performed. Reliability of both algorithms was assessed by computing concordance correlation coefficients (CCCs) between the 90% data and data corresponding to lower AR values. Finally, phase analysis results assessed from OSEM- and TOSEM-reconstructed images were compared. RESULTS: A strong negative correlation (r = -0.749) was found between SDR-R and AR. As AR decreased, phase analysis parameters obtained from OSEM images decreased significantly. On the contrary, reduction of AR had no significant effect on phase analysis parameters obtained from TOSEM images (CCC > 0.88). The magnitude of difference between OSEM and TOSEM results increased as AR decreased. CONCLUSIONS: TOSEM algorithm minimizes the HRV-related error and can be used to provide more robust phase analysis results.

Effect of respiratory motion on cardiac defect contrast in myocardial perfusion SPECT: a physical phantom study.

OBJECTIVE: Correction for respiratory motion in myocardial perfusion imaging requires sorting of emission data into respiratory windows where the intra-window motion is assumed to be negligible. However, it is unclear how much intra-window motion is acceptable. The aim of this study was to determine an optimal value of intra-window residual motion. METHODS: A custom-designed cardiac phantom was created and imaged with a standard dual-detector SPECT/CT system using Tc-99m as the radionuclide. Projection images were generated from the list-mode data simulating respiratory motion blur of several magnitudes from 0 (stationary phantom) to 20 mm. Cardiac defect contrasts in six anatomically different locations, as well as myocardial perfusion of apex, anterior, inferior, septal and lateral walls, were measured at each motion magnitude. Stationary phantom data were compared to motion-blurred data. Two physicians viewed the images and evaluated differences in cardiac defect visibility and myocardial perfusion. RESULTS: Significant associations were observed between myocardial perfusion in the anterior and inferior walls and respiratory motion. Defect contrasts were found to decline as a function of motion, but the magnitude of the decline depended on the location and shape of the defect. Defects located near the cardiac apex lost contrast more rapidly than those located on the anterior, inferior, septal and lateral wall. The contrast decreased by less than 5% at every location when the motion magnitude was 2 mm or less. According to a visual evaluation, there were differences in myocardial perfusion if the magnitude of the motion was greater than 1 mm, and there were differences in the visibility of the cardiac defect if the magnitude of the motion was greater than 9 mm. CONCLUSIONS: Intra-window respiratory motion should be limited to 2 mm to effectively correct for respiratory motion blur in myocardial perfusion SPECT.

Respiratory motion reduction with a dual gating approach in myocardial perfusion SPECT: Effect on left ventricular functional parameters.

BACKGROUND: Respiratory motion (RM) complicates the analysis of myocardial perfusion (MP) single-photon emission computed tomography (SPECT) images. The effects of RM on left ventricular (LV) functional variables have not been thoroughly investigated. METHODS AND RESULTS: Thoracic electrical bioimpedance and electrocardiographic signals were recorded from eighteen patients undergoing the rest phase of a 1-day stress/rest cardiac-gated MP-SPECT examination. The signals and list-mode emission data were retrospectively processed to yield standard cardiac- and dual-gated (respiratory and cardiac gating) image sets applying a novel algorithm. LV volume, MP, shape index (SI), wall motion (WM), wall thickening (WT), and phase analysis parameters were measured with Quantitative Perfusion SPECT/Quantitative Gated SPECT software (Cedars-Sinai Medical Center). Image quality was evaluated by three experienced physicians. Dual gating increased LV volume (77.1 ± 26.8 vs 79.8 ± 27.6 mL, P = .006) and decreased SI (0.57 ± 0.05 vs 0.56 ± 0.05, P = .036) and global WT (39.0 ± 11.8% vs 36.9 ± 9.4%, P = .034) compared to cardiac gating, but did not significantly alter perfusion, WM or phase analysis parameters or image quality (P > .05). CONCLUSIONS: RM reduction has an effect on LV volume, shape, and WT parameters. RM exerts no significant effect on phase analysis parameters.

EIT Imaging Regularization Based on Spectral Graph Wavelets.

The objective of electrical impedance tomographic reconstruction is to identify the distribution of tissue conductivity from electrical boundary conditions. This is an ill-posed inverse problem usually solved under the finite-element method framework. In previous studies, standard sparse regularization was used for difference electrical impedance tomography to achieve a sparse solution. However, regarding elementwise sparsity, standard sparse regularization interferes with the smoothness of conductivity distribution between neighboring elements and is sensitive to noise. As an effect, the reconstructed images are spiky and depict a lack of smoothness. Such unexpected artifacts are not realistic and may lead to misinterpretation in clinical applications. To eliminate such artifacts, we present a novel sparse regularization method that uses spectral graph wavelet transforms. Single-scale or multiscale graph wavelet transforms are employed to introduce local smoothness on different scales into the reconstructed images. The proposed approach relies on viewing finite-element meshes as undirected graphs and applying wavelet transforms derived from spectral graph theory. Reconstruction results from simulations, a phantom experiment, and patient data suggest that our algorithm is more robust to noise and produces more reliable images.

Reconstruction of velocity fields in electromagnetic flow tomography.

Electromagnetic flow meters (EMFMs) are the gold standard in measuring flow velocity in process industry. The flow meters can measure the mean flow velocity of conductive liquids and slurries. A drawback of this approach is that the velocity field cannot be determined. Asymmetric axial flows, often encountered in multiphase flows, pipe elbows and T-junctions, are problematic and can lead to serious systematic errors. Recently, electromagnetic flow tomography (EMFT) has been proposed for measuring velocity fields using several coils and a set of electrodes attached to the surface of the pipe. In this work, a velocity field reconstruction method for EMFT is proposed. The method uses a previously developed finite-element-based computational forward model for computing boundary voltages and a Bayesian framework for inverse problems. In the approach, the vz-component of the velocity field along the longitudinal axis of the pipe is estimated on the pipe cross section. Different asymmetric velocity fields encountered near pipe elbows, solids-in-water flows in inclined pipes and in stratified or multiphase flows are tested. The results suggest that the proposed reconstruction method could be used to estimate velocity fields in complicated pipe flows in which the conventional EMFMs have limited accuracy. This article is part of the themed issue 'Supersensing through industrial process tomography'.

Dependence of left ventricular functional parameters on image acquisition time in cardiac-gated myocardial perfusion SPECT.

BACKGROUND: Reduction of image acquisition time in single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) examinations has been considered. However, association between left ventricular (LV) functional parameters and acquisition time is unclear. METHODS: Twenty-four patients referred to one-day stress/rest SPECT MPI examinations were imaged at rest with dual-headed gamma camera. List-mode emission data were processed into sets of cardiac-gated images corresponding to different acquisition times: 20%, 30%, 40%, 50%, 60%, 80%, and 100% of total acquisition time (30 seconds per projection). Image quality was quantitatively evaluated by computing contrast-to-noise ratio. LV volumes, wall motion, wall thickening, and mechanical dyssynchrony were quantified with automatic clinical software (QGS; Cedars-Sinai Medical Center). RESULTS: A significant negative dependence was found between phase analysis parameter values and image acquisition time. Differences in LV volume parameters were small but statistically significant at relative acquisition times of less than 50%. LV wall motion and wall thickening were found to be robust to the increase of noise. CONCLUSIONS: Image acquisition time of gated SPECT MPI examination can be reduced to 15 seconds per projection without significantly affecting LV volumes, wall motion, or wall thickening. However, reduction of acquisition time has a significant effect on phase analysis results.

A novel respiratory gating method for oncologic positron emission tomography based on bioimpedance approach.

OBJECTIVE: Respiratory motion causes loss of image quality and inaccuracy of quantification in oncologic positron emission tomography (PET) imaging. This study introduces a bioimpedance-based gating method for compensation of respiratory motion artefacts. METHODS: The bioimpedance-based respiratory gating method was studied parallel to a clinically used respiratory gating method [Real-time Position Management by Varian Medical Systems] in 4D PET/CT acquisition of 9 oncologic patients. The quantitative analysis consisted of the evaluation of tumour SUVpeak, SUVmax and volume. Additionally, target-to-background ratios as well as motion in cranial-caudal and anterior-posterior directions were measured. The evaluation was performed with amplitude- and time-based gating using averaged attenuation correction maps. RESULTS: Bioimpedance gating resulted in 17.7-18.9 % increase in mean SUVpeak and 20.0-21.4 % decrease in mean volume compared to non-gated images. The maximum motion measured from the bioimpedance-gated images was 19 mm in cranial-caudal direction and 9 mm in anterior-posterior direction. CONCLUSIONS: Bioimpedance-based respiratory gating compensates the adverse effects of motion in oncologic PET imaging.

An integrated bioimpedance--ECG gating technique for respiratory and cardiac motion compensation in cardiac PET.

Respiratory motion may degrade image quality in cardiac PET imaging. Since cardiac PET studies often involve cardiac gating by ECG, a separate respiratory monitoring system is required increasing the logistic complexity of the examination, in case respiratory gating is also needed. Thus, we investigated the simultaneous acquisition of both respiratory and cardiac gating signals using II limb lead mimicking electrode configuration during cardiac PET scans of 11 patients. In addition to conventional static and ECG-gated images, bioimpedance technique was utilized to generate respiratory- and dual-gated images. The ability of the bioimpedance technique to monitor intrathoracic respiratory motion was assessed estimating cardiac displacement between end-inspiration and -expiration. The relevance of dual gating was evaluated in left ventricular volume and myocardial wall thickness measurements. An average 7.6 ± 3.3 mm respiratory motion was observed in the study population. Dual gating showed a small but significant increase (4 ml, p = 0.042) in left ventricular myocardial volume compared to plain cardiac gating. In addition, a thinner myocardial wall was observed in dual-gated images (9.3 ± 1.3 mm) compared to cardiac-gated images (11.3 ± 1.3 mm, p = 0.003). This study shows the feasibility of bioimpedance measurements for dual gating in a clinical setting. The method enables simultaneous acquisition of respiratory and cardiac gating signals using a single device with standard ECG electrodes.

Optimizing bioimpedance measurement configuration for dual-gated nuclear medicine imaging: a sensitivity study.

Motion artefacts due to respiration and cardiac contractions may deteriorate the quality of nuclear medicine imaging leading to incorrect diagnosis and inadequate treatment. Motion artefacts can be minimized by simultaneous respiratory and cardiac gating, dual-gating. Currently, only cardiac gating is often performed. In this study, an optimized bioimpedance measurement configuration was determined for simultaneous respiratory and cardiac gating signal acquisition. The optimized configuration was located on anterolateral upper thorax based on sensitivity simulations utilizing a simplified thorax model. The validity of the optimized configuration was studied with six healthy volunteers. In the peak-to-peak and frequency content analyses the optimized configuration showed consistently higher peak-to-peak values and frequency content than other studied measurement configurations. This study indicates that the bioimpedance method has potential for the dual-gating in nuclear medicine imaging. The method would minimize the need of additional equipment, is easy for the technologists to use and comfortable for the patients.

Electrical impedance tomography for three-dimensional drug release monitoring.

Electrical impedance tomography (EIT) was adapted to monitor drug release three-dimensionally as a function of time. EIT is an electrical imaging modality in which the three-dimensional conductivity distribution inside an object is computed based on electrical measurements from the boundaries. Here, the three-dimensional concentration distribution was monitored with the help of the experimentally determined relationship between drug concentration and conductivity. The EIT monitoring was carried out with propranolol hydrochloride tablets in an apparatus similar to USP dissolution apparatus 2. The release profiles estimated using EIT matched well with the UV/VIS spectrophotometric analyses that were performed as a reference. There are several benefits conferred by three-dimensional monitoring, i.e., comprehensive information about the release process; no need to take samples during experiments; and not essential to assume homogenous concentration distribution in the drug release analysis. EIT is an in-line technique, and moreover, it is non-intrusive and non-invasive. The possibilities and the characteristics of the EIT monitoring are described in detail, and some potential drug release applications are proposed. EIT is especially encouraged to be exploited for research and development purposes.

Imaging hemorrhagic stroke with magnetic induction tomography: realistic simulation and evaluation.

Magnetic induction tomography (MIT) is a noncontact method for detecting the internal conductivity distribution of an object. This technology has the potential to be used in the biomedical area to check bio-impedance change inside the human body, for example to detect hemorrhage in the human brain. In this study the hemorrhagic stroke detectability with a 16-channel MIT system operating at 10 MHz was evaluated. Since the conductivity distribution is changed by the hemorrhagic stroke as well as the squeezed brain tissue around the stroke, deformation of the brain tissue is also considered and simulated with the help of a FEM-based linear bio-mechanical model in this paper. To simulate the raw measurement data as realistically as possible, the noise estimated from the experimental MIT system with hypothesis testing methods at 95% confidence level is added to the simulated measurements. Stroke images of 600 noisy samples for each detection assignment are reconstructed by the one-step Tikhonov-regularized inverse eddy current solution. Under the statistical framework, the detection failure is in control of a high false negative rate which represents a large artifact visualized in the reconstruction domain. The qualitative detectability of 18 detecting assignments, with three hemorrhagic positions (shallow, medial and center of the cerebrum) and two volume values (10 ml and 20 ml), overlaid by noise with three levels (standard deviation of phase change at 5 x 10(-3) degrees , 2.5 x 10(-3) degrees , 10 x 10(-3) degrees ), are investigated. These detecting assignments are compared with each other to find out which volumes of deformed spherical hemorrhagic stroke can be detected by the modeled MIT system.

An electrical impedance tomography-based approach to monitor in vitro sodium chloride dissolution from pharmaceutical tablets.

An approach to monitor in vitro dissolution process from pharmaceutical tablets utilizing electrical impedance tomography (EIT) is introduced. In the demonstration, a tablet containing sodium chloride (NaCl) was dissolution tested using tap water as a dissolution medium within an apparatus similar to the United States Pharmacopoeia dissolution apparatus II. During the process, the three-dimensional sodium chloride concentration distribution was monitored with EIT measurements as a function of time. For EIT measurements, an array of electrodes was attached on the boundary of the dissolution vessel, a set of alternating electric currents was injected through the electrodes, and the resulting voltages were measured. With these data and by applying mathematical algorithms, an approximation for the spatial/temporal concentration distribution inside the vessel was computed. It was found that the computed distributions were relatively homogeneous. A NaCl release curve was computed by integrating the concentration distribution over the vessel volume, and the final value of the curve matched well with the reference point based on the weight loss of the tablet. Finally, EIT monitoring is suggested to be used for research and product development purposes.