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Foam concrete is a porous cement-based material that could accommodate a high-volume particle addition at the mid- to high-density range (0.8 to 1.6 g/cm3). However, with low-density foam concrete (0.4 to 0.8 g/cm3), conventional particle inclusion (e.g., sand) tends to degrade the cellular microstructure and mechanical performance. Therefore, to improve low-density foam concrete, the novel use of crumb rubber (the rubber particles recycled from waste tires) in foam concrete is studied, as its unique attributes can potentially allow for the retention of structure and improved performance in foam concrete. The influence of no inclusion, sand, and crumb rubber on the microstructure and mechanical performance in foam concrete with the density of cellularized cement paste as 0.40 and 0.60 g/cm3 was studied. Computed tomography indicates that the inclusion of crumb rubber can mitigate the foam degradation concern associated with particle inclusion in low-density mixtures. A notable improvement was also observed in the mechanical properties of 0.40 g/cm3 rubberized foam concrete mixtures—compressive strength, plateau strength, and impact resistance—when referenced to the sand inclusion counterpart. [ABSTRACT FROM AUTHOR]

We examine some bounded perturbations resilient iterative methods for addressing (constrained) consistent linear systems of equations and (constrained) least squares problems. We introduce multiple frameworks rooted in the operator of the Landweber iteration, adapting the operators to facilitate the minimization of absolute errors or residuals. We demonstrate that our operator-based methods exhibit comparable speed to powerful methods like CGLS, and we establish that the computational cost of our methods is nearly equal to that of CGLS. Furthermore, our methods possess the capability to handle constraints (e.g. non-negativity) and control the semi-convergence phenomenon. In addition, we provide convergence analysis of the methods when the current iterations are perturbed by summable vectors. This allows us to utilize these iterative methods for the superiorization methodology. We showcase their performance using examples drawn from tomographic imaging and compare them with CGLS, superiorized conjugate gradient (S-CG), and the non-negative flexible CGLS (NN-FCGLS) methods. [ABSTRACT FROM AUTHOR]

This paper introduces the Kuopio Tomography Challenge 2023 (KTC 2023), created to inspire and facilitate algorithm development for image reconstruction in electrical impedance tomography (EIT). A laboratory EIT dataset was prepared for the KTC 2023, using conductive and resistive inclusions of various shapes and sizes placed inside a shallow, circular water tank. The task for the competitors of the challenge was to produce segmented images of the inclusions from EIT data in cases of complete coverage of the tank surface with electrodes (lowest level of difficulty) and in cases of decreasing boundary coverage (corresponding to increasing level of challenge difficulty). A total of seven teams, with members from seven countries, participated in KTC 2023, submitting a total of 22 algorithms. The results of the competition show a variety of novel algorithms applied to real EIT data, with high quality image reconstructions from limited boundary data. The EIT data set collected for the challenge is publicly available for future studies on EIT image reconstruction. [ABSTRACT FROM AUTHOR]

Our study explores the feasibility of quantum computing in emission tomography reconstruction, addressing a noisy ill-conditioned inverse problem. In current clinical practice, this is typically solved by iterative methods minimizing a L 2 norm. After reviewing quantum computing principles, we propose the use of a commercially available quantum annealer and employ corresponding hybrid solvers, which combine quantum and classical computing to handle more significant problems. We demonstrate how to frame image reconstruction as a combinatorial optimization problem suited for these quantum annealers and hybrid systems. Using a toy problem, we analyze reconstructions of binary and integer-valued images with respect to their image size and compare them to conventional methods. Additionally, we test our method's performance under noise and data underdetermination. In summary, our method demonstrates competitive performance with traditional algorithms for binary images up to an image size of 32 × 32 on the toy problem, even under noisy and underdetermined conditions. However, scalability challenges emerge as image size and pixel bit range increase, restricting hybrid quantum computing as a practical tool for emission tomography reconstruction until significant advancements are made to address this issue. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Ground Improvement is the property of Journal of Ground Improvement Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

BingSat-Tomographic Observation of Polar Ice Sheets (BingSat-TOPIS) is a spaceborne multistatic radar sounding system that can achieve high resolution and stereoscopic observation. It is designed to penetrate ice sheets and acquire tomographic image. The satellite group fly over the Polar Regions, which can form about 6.56-km cross-track baseline. This cross-track baseline is formed by one master satellite and 40 slave CubeSats. In this article, we propose a tomographic imaging algorithm for orbital radar sounding of the Earth's ice sheets. First, we give the method to calculate the two-way slant range in air and ice. The phase errors of the method are smaller than π/4 rad. Second, we express the radar data cube for a point target in ice sheets. The radar data cube is made of 40 bistatic synthetic aperture radar echo signals. At last, the echoes are simulated for the TOPIS system, and a matched filter is used for pulse compression in range. Then, the back projection algorithm is used in track and cross-track imaging. The experimental results demonstrate that our tomographic imaging algorithm is effective and reliable.

Light sheet microscopy in live cells requires minimal excitation intensity and resolves three-dimensional (3D) information rapidly. Lattice light sheet microscopy (LLSM) works similarly but uses a lattice configuration of Bessel beams to generate a flatter, diffraction-limited z-axis sheet suitable for investigating subcellular compartments, with better tissue penetration. We developed a LLSM method for investigating cellular properties of tissue in situ. Neural structures provide an important target. Neurons are complex 3D structures, and signaling between cells and subcellular structures requires high resolution imaging. We developed an LLSM configuration based on the Janelia Research Campus design or in situ recording that allows simultaneous electrophysiological recording. We give examples of using LLSM to assess synaptic function in situ. In presynapses, evoked Ca2+ entry causes vesicle fusion and neurotransmitter release. We demonstrate the use of LLSM to measure stimulus-evoked localized presynaptic Ca2+ entry and track synaptic vesicle recycling. We also demonstrate the resolution of postsynaptic Ca2+ signaling in single synapses. A challenge in 3D imaging is the need to move the emission objective to maintain focus. We have developed an incoherent holographic lattice light-sheet (IHLLS) technique to replace the LLS tube lens with a dual diffractive lens to obtain 3D images of spatially incoherent light diffracted from an object as incoherent holograms. The 3D structure is reproduced within the scanned volume without moving the emission objective. This eliminates mechanical artifacts and improves temporal resolution. We focus on LLS and IHLLS applications and data obtained in neuroscience and emphasize increases in temporal and spatial resolution using these approaches. [ABSTRACT FROM AUTHOR]

The gas and solids in a circulating fluidized bed (CFB) are heterogeneously dispersed and a multiscale flow regime may form both in time and space. Accurate measurement of the fluidizing process is significant for investigating the multiscale gas–solid flow characteristics and the design, optimization, and control of CFBs in various applications. This article develops a deep learning‐based tomographic imaging of electrical capacitance tomography (ECT) to characterize the particle concentration distribution in a CFB. The deep tomographic imaging approach is realized through training a well‐designed convolutional neural network (CNN) with the numerically built dataset. Simulation results demonstrate that the average values of the relative image errors reconstructed by CNN in the test set are 0.1110 and 0.1114 for the 60 and 100 mm pipes, respectively, which are better than the average values of 0.1819 and 0.2519 by the Landweber algorithm. With the verification of the trained model based on the prepared data can image the unseen typical flow patterns better than Landweber, it is further used to investigate the particle flow characteristics of a lab‐scale CFB. Experimental results reveal that the developed deep tomographic imaging of ECT can successfully measure the fluidized particle distribution in both the 60 and 100 mm pipes, showing good prediction and generality of the designed CNN model. A flow regime transformation from "annular" flow to "core‐annular" flow and pneumatic conveying is observed under the tested conditions. Besides, the flow regime would be highly affected by the fluidized gas flow rate and the initial bed height. [ABSTRACT FROM AUTHOR]

Recent advancement in wearable and robot-assisted healthcare technology gives rise to the demand for smart interfaces that allow more efficient human-machine interaction. In this paper, a hydrogel-based soft sensor for subtle touch detection is proposed. Adopting the working principle of a biomedical imaging technology known as electrical impedance tomography (EIT), the sensor produces images that display the electrical conductivity distribution of its sensitive region to enable touch detection. The sensor was made from a natural gelatin hydrogel whose electrical conductivity is considerably less than that of human skin. The low conductivity of the sensor enabled a touch-detection mechanism based on a novel short-circuiting approach, which resulted in the reconstructed images being predominantly affected by the electrical contact between the sensor and fingertips, rather than the conventionally used piezoresistive response of the sensing material. The experimental results indicated that the proposed sensor was promising for detecting subtle contacts without the necessity of exerting a noticeable force on the sensor. [ABSTRACT FROM AUTHOR]

Our study explores the feasibility of quantum computing in emission tomography reconstruction, addressing a noisy ill-conditioned inverse problem. In current clinical practice, this is typically solved by iterative methods minimizing a L2 norm. After reviewing quantum computing principles, we propose the use of a commercially available quantum annealer and employ corresponding hybrid solvers, which combine quantum and classical computing to handle more significant problems. We demonstrate how to frame image reconstruction as a combinatorial optimization problem suited for these quantum annealers and hybrid systems. Using a toy problem, we analyze reconstructions of binary and integer-valued images with respect to their image size and compare them to conventional methods. Additionally, we test our method’s performance under noise and data underdetermination. In summary, our method demonstrates competitive performance with traditional algorithms for binary images up to an image size of 32×32 on the toy problem, even under noisy and underdetermined conditions. However, scalability challenges emerge as image size and pixel bit range increase, restricting hybrid quantum computing as a practical tool for emission tomography reconstruction until significant advancements are made to address this issue.

The quality factor value (Q) of the crustal medium, which can describe the anelasticity within the Earth’s interior, is a sensitive indicator of changes in the crystalline structure induced by temperature and phase transformations. Although the velocity structure of the Tianshan region in Central Asia has been extensively studied, studies regarding its Q values are limited. These studies focus mainly on the crustal attenuation structure of the Tianshan region; however, their results are limited to the qualitative analyses of the local areas or averages over large areas. Therefore, in this study, we conducted seismic attenuation tomography to create a Q map of the crust underneath the Tianshan tectonic belt (TTB) at a resolution of 0.8° × 0.8° using data from 24,273 near-source waveforms recorded by 51 observation stations of the Xinjiang regional seismic network from 2009 to 2020. The regional distribution of the static and sliding-average values (QS) was calculated. The average value (Q0) of TTB was approximately 523. Additionally, Qs exhibited considerable lateral variations that strongly correlate with the surface tectonics of the TTB region. Furthermore, the velocity and attenuation structures of the TTB were positively correlated. The main part of the TTB exhibited high velocities and Q (indicating low attenuation), whereas the areas adjoining the Tarim and Junggar basins (at the South and North of the TBB, respectively) and their margins exhibited low velocities and Q (indicating high attenuation). This suggested that the attenuation structure of the TTB was highly consistent with its velocity and density structures. Since 1900, most earthquakes in the TTB having magnitudes ≥6.0 earthquakes have occurred at the junctions of high- and low-Q-value areas, or in areas with low Q values. According to the Qs values in different periods, the average Qs of the entire TTB only varied between 500 and 540. However, the average Qs in the middle TTB region portrays an upward trended over time (from 494 in 2010 to 554 in 2020). The average Qs of the southwestern TTB region has been relatively stable, varying between 490 and 530. The Q0 of the southwestern TTB region was lower than that observed in the middle TTB region in most of the time. This observation is more consistent with the tectonic activity recorded in the southwestern TTB region (with greater intensity) than that observed in the middle Tianshan. In addition, the number of earthquakes with magnitudes ≥4.0 correlated positively with the regional average Qs in the middle and southwestern Tianshan. Notably, the higher the regional average Q value, the larger the number of moderate earthquakes. This correlation suggests that in earthquake-prone regions, the accumulation and release of stress influence the opening or closure of crustal fractures, resulting in noticeable changes in the Q values. The findings of our study provide novel insights into the mechanisms of earthquakes and their correlation with the structure of the Earth’s crust.

Copyright of Acta Geoscientica Sinica is the property of Acta Geoscientica Sinica Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The advancement of new promising techniques in the field of biomedical imaging has always been paramount for the research community. Recently, ultrasound tomography has proved to be a good candidate for non-invasive and safe diagnostics. In particular, breast cancer imaging may benefit from this approach, as frequent screening and early diagnosis require decreased system size and costs compared to conventional imaging techniques. Furthermore, a major advantage of these approaches consists in the operator-independent feature, which is very desirable compared to conventional hand-held ultrasound imaging. In this framework, the authors present some imaging results on an experimental campaign acquired via an in-house ultrasound tomographic system designed and built at the University of Naples Parthenope. Imaging performance was evaluated via different tests, showing good potentiality in structural information retrieval. This study represents a first proof of concept in order to validate the system and to consider further realistic cases in near future applications. [ABSTRACT FROM AUTHOR]

We consider the randomized Kaczmarz method with a constant relaxation parameter and present an upper bound for the expectation of the noise-error part. Based on the upper bound, we suggest a k -dependent relaxation parameter to control semi-convergence phenomenon. Further, we show the performance of the proposed relaxation parameter using samples taken from tomographic imaging. [ABSTRACT FROM AUTHOR]

We image shallow crustal structures and analyze seismicity patterns in the Hengill high-enthalpy geothermal area in SW Iceland, exploiting a temporary densification of the seismic network 2018 to 2020. Using a subset of 6,300 high-quality manually picked P- and S-phases, we compute a minimum 1-D model for the region. Our results suggest that the most consistent and accurate hypocenter locations are derived from a joint inversion of P and S arrival times for the Hengill area. We demonstrate that this minimum 1-D model in combination with SeisComP detection and location algorithms can be used to produce fully-automated yet high-quality earthquake catalogs. Our analysis established that both the induced and natural seismicity in the Hengill area occurs in several distinct, spatially constrained clusters. In production and injection areas, the depth of the clusters is at about 2 km, near the bottom of the production and injection wells. These are most likely triggered by the injection and induced by the production, respectively. Outside of these clusters, the seismicity is generally deeper, with the depth of the deepest seismicity indicating the brittle-ductile transition zone. This zone is encountered at about 4 km near the center of the Hengill volcanic area and deepens with increasing distance from its volcanic center, to about 7 km in the southernmost region. A spatial analysis of b-values shows slightly increased values in areas with numerous injection wells and slightly decreased values in production areas. Three-dimensional crustal imaging of VP, VS, VP/VS shows a SE-NW trending fast velocity that extends, at 1–3 km depth between the extinct Grensdalur volcanic center and the presently active Hengill volcanic center. The fastest velocities are found in the NW corner of the Grensdalur volcanic center coinciding with a gravity high and probably reflecting dense solidified magmatic intrusion(s). This trend coincides with traces of geothermal surface manifestations, a shallow lying low resistivity anomaly and an aero-magnetic low. All these anomalies are caused by high temperature at some point in the geological history of the area and are most likely due to migration of the crustal accretion and volcanic activity between the two volcanic centers. Below-average VP/VS ratios at similar depth, coincide with the main production field. We suggest that this anomaly is caused by the extensive fluid extraction, which lowers the pore-pressure in the field and consequently increases the steam dominated zone, leading to lower Vp/Vs ratios. Most of the earthquakes are within the Vp/Vs low and at the boundary of the high and low Vp/Vs anomalies, which might indicate a region of good permeability.

In solids, chemical short-range order (CSRO) refers to the self-organization of atoms of certain species occupying specific crystal sites. CSRO is increasingly being envisaged as a lever to tailor the mechanical and functional properties of materials. Yet quantitative relationships between properties and the morphology, number density, and atomic configurations of CSRO domains remain elusive. Herein, it is showcased how machine learning-enhanced atom probe tomography (APT) can mine the near-atomically resolved APT data and jointly exploit the technique's high elemental sensitivity to provide a 3D quantitative analysis of CSRO in a CoCrNi medium-entropy alloy. Multiple CSRO configurations are revealed, with their formation supported by state-of-the-art Monte-Carlo simulations. Quantitative analysis of these CSROs allows establishing relationships between processing parameters and physical properties. The unambiguous characterization of CSRO will help refine strategies for designing advanced materials by manipulating atomic-scale architectures., (© 2024 The Author(s). Advanced Materials published by Wiley‐VCH GmbH.)

In the framework of non-destructive testing and imaging, ultrasound tomography can have an important role in several applications, especially in the biomedical field. The motivation beyond the use of this imaging technique lies in the possibility of obtaining quantitative imaging which is also operator-independent, conversely to conventional approaches. Thus, the need for public data sets for testing inverse scattering approaches is always persisting. To this aim, this paper introduces an experimental multiple-input-multiple-output ultrasound tomographic database whose acquisitions were performed by an air-matched in-house system designed and built by the Authors. The proposed database provides several cases with single and multiple objects of different shapes, sizes, and materials, to be imaged in laboratory-controlled conditions. Therefore, these scenarios can represent interesting options for the preliminary testing of tomographic ultrasound imaging approaches. [ABSTRACT FROM AUTHOR]

The International Atomic Energy Agency has developed a tomographic imaging system for accomplishing the total fuel rod-by-rod verification time of fuel assemblies within the order of 1–2 h, however, there are still limitations for some fuel types. The aim of this study is to develop a deep learning-based de-noising process resulting in increasing the tomographic image acquisition speed of fuel assembly compared to the conventional techniques. Convolutional AutoEncoder (CAE) was employed for de-noising the low-quality images reconstructed by filtered back-projection (FBP) algorithm. The image data set was constructed by the Monte Carlo method with the FBP and ground truth (GT) images for 511 patterns of missing fuel rods. The de-noising performance of the CAE model was evaluated by comparing the pixel-by-pixel subtracted images between the GT and FBP images and the GT and CAE images; the average differences of the pixel values for the sample image 1, 2, and 3 were 7.7%, 28.0% and 44.7% for the FBP images, and 0.5%, 1.4% and 1.9% for the predicted image, respectively. Even for the FBP images not discriminable the source patterns, the CAE model could successfully estimate the patterns similarly with the GT image.

Comparing the observed brightness of various buried objects is a straightforward way to characterize the performance of a ground penetrating radar (GPR) system. However, a limitation arises. A simple comparison of buried object brightness values does not disentangle the effects of the GPR system itself from the system’s operating environment and the objects being observed. Therefore, with brightness values exhibiting an unknown synthesis of systemic, environmental, and object factors, GPR system analysis becomes a convoluted affair. In this work, we use an experimentally collected dataset of over 25000 object observations from five different multistatic radar arrays to develop models of buried object brightness and control for these various effects. Our modeling efforts provide a means for quantifying the relative brightness of GPR systems, the objects they detect, and the physical properties of those objects that influence observed brightness. To evaluate the models’ performance on new object observations, we repeatedly simulate fitting them to half the dataset and predicting the observed brightness values of the unseen half. In addition, we introduce a method for estimating the probability that individual observations constitute a visible object, which aids in failure analysis, performance characterization, and dataset cleaning. [ABSTRACT FROM AUTHOR]

In this paper, we analyze the convergence properties of projected non-stationary block iterative methods (P-BIM) aiming to find a constrained solution to large linear, usually both noisy and ill-conditioned, systems of equations. We split the error of the kth iterate into noise error and iteration error, and consider each error separately. The iteration error is treated for a more general algorithm, also suited for solving split feasibility problems in Hilbert space. The results for P-BIM come out as a special case. The algorithmic step involves projecting onto closed convex sets. When these sets are polyhedral, and of finite dimension, it is shown that the algorithm converges linearly. We further derive an upper bound for the noise error of P-BIM. Based on this bound, we suggest a new strategy for choosing relaxation parameters, which assist in speeding up the reconstruction process and improving the quality of obtained images. The relaxation parameters may depend on the noise. The performance of the suggested strategy is shown by examples taken from the field of image reconstruction from projections. [ABSTRACT FROM AUTHOR]

In this letter, we consider the tomographic imaging issue of layouts only using the received signal strength (RSS) of dual narrowband signals. Specifically, we first introduce the signal model, which describes the relationship between RSS and the layouts in unknown scenario. Then, the propagation differences of dual-band signals are analyzed theoretically. Next, a joint iterative imaging method based on improved total variation constraint is proposed, and the arithmetic fusion strategy is used to obtain final result. Finally, the real data results demonstrate that the proposed approach with dual-band signals can retain the clear edge information of building structures and greatly reduce the artifacts in results. [ABSTRACT FROM AUTHOR]

We present a case of a middle-age male who presented in emergency room with nonspecific abdominal pain. A contrast-enhanced computer tomography (ceCT) scan showed a reduced perfusion of both adrenal glands. The clinical examinations and the laboratory tests were negative for an adrenal pathological process. To reassess the adrenal ischemia, a second ceCT scan was performed 5 days later showing an acute bilateral adrenal hemorrhage. These findings demonstrated that the previous adrenal hypoperfusion represented the prodromal manifestation of a hemorrhagic intraglandular process. This case suggests that adrenal hypoperfusion detected on tomographic imaging dictates a prompt clinical management finalized to strictly monitor the potential evolution towards a more aggressive pathological condition and confirms the pivotal role of imaging in the diagnosis of such uncommon disorder.

An indispensable step in the imaging of Tomographic Synthetic Aperture Radar (TomoSAR) in spectral analysis or Compressive Sensing (CS) technology is estimating the perpendicular baselines in the Perpendicular Line Of Sight (PLOS) in deramping operations. To avoid this procedure, we introduce a Beam Forming (BF) method in the spatial domain that scans for TomoSAR focusing in the PLOS direction. Because of the sophisticated structure of buildings in urban areas, multipass high-resolution SAR images suffer from discrepancies in the look and incidence angles as well as speckle noise. As a result, it is challenging to precisely coregister all the homologous points in the identical pixels of multipass SAR images. To identify the most relevant pixels with respect to both amplitude and phase when BF imaging is implemented, we propose an inconsistency criterion for specific pixels using the joint phase and amplitude of pixels in a window. By minimizing the inconsistency criterion, homologous points with high accuracy can be identified by focusing on TomoSAR imaging. We used simulation and real data from a multipass X-band airborne TomoSAR system in China to test the effectiveness of the proposed method. Experimental results show that the peak of the reflectivity profile via conventional tomographic imaging is about 15.63 m, whereas that by the proposed method is 16.88 m, which is very close to the actual height of the 18 m building. The results demonstrate the feasibility of improving the focusing power of scatterers in the PLOS direction and extracting the threedimensional outliers of buildings.

The advancement of new promising techniques in the field of biomedical imaging has always been paramount for the research community. Recently, ultrasound tomography has proved to be a good candidate for non-invasive and safe diagnostics. In particular, breast cancer imaging may benefit from this approach, as frequent screening and early diagnosis require decreased system size and costs compared to conventional imaging techniques. Furthermore, a major advantage of these approaches consists in the operator-independent feature, which is very desirable compared to conventional hand-held ultrasound imaging. In this framework, the authors present some imaging results on an experimental campaign acquired via an in-house ultrasound tomographic system designed and built at the University of Naples Parthenope. Imaging performance was evaluated via different tests, showing good potentiality in structural information retrieval. This study represents a first proof of concept in order to validate the system and to consider further realistic cases in near future applications.

• Combination of TDLAS and tomographic achieves hazardous gas distribution reconstruction. • Optical path arrangement, beam density, and concentration gradients significantly effect on reconstruction resolution. • Experimental validation demonstrated the effectiveness of TDLAS remote sensing for gas distribution mapping. The accurate identification of leakage concentration fields is critical in responding to hazardous gas leaks. Laser absorption spectroscopy provides high sensitivity and real-time measurement capabilities but lacks global gas component distribution information. To overcome this limitation, we propose a new method combining tomographic imaging algorithms with optimized laser beam path arrangements to obtain gas component distributions within a plane, enabling precise localization of the leak source. We also employed tunable diode laser absorption spectroscopy (TDLAS) remote sensing technology, in conjunction with the algebraic reconstruction technique (ART), for inverse reconstruction of leakage concentration fields. Numerical simulations and experimental validation demonstrated the convenience and effectiveness of this approach. Results showed the density of effective laser paths and the concentration gradient within the reconstruction plane to be crucial factors affecting the resolution of reconstructions. Specifically, a higher density for the effective laser beam path led to improved accuracy, while higher concentration gradients contributed to the enhancing of image resolution and the acquisition of fine details. Experimental validation revealed relative errors between the reconstructed component concentrations and measured concentrations of 3.4 %, 5.8 %, and 5.7 %, confirming the feasibility and applicability of this methodology for practical leak detection. [ABSTRACT FROM AUTHOR]

X-ray luminescence optical tomography (XLOT) is an emerging hybrid imaging modality in which x-ray excitable particles (phosphor particles) emit optical photons when stimulated with a collimated x-ray beam. XLOT can potentially combine the high sensitivity of optical imaging with the high spatial resolution of x-ray imaging. For reconstruction of XLOT data, we compared two reconstruction algorithms, conventional filtered backprojection (FBP) and a new algorithm, x-ray luminescence optical tomography with excitation priors (XLOT-EP), in which photon propagation is modeled with the diffusion equation and the x-ray beam positions are used as reconstruction priors. Numerical simulations based on dose calculations were used to validate the proposed XLOT imaging system and the reconstruction algorithms. Simulation results showed nanoparticle concentrations reconstructed with XLOT-EP are much less dependent on scan depth than those obtained with FBP. Measurements at just two orthogonal projections are sufficient for XLOT-EP to reconstruct an XLOT image for simple source distributions. The heterogeneity of x-ray energy deposition is included in the XLOT-EP reconstruction and improves the reconstruction accuracy, suggesting that there is a need to calculate the x-ray energy distribution for experimental XLOT imaging.

In the framework of non-destructive testing and imaging, ultrasound tomography can have an important role in several applications, especially in the biomedical field. The motivation beyond the use of this imaging technique lies in the possibility of obtaining quantitative imaging which is also operator-independent, conversely to conventional approaches. Thus, the need for public data sets for testing inverse scattering approaches is always persisting. To this aim, this paper introduces an experimental multiple-input-multiple-output ultrasound tomographic database whose acquisitions were performed by an air-matched in-house system designed and built by the Authors. The proposed database provides several cases with single and multiple objects of different shapes, sizes, and materials, to be imaged in laboratory-controlled conditions. Therefore, these scenarios can represent interesting options for the preliminary testing of tomographic ultrasound imaging approaches.

The moisture content of stored rice is dependent on the surrounding and environmental factors which in turn affect the quality and economic value of the grains. Therefore, the moisture content of grains needs to be measured frequently to ensure that optimum conditions that preserve their quality are maintained. The current state of the art for moisture measurement of rice in a silo is based on grab sampling or relies on single rod sensors placed randomly into the grain. The sensors that are currently used are very localized and are, therefore, unable to provide continuous measurement of the moisture distribution in the silo. To the authors’ knowledge, there is no commercially available 3D volumetric measurement system for rice moisture content in a silo. Hence, this paper presents results of work carried out using low-cost wireless devices that can be placed around the silo to measure changes in the moisture content of rice. This paper proposes a novel technique based on radio frequency tomographic imaging using low-cost wireless devices and regression-based machine learning to provide contactless non-destructive 3D volumetric moisture content distribution in stored rice grain. This proposed technique can detect multiple levels of localized moisture distributions in the silo with accuracies greater than or equal to 83.7%, depending on the size and shape of the sample under test. Unlike other approaches proposed in open literature or employed in the sector, the proposed system can be deployed to provide continuous monitoring of the moisture distribution in silos.

Introduction and hypothesis: Tears of the levator ani muscle are common after vaginal birth and associated with pelvic organ prolapse (POP). Although such trauma is usually attributed to the first vaginal birth, epidemiological evidence suggests an additional effect of subsequent vaginal deliveries. Our hypothesis was: "The prevalence of avulsion increases with the number of vaginal births". Methods: We conducted a retrospective cohort study in patients who presented to a tertiary urogynaecology clinic. Assessment included a physician-directed interview, POP-Q and 4D translabial ultrasound (TLUS), supine, after voiding, at rest, on maximum pelvic floor muscle contraction (PFMC) and Valsalva. Offline analysis of levator integrity was undertaken by tomographic imaging (TUI) at a later date, blinded against all other data. Results: A total of 1,124 patients had been seen between 1 January 2014 and 30 June 2016, on average 33 (0.32–69.7) years after their first birth. Mean age was 56 (19–90) years. 1,012 (90%) were vaginally parous with a median vaginal parity of 2 (1–8). On TUI, avulsion was diagnosed in 257 (23%) women, all of whom were vaginally parous. On univariate analysis, there was no significant difference in the prevalence of avulsion on comparing vaginally primiparous and multiparous women (P = 0.6), nor was there any difference between vaginal parity groups (one, two, three, and ≥4 births; p = 0.7). This remained true after controlling for potential confounding factors using multivariate regression (p = 0.6). Conclusions: There was no significant difference in the prevalence of avulsion between vaginally primiparous and multiparous women. Vaginal deliveries after a first vaginal birth are unlikely to cause avulsion. [ABSTRACT FROM AUTHOR]

The safety diagnostic inspection of large plate structures, such as nuclear power plant containment liner plates and aircraft wings, is an important issue directly related to the safety of life. This research intends to present a more quantitative defect imaging in the structural health monitoring (SHM) technique by using a wide range of diagnostic techniques using guided ultrasound. A noncontact detection system was applied to compensate for such difficulties because direct access inspection is not possible for high-temperature and massive areas such as nuclear power plants and aircraft. Noncontact systems use unstable pulse laser and air-coupled transducers. Automatic detection systems were built to increase inspection speed and precision and the signal was measured. In addition, a new Difference Hilbert Back Projection (DHB) algorithm that can replace the reconstruction algorithm for the probabilistic inspection of damage (RAPID) algorithm used for imaging defects has been successfully applied to quantitative imaging of plate structure defects. Using an automatic detection system, the precision and detection efficiency of data collection has been greatly improved, and the same results can be obtained by reducing errors in experimental conditions that can occur in repeated experiments. Defects were made in two specimens, and comparative analysis was performed to see if each algorithm can quantitatively represent defects in multiple defects. The new DHB algorithm presented the possibility of observing and predicting the growth direction of defects through the continuous monitoring system. [ABSTRACT FROM AUTHOR]

The principal objective of this research is to conceive a mobile system based on electrical tomography for subsurface imaging and monitoring in order to enable simultaneous recording of electrical potentials of cardiac and pulmonary activity. For an exploration of excitation waveforms in electrical tomography, specialized hardware is required. As the main principle of tomography is the measurement of electrical perturbations on an unknown object, it is crucial to synchronize excitation and sensing processes in a very precise way for the purpose of acquiring meaningful data. To cope with this problem, an FPGA device is used, with an architecture that allows us to trigger excitation signals and to read sensed data simultaneously via independent processes that share the same clock. In this way, waveform reconfiguration on frequency and shape can be provided and studied. The system is connected to a standard microcontroller SoC with a simple API that allows for IoT capabilities for on-line operation and tracking, given that the design is targeted for in vivo medical monitoring. As a result of the research work, a measuring device was developed, the surface data analyzed and the image was reconstructed using the selected configuration.

Objective: Three-/four-dimensional translabial ultrasound (TLUS) is gaining popularity for the assessment of anal sphincter trauma, although repeatability data are lacking. This study aimed to determine the repeatability of tomographic ultrasound imaging (TUI) on TLUS for the diagnosis of external anal sphincter (EAS) trauma and compare the performance of a novice with that of an experienced investigator.Methods: This was a retrospective study of archived ultrasound datasets of patients who presented with symptoms of pelvic floor dysfunction and were examined twice between 2012 and 2016 at an average interval of 260 (range, 1-1100) days. All volumes were obtained using a GE Medical Systems Voluson 730 Expert or E8 ultrasound system. Post-processing of volumes was performed independently by two investigators, one with over 1 year's experience and another with no prior experience in using TUI, who were blinded to clinical data, each other's results and the results obtained at the first timepoint. Significant trauma on EAS was diagnosed if four of the six TUI slices showed a defect of ≥ 30°. Intra- and interobserver agreement were determined using Cohen's kappa (κ) and intraclass correlation coefficients.Results: During the study period, 105 women underwent two TLUS assessments of the anal sphincter. Of these, 103 patients with ultrasound volumes available for both timepoints were included in the analysis. The novice investigator demonstrated average repeatability for assessment of significant EAS trauma and single-slice defect (κ, 0.30 and 0.22, respectively) despite relatively high agreement between measurements obtained at the two timepoints (84.5% and 79.3%, respectively). The experienced investigator demonstrated good to very good repeatability for significant EAS trauma and single-slice defect (κ, 0.91 and 0.78, respectively) between the two assessments, which equates to 98.1% and 94.7% agreement, respectively.Conclusion: The repeatability of TLUS measurements for diagnosis of EAS trauma seems to be very good when imaging is undertaken with state-of-the-art equipment and the analysis is performed by an experienced observer; however, the performance of a novice investigator is much poorer. Copyright © 2018 ISUOG. Published by John Wiley & Sons Ltd. [ABSTRACT FROM AUTHOR]

Highlights • Magnetic resonance imaging (MRI) visualizes bubbles injected into fluidized beds. • Particle flow fields around bubbles of different sizes are imaged. • Data on bubble shape and volume and particle velocity are quantified. • The data provides a strong set of challenge problems for computational models. Abstract Rapid magnetic resonance imaging is used to investigate the volume, shape and rise velocity of single isolated bubbles injected into incipiently fluidized beds as well as the particle velocity field surrounding these bubbles. The volume of gas injected and particle size are varied to investigate their effects on bubble behavior. Image processing is used to quantify data into plots which can be compared directly with predictions from analytical and numerical models. Results show that more injected gas leaks into the interstitial flow in beds of large particles than beds of small particles because of the higher permeability to gas flow. Bubbles develop from a taller shape with a large wake angle into a wider shape with a smaller wake angle as they develop from a spherical shape to a spherical cap shape as they rise. Bubble rise velocities for fully formed bubbles are consistent with correlations in the literature. [ABSTRACT FROM AUTHOR]

Objectives: Three‐/four‐dimensional translabial ultrasound (US) is increasingly used to image the levator ani and anal sphincters, especially in the form of tomographic US. The aim of the study was to evaluate the validity of these published methods. Methods: This work was a retrospective analysis of datasets of 172 nulliparous women who attended 2 tertiary urogynecologic centers for symptoms of pelvic floor dysfunction between June 2012 and September 2016. All patients had a standardized interview, clinical examination, and 4‐dimensional translabial US examination. An evaluation of volume data was performed by the first author, who was blinded against all clinical data, including parity. An assessment for levator avulsion and anal sphincter defects was performed using stored US volume data. Results: Data sets of 162 and 153 nulliparous women were available for levator and anal sphincter assessments, respectively. On the assessment by the first author, a complete avulsion was diagnosed in 3 nulliparas. On a review by 2 senior authors, 1 was judged as positive and the other 2 as normal. On the sphincter assessment, 2 significant external anal sphincter defects were detected. On the review, 1 was judged as false‐positive. The second was judged as highly abnormal by all authors. Therefore, 1 nullipara each was diagnosed with avulsion and a significant external anal sphincter defect. Conclusions: Published diagnostic criteria for levator avulsion and external anal sphincter trauma on tomographic US imaging are highly unlikely to result in false‐positive findings. This finding supports the clinical validity of this method. [ABSTRACT FROM AUTHOR]

This paper introduces a new concept of slow-time spatial frequency space, also known as “slow-time $k$ -space,” and redefines the associated cross-range bandwidth, which arises naturally from Doppler radar tomography. The slow-time $k$ -space is the most suitable for narrow-band radar imaging, and can be augmented for higher resolution imaging by appropriate signal processing. The respective relationships with the more traditional concepts of fast-time $k$ -space and signal (or range) bandwidth are explained. We also discuss image resolution limits and demonstrate the concepts with simulated data examples. [ABSTRACT FROM AUTHOR]

A concept of invertible Radon-to-Helmholtz mapping is proposed as a model of directed (i.e., paraxial) wave scattering. It is shown that not only the Mazar-Felsen (MF) solution, but also Born and Rytov approximations can be expressed in terms of a propagation operator that transforms (the complex exponential of) a linogram of the illuminated object into a set of its diffraction patterns. Since the propagation operator is easily invertible, a unified approach, based on either of these approximations, may be used to recover the scattering potential. For a purely refractive phantom, the superiority of the MF propagator as compared to the classical perturbative solutions is demonstrated. [ABSTRACT FROM AUTHOR]

When applying the non-stationary simultaneous iterative methods for solving an ill-posed set of linear equations, the error usually initially decreases but after some iterations, depending on the amount of noise in the data, and the degree of ill-posedness, it starts to increase. This phenomenon is called semi-convergence. We study the semi-convergence behavior of the non-stationary simultaneous iterative methods and obtain an upper bound for data error (noise error). Based on this bound, we propose new ways to specify the relaxation parameters to control the semi-convergence. The performance of our strategies is shown by examples taken from tomographic imaging.

The combination of tomographic imaging and deep learning, or machine learning in general, promises to empower not only image analysis but also image reconstruction. The latter aspect is considered in this perspective article with an emphasis on medical imaging to develop a new generation of image reconstruction theories and techniques. This direction might lead to intelligent utilization of domain knowledge from big data, innovative approaches for image reconstruction, and superior performance in clinical and preclinical applications. To realize the full impact of machine learning for tomographic imaging, major theoretical, technical and translational efforts are immediately needed.

The safety diagnostic inspection of large plate structures, such as nuclear power plant containment liner plates and aircraft wings, is an important issue directly related to the safety of life. This research intends to present a more quantitative defect imaging in the structural health monitoring (SHM) technique by using a wide range of diagnostic techniques using guided ultrasound. A noncontact detection system was applied to compensate for such difficulties because direct access inspection is not possible for high-temperature and massive areas such as nuclear power plants and aircraft. Noncontact systems use unstable pulse laser and air-coupled transducers. Automatic detection systems were built to increase inspection speed and precision and the signal was measured. In addition, a new Difference Hilbert Back Projection (DHB) algorithm that can replace the reconstruction algorithm for the probabilistic inspection of damage (RAPID) algorithm used for imaging defects has been successfully applied to quantitative imaging of plate structure defects. Using an automatic detection system, the precision and detection efficiency of data collection has been greatly improved, and the same results can be obtained by reducing errors in experimental conditions that can occur in repeated experiments. Defects were made in two specimens, and comparative analysis was performed to see if each algorithm can quantitatively represent defects in multiple defects. The new DHB algorithm presented the possibility of observing and predicting the growth direction of defects through the continuous monitoring system.

Abstract We consider a flexible sequential block iterative method for the solution of consistent linear systems of equations and give its convergence analysis. The method is able to use weight matrices and relaxation parameters which can be updated in each iteration whereas the most of previous studies on sequential block iterative methods considered a finite number of weight matrices. Furthermore, we consider the constraint version of the method and give its convergence analysis for the special case of relaxation parameters and weight matrices. We report on some numerical tests with examples taken from the field of image reconstruction from projections. Our numerical results show considerable improvement, specially on noisy data, compared to the other methods which use finite number of weight matrices. [ABSTRACT FROM AUTHOR]