X-ray Computed Tomography Imaging Research Articles

Three-Dimensional X-Ray Computed Tomography Image Segmentation and Point Cloud Reconstruction for Internal Defect Identification in Laser Powder Bed Fused Parts

Abstract Defects shape, volume, and orientation all have a direct impact on the mechanical properties of Laser Powder Bed Fused (L-PBF-ed) parts. Therefore, it is necessary to evaluate and analyze the three-dimensional (3D) geometrical characteristics of these defects. X-ray Computed Tomography (XCT) can reveal an object's internal structure by volumetric scanning through its building direction. Point clouds are 3D data that can be extracted from the stack of XCT images taken from a part to perform further analysis. This study presents a novel approach for 3D segmentation and geometrical analysis of L-PBF defect structures from XCT images. The proposed method integrates Voronoi labeling and 3D point cloud reconstruction to reveal individual defect characteristics from the XCT image stack of a part. A case study showed the proposed methodology's effectiveness in identifying and characterizing defect regions in L-PBF-ed Cobalt-Chrome (CoCr) parts.

Prior function designs for X-ray reconstructions from limited angular views

The objectivity of three-dimensional imaging has placed X-ray Computed Tomography (CT) into an indispensable diagnostic method in clinical and industrial applications. Despite the advances in the X-ray CT imaging, high- resolution three-dimensional reconstruction of small details in objects with large in-plane dimensions has been a fundamental challenge for the conventional X-ray CT method. An alternative scanning geometry, where X-ray source and a detector move synchronously irradiating a specimen at an inclined angle, has been proposed to address this challenge. This work presents new designs of prior (or penalty) functions developed for reconstructing the radiography data obtained under the limited angular conditions. The new prior targets reduction of shape distortion artifacts, common for laminographic reconstructions, as well as preservation of small features, such as voids, edge details, and high-density inclusions. The novel prior function designs are demonstrated on the computational phantom of a specimen scanned under tilted planar CT geometry simulating large planar dimensions of a specimen. To accommodate physical CT scanning of such specimens, a novel microfocus X-ray CT scanning device that rotates X-ray source and moves the detector synchronously while staying on the same side of the test specimen (Inclined CT), is introduced. This device allows scanning of critical areas of up to 3-meter-wide and potentially unlimited length specimens with high resolution required for identification of manufacturing and structural defects typical for modern composite structural elements used in the aerospace industry.

Prediction of three-dimensional flow field inside realistic fibrous filter obtained from x-ray computed tomography images using deep convolutional neural networks

Deep-learning models garnered considerable attention in the field of fluid mechanics for physics discovery and approximation-model generation. This study aims to develop an approximation model to predict the flow field inside realistic fibrous filters based on an image-to-image approach to replace three-dimensional (3D) computational fluid dynamics (CFD) simulations, which are computationally expensive and difficult to apply to realistic fibrous filters. A data-driven framework is proposed using deep convolutional neural networks (CNNs) to provide a per-pixel prediction of the flow field. The model inputs are two-dimensional x-ray computed tomography images, whereas the outputs are the 3D distributions of the velocity vectors and pressure. High-resolution 3D CFD simulations are performed to create a database to train and test the CNN model. The model is applied to surgical and N95 face masks. The relative error of the CNN model over the test dataset is approximately 10% in regions with high velocity and pressure, and the model can provide a detailed high-resolution prediction of the flow field with a speedup of about three orders of magnitudes. A strict generalization test is conducted for completely unseen 3D segments with complex microstructures. The model generalizability still needs more improvements; however, the model can provide a low-resolution 3D flow field for those segments that can be used as the initial condition for CFD simulation to reduce the CFD computational time. This framework can be utilized for other types of filters and provides a basis for the design and optimization of fibrous filters.

Reducing Metal Artifacts in X-ray Computed Tomography Based on Metal Effect Estimation and Multiple CT Volume Fusion

In recent years, X-ray Computed Tomography (CT) has been widely used for investigating industrial parts. Many industrial parts often include metals, which cause various CT artifacts such as beam hardening artifacts, and metal artifacts. These CT artifacts lower the quality of X-ray CT images, prevent precise measurements. In order to reduce metal artifacts, here we propose using multiple X-ray CT scanning. Our multiple X-ray CT scanning method includes local artifacts estimation, proposing adequate multiple scanning angles, multiple scanned data registration and multiple CT data fusion. Based on local artifacts estimation, optimal multiple scan angles for data fusion are selected. Data registration and fusion are also based on local artifacts estimation, excluding effects of artifacts during the process. In order to demonstrate our method, we measured industrial parts which includes metals and resins, proposed optimal multiple scanning angles and conducted volume fusion. As a result, the metal artifacts in the CT volume reduced significantly compared to single X-ray CT scanning. Experiments also showed that metal artifacts in different regions are reduced by additional scans, which suggest that our scan angle selection method successfully selected optimal multiple scan angles.

Ring artifacts suppression for X-ray CT images by fusion of dual-domain images based on improved UNet

The ring artifact is a typical artifact in X-ray Computed Tomography (CT) images, the existence of which can reduce the image's quality, change the structure and details and affects the interpretation of image information. This paper conducts research from two aspects: tomographic images and sinograms, and designs a dual-domain artifact suppression network. By introducing the Inception module and the residual module, the network's ability to extract features is improved, and the gradient diffusion is suppressed. By customizing the loss function, the network's recognition of ring artifacts is improved and the network's convergence is accelerated. Finally, the outputs of the dual-domain are fused based on the Nonsubsampled Contourlet Transform (NSCT) fusion theory to improve the quality of the image. In addition, three experiments of CT scanning are designed based on microfocus cone-beam CT system to verify the effectiveness. The model is trained and tested using real datasets. Peak Signal-to-Noise Ratio (PSNR), Structural Similarity (SSIM), and Mean Squared Error (MSE) are employed as evaluation indicators of image quality. Finally, the proposed method is compared with typical algorithms for artifact suppression. The experimental results show that the method effectively protects the structure information in CT images while suppressing ring artifacts to the greatest extent. The PSNR, SSIM, and MSE of the processed images can respectively reach 36.167 dB, 0.9847 and 6.87 × e-4.

A microstructural insight into the compression behaviour of scaly clays

Scaly clays are intensely fissured clays with lens-shaped elements of millimetre size and they show a complex compression behaviour that poses challenges to the design and construction of geostructures (excavations, retaining diaphragms and tunnels). Scaly clays show a normal compression line (NCL) where plastic deformation accumulates, as typically observed in non-scaly clays. Yet the response observed upon unloading and subsequent reloading is very peculiar, (a) the unloading–reloading cycle is typically a closed loop with relatively large hysteresis; (b) the compressibility recorded at high overconsolidation ratio of the unloading or reloading branches is close to the NCL compressibility. This paper presents a microstructural study on an Italian scaly clay where scanning electron microscope observations are integrated with mercury intrusion porosimetry analyses and X-ray computed tomography images. The mechanism associated with the closing of inter-scale porosity and the generation of new intra-scale porosity was identified as the process responsible for the plastic deformation. Experimental observation of reconstituted clay showed a ‘quasi-reversible’ behaviour upon loading and unloading and a pore size distribution characterised only by interparticle porosity. The observation that unloading and reloading curves are parallel in natural and reconstituted clays, led to the postulation that the interparticle porosity is controlling the elastic response.

Use of X-ray CT Imaging to Quantitatively Analyze the Effects of the Pore Morphology on the Tensile Properties of CP-Ti L-PBF Materials

Use of X-ray CT Imaging to Quantitatively Analyze the Effects of the Pore Morphology on the Tensile Properties of CP-Ti L-PBF Materials

Contact area analysis of an asphalt-concrete boundary layer with X-ray computed tomography imaging

This study focusses on the bond between asphalt and concrete. The bond is a decisive factor for the transfer of traffic loads. A lack of bond between the layers can quickly reduce the load-bearing behavior and thus lead to pavement failure. In the literature, the bond between asphalt pavements and concrete substrates is usually analyzed using mechanical test methods. With mechanical test methods, the effects of interlocking, glue adhesion and friction, which have an effect at the layer boundary, are not considered individually. Based on previous findings, the aim of this study is to carry out a precise analysis of the bonding at the layer interface between concrete and asphalt using bitumen emulsion by means of measurements with a high-resolution X-ray computer tomography (CT). To determine the effect of the surface texture of the substrate, the investigations were carried out on milled and smooth surface textures. In addition to the variation of the substrate profiles, the influence of the application quantity of the bitumen emulsions C40 B5-S and C60 BP4-S was analyzed by spraying quantities of 90 g/m² and 180 g/m² bitumen after breaking. A newly developed method was used to determine the effective degree of gluing at the layer boundary, which allowed the bonding efficiency to be determined. The results of the calculated degree of gluing for the individual variants show that the highest degree of gluing of 61.94% is achieved with the smooth texture variant and high application quantity of bitumen emulsion. The lowest degree of gluing of 17.01% was achieved with the milled texture variant without the application of bitumen emulsion. Overall, the results showed that the degree of gluing was increased for both surface textures by applying the bitumen emulsion. Compared to the smooth texture, the milled textures exhibit a lower degree of gluing for both bitumen quantities, which could be explained by the distribution of the bitumen emulsions on the substrate profiles.

Simplified Beam Hardening Correction for Ultrafast X-ray CT Imaging of Binary Granular Mixtures.

Ultrafast X-ray computed tomography is an advanced imaging technique for multiphase flows. It has been used with great success for studying gas-liquid as well as gas-solid flows. Here, we apply this technique to analyze density-driven particle segregation in a rotating drum as an exemplary use case for analyzing industrial particle mixing systems. As glass particles are used as the denser of two granular species to be mixed, beam hardening artefacts occur and hamper the data analysis. In the general case of a distribution of arbitrary materials, the inverse problem of image reconstruction with energy-dependent attenuation is often ill-posed. Consequently, commonly known beam hardening correction algorithms are often quite complex. In our case, however, the number of materials is limited. We therefore propose a correction algorithm simplified by taking advantage of the known material properties, and demonstrate its ability to improve image quality and subsequent analyses significantly.

Spatiotemporal X-Ray Imaging of Neat and Viscosified CO2 in Displacement of Brine-Saturated Porous Media

Summary CO2 storage in saline aquifers may contribute to a 90% share in preventing emissions to the atmosphere. Due to low CO2 viscosity at the subsurface often found in supercritical (sc) conditions, the injected CO2 may spread quickly at the formation top and increase the probability of leakage. This work relates to improved CO2 storage in saline aquifers by effective viscosification of the sc-CO2 at very low concentrations of engineered oligomers and the effectiveness of slug injection of viscosified CO2 (vis-CO2). We present the results from X-ray computed tomography (CT) imaging to advance the understanding of two-phase CO2-brine flow in porous media and firmly establish the transport mechanisms. X-ray CT imaging of displacement experiments is conducted to quantify the in-situ sc-CO2 saturation spatiotemporally. In neat CO2 injection, gravity override and adverse mobility ratio may result in early breakthrough and low sweep efficiency. We find cumulative brine production from the fraction collector to be lower than X-ray CT imaging at 2 pore volume (PV) injection. The difference between the two is attributed to the solubility of the produced water in the produced CO2 at atmospheric pressure. We show that when the solubility is accounted for, there is a good agreement between direct measurements and in-situ saturation results. There are three reports (two by the same group) that oligomers of 1-decene (O1D) with six repeat units may have marginal CO2 viscosification. The majority of published work by other groups shows that O1D with six repeat units and higher are effective CO2 viscosifiers. In the past, we have demonstrated the effectiveness of an O1D in the displacement of brine by CO2 at a concentration of 1.5 wt%. The effectiveness is examined and identified by three different methods. In this work, we show that the same oligomer is effective at a low concentration of 0.6 wt%. The oligomer slows the breakthrough by 1.6 times and improves the brine production by 34% in the horizontal orientation. X-ray CT imaging results reveal that such a large effect may be from the increase in the interfacial elasticity. We also show that there is no need for continuous injection of the oligomer. A slug of 0.3 PV injection (PVI) of vis-CO2 followed by neat CO2 injection has the same effectiveness as the continuous injection of the vis-CO2. In this work, we also demonstrate the effectiveness of a new engineered molecule at 0.3 wt% that may increase residual trapping by about 35%. The combination of mobility control and residual brine saturation reduction is expected to improve CO2 storage by effective viscosification with low concentrations of oligomers.

Energy evolution and strain localization in fractured sandstone under freeze-thaw cycling and uniaxial loading-unloading

In cold regions, combined cyclic freeze-thaw (F-T) and loading-unloading can cause rock slope instability and sliding. The macro-failure of rock masses originates from the expansion of strain localization areas driven by energy. Therefore, a deep understanding of the energy evolution and strain distribution can reveal the instability process. Along these lines, in this work, intact and intermittently jointed sandstones were subjected to a cyclic F-T environment and subsequently carried out uniaxial graded loading-unloading to obtain their mechanical parameters and X-ray computed tomography images. By investigating the energy density, it was found that the input, elastic, dissipated, and damage energies all increased with loading according to a quadratic polynomial function, with the energies obeying a linear allocation law. Meanwhile, F-T changed the energy storage capacity and energy dissipation coefficient of the rock by causing meso-damage. To measure the meso-scale strain localization characteristics, the advanced digital volume correlation technique was also used to obtain three-dimensional strain fields. In terms of local strain, the failure behavior of intact specimens under the application of low and high numbers of F-T cycles was controlled by potential fracture bands and frost-heave cracks, respectively, while fractured specimens were mainly dependent on the macro-fracture arrangement. However, both frost heaving and thawing transformed sandstone from brittle to ductile. In terms of statistical strain, the equivalent strain (εeq) showed a log-normal distribution and continued to deviate to the right due to loading-unloading. Meanwhile, the normal strain (εxx, εyy, εzz) exhibited a normal distribution, where fractured sandstone mainly developed along with the slip direction. Finally, the intrinsic correlations among the energy parameters, meso-damage, and macro-failure were discussed. From our analysis, three stages of energy allocation and transformation were revealed, namely the uniform allocation of damage energy, banded accumulation of damage energy, and fracture caused by the elastic energy release.

Characterization of hydration levels of salt hydrate using X-ray computed tomography

Salt hydrates are promising phase change materials (PCMs) for energy storage due to their high enthalpy of fusion and cost-effectiveness. However, they face challenges like segregation. X-ray computed tomography (XCT) is suggested for non-destructive analysis to assess the formation of segregation. But first, the feasibility of using XCT to distinguish between different hydration levels of salt hydrates needs to be investigated. This study compares XCT gray values of anhydrous and salt hydrate samples, particularly sodium acetate (SA) hydrates, to understand the influence of hydration level on XCT images, aiming to assess XCT’s suitability for salt hydrate investigation.

Plateau stress estimation of aluminum foam by machine learning using X-ray computed tomography images

Plateau stress estimation of aluminum foam by machine learning using X-ray computed tomography images

Isocentric fixed angle irradiation-based DRR: a novel approach to enhance x-ray and CT image registration.

Objective.Digitally reconstructed radiography (DRR) plays an important role in the registration of intraoperative x-ray and preoperative CT images. However, existing DRR algorithms often neglect the critical isocentric fixed angle irradiation (IFAI) principle in C-arm imaging, resulting in inaccurate simulation of x-ray images. This limitation degrades registration algorithms relying on DRR image libraries or employing DRR images (DRRs) to train neural network models. To address this issue, we propose a novel IFAI-based DRR method that accurately captures the true projection transformation during x-ray imaging of the human body.Approach.By strictly adhering to the IFAI principle and utilizing known parameters from intraoperative x-ray images paired with CT scans, our method successfully simulates the real projection transformation and generates DRRs that closely resemble actual x-ray images.Main result.Experimental results validate the effectiveness of our IFAI-based DRR method by successfully registering intraoperative x-ray images with preoperative CT images from multiple patients who underwent thoracic endovascular aortic procedures.Significance. The proposed IFAI-based DRR method enhances the quality of DRR images, significantly accelerates the construction of DRR image libraries, and thereby improves the performance of x-ray and CT image registration. Additionally, the method has the generality of registering CT and x-ray images generated by large C-arm devices.

Hyperparameter tuning for deep learning semantic image segmentation of micro computed tomography scanned fiber-reinforced composites

Image segmentation with deep learning models has significantly improved the accuracy of the pixel-wise labeling of scientific imaging which is critical for many quantitative image analyses. This has been feasible through U-Net and related architecture convolutional neural network models. Although the adoption of these models has been widespread, their training data pool and hyperparameters have been mostly determined by educated guesses through trial and error. In this study, we present observations of how training data volume, data augmentation, and patch size affect deep learning performance within a limited data set. Here we study U-Net model training on four different samples of x-ray CT images of fiber-reinforced composites. Because the training process is not deterministic, we relied on seven-fold replication of each experimental condition to avoid under-sampling and observe model training variance. Unsurprisingly, we find greater training data volume strongly benefits individual models’ final accuracy and learning speed while depressing variance among replicates. Importantly, data augmentation has a profound benefit to model performance, especially in cases with a low abundance of ground truth, and we conclude that high coefficients of data augmentation should be used in scientific imaging semantic segmentation models. Future work to describe and measure image complexity is warranted and likely to ultimately guide researchers on the minimum required training data volume for particular scientific imaging deep learning tasks.

Yield stress modification of suspensions of irregularly shaped particles by addition of spherical colloidal silica

Magnesium hydroxide (Mg(OH)2) suspensions are encountered in the nuclear industry as legacy waste that is to be packaged for long-term storage. It is desirable to increase the solids content of the waste to minimize the total volume, yet this would produce high yield stress fluids that are difficult to process. However, high solids content suspensions of low yield strength are desired. Blending nano-silica (nano-SiO2) into a high yield stress suspension of 27 vol% Mg(OH)2, the suspension yield stress was reduced from 86 Pa to 47 Pa. X-ray CT imaging revealed that approximately two-thirds of the 3 vol% nano-SiO2 added to the Mg(OH)2 suspension was well-dispersed, with the rest forming large clusters that had minimal interaction with the Mg(OH)2 network. SEM images showed small aggregates/individual particles of nano-SiO2 dispersed between Mg(OH)2 particles. We conclude that the finely dispersed nano-SiO2 act like ball bearings to lubricate contacts between the irregularly shaped Mg(OH)2 particles, thus decreasing yield stress. When aging the samples for several days, the yield stress of the binary suspension increased, reversing the yield stress reduction that was observed within the first day. The network stiffening is attributed to the formation of magnesium silicate hydrate (MSH) due to a reaction between soluble Mg2+ and Si(OH)4. The MSH precipitates onto the nano-SiO2 to fuse particles together, thus reducing their effectiveness as flow modifiers. While this is a side effect of this particular binary suspension, the initial yield stress drop remains encouraging to provide the desired fluid conditions to process legacy wastes.

Engineering Nanozymes for Tumor Therapy via Ferroptosis Self-Amplification.

Ferroptosis induction is an emerging strategy for tumor therapy. Reactive oxygen species (ROS) can induce ferroptosis but are easily consumed by overexpressed glutathione (GSH) in tumor cells. Therefore, achieving a large amount of ROS production in tumor cells without being consumed is key to efficiently inducing ferroptosis. In this study, a self-amplifying ferroptosis-inducing therapeutic agent, Pd@CeO2-Fe-Co-WZB117-DSPE-PEG-FA (PCDWD), is designed for tumor therapy. PCDWD exhibits excellent multi-enzyme activities due to the loading of Fe-Co dual atoms with abundant active sites, including peroxidase-like enzymes, catalase-like enzymes, and glutathione oxidases (GSHOx), which undergo catalytic reactions in the tumor microenvironment to produce ROS, thereby inducing ferroptosis. Furthermore, PCDWD can also deplete GSH in tumor cells, thus reducing the consumption of ROS by GSH and inhibiting the expression of GSH peroxidase 4. Moreover, the photothermal effect of PCDWD can not only directly kill tumor cells but also further enhance its own enzyme activities, consequently promoting ferroptosis in tumor cells. In addition, WZB117 can reduce the expression of heat shock protein 90 by inhibiting glucose transport, thereby reducing the thermal resistance of tumor cells and further improving the therapeutic effect. Finally, X-ray computed tomography imaging of PCDWD guides it to achieve efficient tumor therapy.

Three-dimensional shape estimation of wires from three-dimensional X-ray computed tomography images of electrical cables

Three-dimensional shape estimation of wires from three-dimensional X-ray computed tomography images of electrical cables

A rigorous approach to the specific surface area evolution in snow during temperature gradient metamorphism

Abstract. Despite being one of the most fundamental microstructural parameters of snow, the specific surface area (SSA) dynamics during temperature gradient metamorphism (TGM) have so far been addressed only within empirical modeling. To surpass this limitation, we propose a rigorous modeling of SSA dynamics using an exact equation for the temporal evolution of the surface area, fed by pore-scale finite-element simulations of the water vapor field coupled with the temperature field on X-ray computed tomography images. The proposed methodology is derived from the first principles of physics and thus does not rely on any empirical parameter. Since the calculated evolution of the SSA is highly sensitive to fluctuations in the experimental data, we quantify the impact of these fluctuations within a stochastic error model. In our simulations, the only poorly constrained physical parameter is the condensation coefficient α. We address this problem by simulating the SSA evolution for a wide range of α values and estimate optimal values by minimizing the differences between simulations and experiments. This methodology suggests that α lies in the intermediate range 10-3<α<10-1 and slightly varies between experiments. Also, our results suggest a transition of the value of α in one TGM experiment, which can be explained by a transition in the underlying surface morphology. Overall, we are able to reproduce very subtle variations in the SSA evolution with correlations of R2=0.95 and 0.99, respectively, for the two TGM time series considered. Finally, our work highlights the necessity of including kinetic effects and of using realistic microstructures to comprehend the evolution of SSA during TGM.

491 Clinical and Radiographic Features of Mesenteric Ischemia after Intra-Aortic Balloon Pump Placement

OBJECTIVES/GOALS: Intra-aortic balloon pumps are commonly used as circulatory support in patients with critically reduced cardiac function. The goal of this study is to estimate the incidence of mesenteric ischemia as an understudied vascular complication and to describe the clinical and radiographic characteristics of patients experiencing this complication. METHODS/STUDY POPULATION: We will be conducting a retrospective analysis of the electronic medical records of all patients who underwent intra-aortic balloon pump (IABP) placement between October 2020 and April 2023 at our academic medical center to identify the incidence of mesenteric ischemia. We will describe the clinical course of these patients and characterize them based on demographic features and risk factors for vascular complications including medical comorbidities. Finally, we will assess available chest x-ray and thoracoabdominal CT imaging for adequacy of balloon tip positioning, concordance between balloon size and aortic dimensions, and compromise of any visceral arteries in patients who experienced mesenteric ischemia vs. those who did not. RESULTS/ANTICIPATED RESULTS: We anticipate approximately 150 patients to have recieved IABPs over this period with at least 4 known cases of mesenteric ischemia. We will describe the clinical presentation of these cases and their often fatal outcomes. We expect several known risk factors will be present in these patients, including history of peripheral vascular disease, diabetes, or smoking history. On chest x-ray, we predict balloon tip positioning to be suboptimal (defined as >5cm below the aortic arch) in many patients, both those with mesenteric ischemia and those without, but a greater discordance on CT imaging between balloon size and aortic dimensions with greater evidence of visceral compromise in patients with mesenteric ischemia compared to those without. DISCUSSION/SIGNIFICANCE: Mesenteric ischemia is a serious and poorly studied complication of intra-aortic balloon pumps. Understanding the hospital course, clinical characteristics, and radiographic features present in these patients may guide clinicians in the early recognition and management of this potentially fatal complication.