X-ray Computed Tomography Research Articles

Non-destructive larval infestation detection in pear fruits using deep learning and x-ray CT generated radiographs

Non-destructive larval infestation detection in pear fruits using deep learning and x-ray CT generated radiographs

A demonstration of a new energy dispersive X-ray CT simulation tool

A demonstration of a new energy dispersive X-ray CT simulation tool

Magnesium silicate chimneys at the Strytan hydrothermal field, Iceland, as analogues for prebiotic chemistry at alkaline submarine hydrothermal vents on the early Earth

The Strytan Hydrothermal Field (SHF) in basaltic terrain in Iceland is one of the extant alkaline submarine hydrothermal vent systems favoured as analogues for where life on Earth may have begun. To test this hypothesis we analyse the composition, structure, and mineralogy of samples from hydrothermal chimneys generated at the SHF. We find that the chimney precipitates are composed of Mg-silicates including clays of the saponite-stevensite group (high Mg and Si, low Fe and Al), Ca-carbonates and Ca-sulfates. The chimneys comprise permeable structures with pores sizes down to 1 µm or less. Their complex interiors as observed with SEM (Scanning Electron Microscopy) and X-ray CT (computed tomography scanning), exhibit high internal surface areas. EDX (energy-dispersive X-ray spectroscopy) analysis reveals an increase in the Mg/Si ratio toward the chimney exteriors. Chemical garden analogue experiments produce similar Mg–silicate chimneys with porous internal structures, indicating that injection-precipitation experiments can be high-fidelity analogues for natural hydrothermal chimneys at the SHF. We conclude that SHF chimneys could have facilitated prebiotic reactions comparable to those proposed for clays and silica gels at putative Hadean to Eoarchean alkaline vents. Analysis of the fluid dynamics shows that these chimneys are intermediate in growth rate compared to faster black smokers though slower than those at Lost City. The SHF is proposed as a prebiotic alkaline vent analogue for basaltic terrains on the early Earth.

Study on Fatigue Life of Aluminum Alloy 6061-T6 Based on Random Defect Characteristics.

A certain number of hole-like defects will occur in aluminum alloys under cyclic loading. The internal holes will reduce the strength of the material and cause stress concentration, which will aggravate the development of fatigue damage. A classification method of defect features based on X-ray CT damage data is proposed. The random hole distribution model is established through the linear congruence method and the region division method. The hole parameter is introduced as the intermediate variable of the 3D reconstruction model of internal defects. In the mesoscopic stage, the function relationship between the distribution of random holes and the fatigue life is established based on the coupling relationship between the number and proportion of pores and the fatigue life. In the macroscopic stage, the relationship between the random holes and the macroscopic crack growth life is established by taking the crack length as the damage variable. The crack propagation rate decreased with the increase in the number of holes. The prediction model of the whole life stage is established using the life function from microcrack initiation to macroscopic crack propagation. Finally, the validity of the whole stage fatigue life prediction model is demonstrated through the comparison and verification of experiments, which provides a certain engineering value for the life estimation of 6061-T6 aluminum alloy materials.

End-to-end multimodal 3D imaging and machine learning workflow for non-destructive phenotyping of grapevine trunk internal structure

Quantifying healthy and degraded inner tissues in plants is of great interest in agronomy, for example, to assess plant health and quality and monitor physiological traits or diseases. However, detecting functional and degraded plant tissues in-vivo without harming the plant is extremely challenging. New solutions are needed in ligneous and perennial species, for which the sustainability of plantations is crucial. To tackle this challenge, we developed a novel approach based on multimodal 3D imaging and artificial intelligence-based image processing that allowed a non-destructive diagnosis of inner tissues in living plants. The method was successfully applied to the grapevine (Vitis vinifera L.). Vineyard’s sustainability is threatened by trunk diseases, while the sanitary status of vines cannot be ascertained without injuring the plants. By combining MRI and X-ray CT 3D imaging with an automatic voxel classification, we could discriminate intact, degraded, and white rot tissues with a mean global accuracy of over 91%. Each imaging modality contribution to tissue detection was evaluated, and we identified quantitative structural and physiological markers characterizing wood degradation steps. The combined study of inner tissue distribution versus external foliar symptom history demonstrated that white rot and intact tissue contents are key-measurements in evaluating vines’ sanitary status. We finally proposed a model for an accurate trunk disease diagnosis in grapevine. This work opens new routes for precision agriculture and in-situ monitoring of tissue quality and plant health across plant species.

Comprehensive pore structure characterization and permeability prediction of carbonate reservoirs using high-pressure mercury intrusion and X-ray CT

Comprehensive pore structure characterization and permeability prediction of carbonate reservoirs using high-pressure mercury intrusion and X-ray CT

Comparison of Haller Index Values Calculated with Chest Radiographs versus Computed Tomography for Pectus Excavatum Evaluation

Objective: To compare and correlate the value of the Haller index calculated with chest x-ray with the values calculated with a Computed Tomography (CT) scan. Study Design: Cross-sectional study. Place and Duration of Study: Department of Radiology, Combined Military Hospital, Peshawar Pakistan, from Jan to Jun 2018. Methodology: A total of 50 male patients aged ≥16 years presenting with pectus excavatum were included. Haller index was calculated after CT scan and X-ray. Results: The mean age of the patients was 20.20±2.34 years. The mean Haller Index for CT scan was 2.35±0.39, and the mean Haller Index for X-ray was 2.01±0.45. A strong and positive correlation existed between the Haller index for CT scans and X-rays (r=0.83). Conclusion: X-rays can be used instead of CT scans to measure the Haller index and plan the surgical intervention with similar accuracy.

Development of a model for the differential diagnosis of community-acquired bacterial pneumonia and viral lung injury in hospitalized adult patients

Relevance. During and after the COVID-19 pandemic, viruses have become a more common cause of pulmonary infections in adults; therefore, the distinction between viral lung injury and community-acquired bacterial pneumonia is of increasing importance. Aim. Development of a model for differentiating community-acquired bacterial pneumonia and viral lung injury, including COVID-19. Materials and methods. This retrospective case–control study included 300 adult patients with viral lung injury and 100 adult patients with community-acquired bacterial pneumonia. Clinical, laboratory, and instrumental data were analyzed, significant factors were selected by which the samples differed, and a model was developed using logistic regression to distinguish between community-acquired bacterial pneumonia and viral lung damage, including COVID-19. Results. The developed model included the following parameters: total protein level, neutrophil/lymphocyte index, heart rate, unilateral infiltration on CT or chest x-ray, vasopressor prescription in the first 24 h of hospitalization, altered level of consciousness, chills, and fatigue. The model had the following characteristics: AUC = 0.94 (0.92–0.96), AUC_PR = 0.84 (0.76 to 0.92), prediction accuracy — 90%, sensitivity — 76%, specificity — 95%, positive predictive value — 83 %. Conclusion. The use of this model can facilitate the differential diagnosis of community-acquired bacterial pneumonia and viral lung injury, including COVID-19, in adults in general wards and intensive care units.

Effect of Al2O3 nanoparticles additions on wear resistance of plasma electrolytic oxidation coatings on TC4 alloys

To enhance the tribological properties of TC4 alloy, the plasma electrolytic oxidation (PEO) method was utilized to prepare the coating incorporated various contents of Al2O3 nanoparticles (0, 3, 6, 9, 12 and 15 g/L) on TC4 alloy. The phase composition, chemical compositions, elemental distribution and microstructure of the coatings were investigated by using X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM) with energy dispersive spectroscopy (EDS) and X-ray computer tomography (XCT). The results revealed that the introduction of Al2O3 nanoparticles into the electrolyte promoted the formation of Al2TiO5 phase in the PEO coatings, and most of the nanoparticles were embedded into the coatings which reduced porosity of the coatings, but increased surface roughness. Also, the increase in the addition of Al2O3 nanoparticles enhanced the microhardness of the PEO coatings due to the formation of Al2TiO5. The tribological behavior of the PEO coatings was improved significantly owing to the high microhardness and porous structure of the coatings. The primary wear mechanism of the coating with 12 g/L Al2O3 nanoparticles was abrasive wear as this coating formed a lubrication zone during the wear process. Besides, the friction coefficient and wear loss mass of the PEO coating prepared with 12 g/L Al2O3 nanoparticles additive exhibited the excellent wear resistance compared to its counterparts.

Comprehensive Study on Mineral Processing Methods and Mineral Technical Economics of Manganese Ore in Chongqing Chengkou.

Chongqing Chengkou manganese deposit is a large carbonate-type manganese deposit in the upper reaches of the Yangtze River, located in Gaoyan Town, Chengkou County, Chongqing. In order to improve the recovery rate of low-grade manganese ore and concentrate grade index, achieve efficient utilization of mineral resources, and sustainable development of Gaoyan manganese ore deposit in Chengkou, Chongqing, China, in this paper, by means of optical microscope analysis, high-resolution X-ray tomography technology, three-dimensional image analysis technology, X-ray diffraction analysis, X-ray fluorescence spectrum analysis, and technical and economic analysis, the occurrence state and process mineralogy of manganese are studied, and the technical and economic analysis of flotation, high-intensity magnetic separation, and gravity separation are carried out. It provides a reference for other mining enterprises to choose the most suitable beneficiation method according to the specific mineral species.

Research on the Multiscale Microscopic Pore Structure of a Coalbed Methane Reservoir

Coal rock pores are the space in which coalbed gas is stored and flows. Accurately characterizing the pore structure of coalbed gas is the foundation of coalbed gas reserve assessment and production forecasting. Traditional experimental methods are unable to characterize the multi-scale pore structure characteristics of coal rock. In this paper, a multi-scale pore structure characterization method is proposed by coupling various experimental methods, including low-pressure nitrogen gas adsorption experiments, X-ray computed tomography (XCT) imaging technology, and scanning electron microscopy (SEM). Using Zhengzhuang coalbed gas as an example, the micro-pore structure of coalbed gas reservoirs is characterized and depicted from a multi-scale perspective. The results indicate that a single experimental approach can only partially reveal the microstructure of coal rock pores. The combined use of multiple methods can accurately reveal the full-scale microstructure of coal rock pores. The pore structure of the experimental coal rock samples exhibits multi-scale characteristics, with a complex variety of pore types, including inorganic pores, organic pores, and fractures. Organic pores are predominant, with a small number of inorganic pores, and their sizes range from 2 nm to 50 μm. Mineral particles and fractures are observed at both the nanoscale and microscale, exhibiting typical multi-scale characteristics, with quartz being the predominant mineral.

Influence of hybrid steel-polyacrylonitrile fibers on the mechanical toughness and freeze-thaw resistance of sulfoaluminate cement composites

Sulfoaluminate cement (SAC), an environmentally friendly low-carbon cement, is commonly applied for rapid repair and construction. However, limited studies were conducted to elevate the performance of SAC-based materials by using the hybrid fiber modification, especially the durability. This study investigated the mechanical behaviors and freeze-thaw (F-T) resistance of SAC-based materials with hybrid steel-polyacrylonitrile (PAN) fibers, as well as their enhancement mechanism characterized using X-ray computed-tomography (CT) and scanning electron microscope. The results showed that incorporating hybrid fibers remarkably increased the flexural and compressive toughness of mortars, with steel fibers contributing the most critically. The fiber hybridization also significantly enhanced the F-T resistance of mortars, with PAN fiber being the main contributor. Specifically, the use of hybrid fibers caused a 61.0% improvement in the relative dynamic elastic modulus of mortars after 300 F-T cycles. CT scanning demonstrated that incorporating PAN fibers reduced the porosity of mortars and restrained the initiation and propagation of microcracks, while uniformly and randomly distributed steel fibers interspersed between macrocracks. Morphology observation illustrated that PAN fiber addition was conducive to enhance the anchoring force of steel fiber. Accordingly, the hybrid steel-PAN fibers contributed to suppress cracking at different scales and achieved a positive hybrid effect. At last, the results of this work provide a promising design solution for SAC-based composites to achieve better toughness and frost resistance.

A review of fracture propagation in concrete: fundamentals, experimental techniques, modelling and applications

A comprehensive overview of fracture propagation in concrete, covering various aspects ranging from fundamentals to applications and future directions, is presented. The introduction presents an overview of fracture propagation in concrete, emphasising its importance in understanding the behaviour of concrete structures. The fundamentals of fracture propagation are then explored, including concrete as a composite material, crack initiation and propagation mechanisms, types of fractures and the factors that influence fracture propagation. Next, experimental techniques for studying fracture propagation are discussed, encompassing both destructive and non-destructive testing methods, such as acoustic emission, ultrasonic testing, digital image correlation and advanced imaging techniques like X-ray computed tomography and scanning electron microscopy. Modelling approaches, including continuum damage mechanics, the finite-element method, the discrete-element method, the lattice discrete particle model and hybrid models, for simulating and predicting fracture propagation behaviour are then reviewed. The applications of fracture propagation in concrete are highlighted, including structural health monitoring, design optimisation, failure analysis and repair and rehabilitation strategies. Research opportunities for further improvement are addressed. This article should serve as a valuable resource for researchers, engineers and professionals in the field, providing a comprehensive understanding of fracture propagation in concrete and guiding future research endeavours.

Influence of Bioceramic Cements on the Quality of Obturation of the Immature Tooth: An In Vitro Microscopic and Tomographic Study.

The present in vitro study focuses on the filling ability of three different bioceramic cements with or without the addition of a bioceramic sealer in an open apex model on the marginal apical adaptation, tubule infiltrations, and void distributions as well as the interface between the cement and the sealer materials. To this end, sixty mandibular premolars were used. MTA-Biorep (BR), Biodentine (BD), and Well-Root Putty (WR) were used to obturate the open apex model with or without the addition of a bioceramic sealer, namely TotalFill® BC sealer™ (TF). A digital optical microscope and scanning electron microscope (SEM) were used to investigate the cement-dentin interface, marginal apical adaptation, and the material infiltration into the dentinal tubules. Micro-computed X-ray tomography and digital optical microscopy were used to investigate the cement-sealer interface. The results were analyzed by using the Kruskal-Wallis test. No significant difference was found between the groups for the marginal apical adaptation quality (p > 0.05). Good adaptation of the dentin-cement interface was found for all tested groups and the sealer was placed between the cement material and dentinal walls. All the groups demonstrated some infiltrations into the dentinal tubules at the coronal part except for the BR group. A good internal interface was found between the cement and the sealer with the presence of voids at the external interface. A larger number of voids were found in the case of the BD-TF group compared to each of the other two groups (p < 0.05). Within the limitations of the present in vitro study, all the groups demonstrated good marginal apical adaptation. The use of a sealer in an open apex does not guarantee good filling and, in addition, creates voids at the external interfaces with the dental walls when the premixed sealer is used with powder-liquid cement systems. The use of a premixed bioceramic cement could offer fewer complications than when a powder-liquid cement system is used.

Particle size analysis: A comparison of laboratory-based techniques and their application to geoscience

In sedimentary geoscience, the particle size distribution (PSD) of a sediment has a fundamental effect on a sediment's ability to be entrained, eroded, and deposited. Therefore, it is crucial to accurately measure the PSD of sediments. Several laboratory-based methods of particle size analysis are commonly employed in geoscience; however, each method is based on different principles and the comparison of data from one technique to another is challenging. In this study, we have compared the output of four commonly-used laboratory-based techniques: Laser Particle Size Analysis (LPSA), optical point counting, 2D automated image analysis, and X-ray Computed Tomography (XCT). Each technique has been used to measure eight samples of spherical silica particles, all prepared with known particle size ranges. Spherical particles have been used to minimise the effects of variable sorting and particle shape on data output. Here we have compared the differences between the measured PSD and descriptors of each PSD, showing that, at small particle diameters (<150 μm), all techniques agree. However, at particle diameters >150 μm, LPSA overestimates the size of particles, due to limitations in the way that particle diameter is calculated by this technique. In contrast, 2D automated image analysis and optical point counting underestimate the diameters of particles, due to stereology (e.g., the effect of slicing particles during thin section preparation). Results from XCT analyses have the lowest values of sorting (range of measured particle diameters) and are therefore the most tightly constrained. In addition, XCT is the only 3D analysis method, allowing particle shape, orientation, and intraparticle porosity to be measured for a volume of material. We therefore conclude that XCT is the most accurate way to determine a grain size distribution in sediments.

A simple image correlation technique for imaging subsurface damage from low-velocity impacts in composite structures

A robust computer vision system is proposed to visualize subsurface barely visible impact damage (BVID) in composite structures through a simple image correlation technique together with a damage imaging condition. This system uses a digital camera to record a video of the surface motion, capturing micron-scale dynamic movement from guided waves propagating on the surface of the structure generated via a sweeping frequency excitation (chirp) up to the ultrasonic frequency range. As the excitation frequency changes during the chirp, waves become trapped within this damaged region, forming standing waves to generate local resonance at specific frequencies. This localized resonance accumulates high wave energy in the region, generating a higher transverse displacement at the damage site compared to the remaining part of the structure. In this work, a simple image correlation technique is proposed to correlate each filtered video frame with the temporal mean of the filtered wavefield video to highlight standing waves at localized damage. The proposed image correlation technique is distinct from digital image correlation (DIC) since it does not use correlation for subset matching to track the movement of surface patterns between two images (video frames). Instead, it uses correlation to directly quantify similarities between corresponding image pixels (windows). Utilizing a single camera greatly simplifies system complexity and hence enhances the practicality and potential for real-time performance over a recently developed technique that utilized 3D DIC with a stereo camera for vision-based BVID detection. To realize the aim, work was conducted in two sequential steps: (1) off-axis 2D DIC was employed rather than 3D DIC to examine the potential of employing a single camera to capture images and extract not only in-plane displacement but also a fraction of transverse displacement in which local resonance is dominant and (2) image correlation was then employed, supplanting the off-axis 2D DIC image processing involved in the first step, to highlight the damage with significantly less processing complexity. This proposed technique using a zero-mean normalized cross-correlation imaging condition, rather than the total wave energy used for DIC-based approaches, is efficient and effective for identifying regions of minute surface movement from local resonance within the damage region without the use of the computationally intensive interpolation to get the sub-pixel gray level information followed by subset matching employed in DIC-based image processing. Two geometrically identical CFRP composite honeycomb panels that had been subjected to low-velocity impacts were used for verification and validation, and two excitation location configurations were tested for each panel. Damaged images produced with correlation for a 100 mm × 100 mm field of view using a single 3-s video, or a total of 19,200 video frames, show accurate damage imaging capabilities regardless of excitation location that exceed that of DIC techniques and is comparable to benchmark damage images obtained from laser Doppler vibrometry, ultrasonic C-scans, and X-ray CT scans. This success of correlation-based imaging of subsurface BVID demonstrates substantial improvements in efficiency and practicality and shows high potential for in situ and real-time computer vision-based nondestructive inspection or structural health monitoring of subsurface BVID in composite aircraft and other critical structures.

Mitigation of charge heterogeneity by uniform in situ coating enables stable cycling of LiCoO2 at 4.6V

LiCoO2 is a predominant cathode for lithium-ion batteries of portable electronics owing to its merit of high volumetric energy density. Nevertheless, it experiences rapid capacity deterioration under high voltages, concomitant with structural degradation and numerous intragranular cracks. Coating has been recognized as an efficacious strategy to ameliorate the decline in cycling performance of LiCoO2 at high voltages. Hence, a systematic elucidation of the precise mechanisms underlying the mitigation of structural degradation via coating layers assumes paramount importance in the context of advancing the next generation of high-voltage LiCoO2. In this work, the intricate interrelation among lithium-ion diffusion coefficients, charge heterogeneity, and crack distribution is explicated through techniques inclusive of galvanostatic intermittent titration technique (GITT), finite element analysis (FEA), and X-ray computed tomography (XCT). A robustly stable lithium-ion-conducting coating material serves the function of curtailing the occurrence of surface passivation layers, achieved by diminishing side reactions between the LiCoO2 and the electrolyte; while a uniform coating ensures a homogeneous lithium-ion flux, thereby mitigating charge heterogeneity and the resultant mechanical strain as well as intragranular cracks. Both are important elements that collectively allow the coating to effectively protect the surface from structural degradation, thus achieving superior performances upon high-voltage charging.

Optimizing liberation of phosphate ore through high voltage pulse fragmentation

This study investigates the selective high voltage pulse (HVP) fragmentation and its role in enhancing the metallurgical performance in phosphate ore processing. We have adapted the use of HVP fragmentation to enable the complete comminution of the considered ore, without the need for additional grinding steps. The efficiency of the HVP process strongly depends upon two parameters – the discharge ratio and the electric field, which, combined, allow for an improved liberation. Furthermore, for the same feed, the high voltage pulse fragmentation provides a coarser product with fewer fines. This study also emphasizes an improved liberation of the target mineral, carbonate fluorapatite, in the 100–315 μm fraction, while concentrating gangue minerals in the <100 μm size fraction. These findings are supported by X-ray tomography, validating the principle of pre-weakening induced by high voltage pulses on phosphate ore and further confirming the significance of our research.

Semi-supervised medical image classification via distance correlation minimization and graph attention regularization

We propose a novel semi-supervised learning method to leverage unlabeled data alongside minimal annotated data and improve medical imaging classification performance in realistic scenarios with limited labeling budgets to afford data annotations. Our method introduces distance correlation to minimize correlations between feature representations from different views of the same image encoded with non-coupled deep neural networks architectures. In addition, it incorporates a data-driven graph-attention based regularization strategy to model affinities among images within the unlabeled data by exploiting their inherent relational information in the feature space. We conduct extensive experiments on four medical imaging benchmark data sets involving X-ray, dermoscopic, magnetic resonance, and computer tomography imaging on single and multi-label medical imaging classification scenarios. Our experiments demonstrate the effectiveness of our method in achieving very competitive performance and outperforming several state-of-the-art semi-supervised learning methods. Furthermore, they confirm the suitability of distance correlation as a versatile dependence measure and the benefits of the proposed graph-attention based regularization for semi-supervised learning in medical imaging analysis.

X-ray CT quantification of in-situ fabric evolution and shearing behaviour of granular soils of different particle shapes

The role of particle shape on soil mechanical response has been studied extensively especially through numerical means. The underlying micro-mechanics of how particle shape may affect the soil mechanical responses at element scale remains unclear. Systematic micro-mechanical experiments that consider in-situ tracking of the evolution of fabric during the shearing process is missing. Aided by a miniaturised triaxial apparatus and X-ray computed tomography, this study presents a series of triaxial compression on four granular soils with different particle shapes yet the same mineralogy, grading and initial density. Evolution of three-dimensional soil fabric quantifiers during shearing was captured based on 192 full-field CT images. The results revealed that the initial shearing reduced the packing density without changing the particle packing pattern, followed by particle sliding and particle rotation which redistributed the force chains and formed a new packing pattern to resist shearing, causing strain localisation and reductions in both the contact number and concentration of contacts di-rection. Fabric anisotropy increased before reaching the peak and attained the maximum value as the soil approached the critical state. Particle shape, especially when quantified by overall regularity, or other combinations of descriptors, displayed more significant linear cor-relations with critical-state parameters than by local descriptor.