Search Results (33)

While advanced imaging techniques and ordered porous materials like MOFs have gained prominence, gas sorption remains the indispensable tool for characterizing the multiscale heterogeneity of industrially important disordered solids, such as catalysts and shales. This review examines recent developments in gas sorption methodologies specifically tailored for rigid, disordered porous media. We discuss experimental advances, including the choice of adsorbate and the utility of the overcondensation method for probing macroporosity and ensuring saturation. Furthermore, we critically evaluate theoretical approaches for determining pore size distributions (PSDs), contrasting classical methods with Density Functional Theory (DFT) and Grand Canonical Monte Carlo (GCMC) simulations. Special emphasis is placed on the impact of pore-to-pore cooperative effects, such as advanced condensation, cavitation, and pore-blocking, on the interpretation of sorption isotherms. We highlight how complementary techniques, including integrated mercury porosimetry, NMR, and computerized X-ray tomography (CXT), are essential for deconvolving these complex network effects and validating void space descriptors. We conclude that, while “brute force” molecular simulations on image-based reconstructions are progressing, “minimalist” pore network models, which incorporate cooperative mechanisms, currently offer the most empirically adequate approach. Ultimately, gas sorption remains unique in its ability to statistically characterize void spaces from Angstroms to millimeters in a single experiment. Full article

Objective: To evaluate the three-dimensional (3D) angular displacement (Roll, Yaw, and Pitch) of the upper cervical vertebrae (C1, C2, and C3) in patients with severe mandibular deviation (MD) due to condylar hyperplasia (CH), utilizing a computed tomography (CT)-based segmentation approach. Methods: This retrospective cross-sectional study included 50 patients with MD ≥ 6 mm caused by hemimandibular elongation (HE) or a hybrid form (HF) of CH. The skull, mandible, and cervical vertebrae (C1–C3) were segmented using 3D Slicer software. Angular deviations (Pitch, Yaw, Roll) were measured relative to the Frankfurt plane. Patients were categorized by the side of CH (right or left), and intergroup comparisons were performed using Kruskal–Wallis and Mann–Whitney U tests. Spearman’s correlation analyses assessed associations between MD magnitude and cervical angles. Results: CH was significantly more prevalent in females (58%; p = 0.021). C2 and C3 exhibited significantly increased lateral Roll inclination toward the side of deviation (p = 0.006 and p = 0.045, respectively). C2 Pitch negatively correlated with MD severity bilaterally (r ≈ −0.51, p = 0.02 right; r ≈ −0.50, p = 0.02 left). Strong intra-vertebral correlations between Pitch and Yaw were observed in C1 and C2, indicating synchronized vertical and rotational motion. No significant intergroup differences were found in Yaw angles (p > 0.05). Conclusions: Patients with CH and severe MD exhibit consistent patterns of 3D cervical displacement, particularly in lateral inclination and vertical movement, suggesting compensatory postural adaptations in the upper cervical spine. Full article

Background/Objectives: Limb malalignment disrupts physiological joint forces and predisposes individuals to the development of osteoarthritis. Surgical interventions such as distal femur or high tibial osteotomy aim to restore mechanical balance on weight-bearing joints, thereby reducing long-term morbidity. Accurate alignment is crucial since it cannot be adjusted after stabilization with plates and screws. Recent advances in personalized medicine offer the opportunity to tailor surgical corrections to each patient’s unique anatomy and biomechanical profile. This study evaluates the benefits of 3D planning and patient-specific cutting guides over traditional 2D planning with standard implants for alignment correction procedures. Methods: We assessed limb alignment parameters pre- and postoperatively in patients with varus and valgus lower limb malalignment undergoing acute realignment surgery. The cohort included 23 opening-wedge high tibial osteotomies and 28 opening-wedge distal femur osteotomies. We compared the accuracy of postoperative alignment parameters between patients undergoing traditional 2D preoperative X-ray planning and those using 3D reconstructions of CT data. Outcome measures included mechanical axis deviation and tibiofemoral angles. Results: 3D reconstructions of computerized tomography data and patient-specific cutting guides significantly reduced the variation in postoperative limb alignment parameters relative to preoperative goals. In contrast, traditional 2D planning with standard non-custom implants resulted in higher deviations from the targeted alignment. Conclusions: Utilizing 3D CT reconstructions and patient-specific cutting guides enhances the accuracy of postoperative limb realignment compared to traditional 2D X-ray planning with standard non-custom implants. Patient-specific instrumentation and personalized approaches represent a key step toward precision orthopedic surgery, tailoring correction strategies to individual patient anatomy and potentially improving long-term joint health. This improvement may reduce the morbidity associated with lower limb malalignment and delay the onset of osteoarthritis. Level of Evidence: Therapeutic Level III. Full article

As a novel pavement wear layer material, the micromechanical mechanisms of High-toughness Ultra-thin Friction Course (HUFC) have not been fully elucidated. This paper presents a new method for the three-dimensional micromechanical simulation of high-toughness asphalt mixtures based on a viscoelastic parameter calibration model. X-ray Computerized Tomography (CT) was employed to scan samples of high-toughness asphalt mixtures to obtain detailed information on the internal structure (aggregate, fine aggregate matrix FAM and voids), and a three-dimensional micromechanical model was constructed based on the real-scale distribution of these components. Aggregates in the high-toughness asphalt mixture were modeled as elastic bodies, while FAM was treated as a viscoelastic material characterized by the Burgers model. Using the Boltzmann linear superposition principle and Laplace transform theory, the viscoelastic properties of FAM were converted into Prony parameters recognizable by finite element software, and the viscoelastic parameters were calibrated. Micromechanical simulations were conducted for three different gradings of high-toughness asphalt mixtures, and the results show that the predicted deformation closely matched the measured deformation. This method accurately reflects the deformation characteristics of different gradings of high-toughness asphalt mixtures, overcoming the limitations of traditional numerical simulations based on homogeneous material models. It represents an advancement and refinement of micromechanical simulation methods for high-toughness asphalt mixtures. Full article

Introducing a hybrid imaging approach, such as single-photon emission computerized tomography with X-ray computed tomography (SPECT)/CT, improves diagnostic accuracy and patient management. The ongoing advancement of SPECT hardware and software has resulted in the clinical application of novel approaches. For example, whole-body SPECT/CT (WB-SPECT/CT) studies cover multiple consecutive bed positions, similar to positron emission tomography-computed tomography (PET/CT). WB-SPECT/CT proves to be a helpful tool for evaluating bone metastases (BM), reducing equivocal findings, and enhancing user confidence, displaying effective performance in contrast to planar bone scintigraphy (PBS). Consequently, it is increasingly utilized and might substitute PBS, which leads to new questions and issues concerning the acquisition protocol, patient imaging time, and workflow process. Therefore, this review highlights various aspects of WB-SPECT/CT acquisition protocols that need to be considered to help understand WB-SPECT/CT workflow processes and optimize imaging protocols. Full article

Obesity is a chronic relapsing disease and a major public health concern due to its high prevalence and associated complications. Paradoxically, several studies have found that obesity might positively impact the prognosis of patients with certain existing chronic diseases, while some individuals with normal BMI may develop obesity-related complications. This phenomenon might be explained by differences in body composition, such as visceral adipose tissue (VAT), total body fat (TBF), and fat-free mass (FFM). Indirect measures of body composition such as body circumferences, skinfold thicknesses, and bioelectrical impedance analysis (BIA) devices are useful clinically and in epidemiological studies but are often difficult to perform, time-consuming, or inaccurate. Biomedical imaging methods, i.e., computerized tomography scanners (CT scan), dual-energy X-ray absorptiometry (DEXA), and magnetic resonance imaging (MRI), provide accurate assessments but are expensive and not readily available. Recent advancements in 3D optical image technology offer an innovative way to assess body circumferences and body composition, though most machines are costly and not widely available. Two-dimensional optical image technology might offer an interesting alternative, but its accuracy needs validation. This review aims to evaluate the efficacy of 2D and 3D automated body scan devices in assessing body circumferences and body composition. Full article

Discrete tomography is a specific case of computerized tomography that deals with the reconstruction of objects made of a few density values on a discrete lattice of points (integer valued coordinates). In the general case of computerized tomography, several hundreds of projections are required to obtain a single high-resolution slice of the object; in the case of discrete tomography, projections of an object made by just one homogeneous material are sums along very few angles of the pixel values, which can be thought to be 0’s or 1’s without loss of generality. Genetic algorithms are global optimization techniques with an underlying random approach and, therefore, their convergence to a solution is provided in a probabilistic sense. We present here a genetic algorithm able to straightforwardly reconstruct binary objects in the three-dimensional space. To the best of our knowledge, our methodology is the first to require no model of the shape (e.g., periodicity, convexity or symmetry) to reconstruct. Experiments were carried out to test our new approach in terms of computational time and correctness of the solutions. Over the years, discrete tomography has been studied for many interesting applications to computer vision, non-destructive reverse engineering and industrial quality control, electron microscopy, X-rays crystallography, biplane angiography, data coding and compression. Full article

The utilization of reclaimed asphalt pavement (RAP) could reduce the cost of pavements containing epoxy polymer (EP) materials. This study was aimed at improving the homogeneity of an EP-reclaimed asphalt mixtures (ERAMs) at both the micro- and meso-scale to provide a reference for an ERAM production process. At the microscale, nanoindentation tests were conducted to characterize the diffusion between the EP and aged asphalt mastic. At the mesoscale, computerized tomography (CT) X-ray scanning and MATLAB analysis were employed to investigate the distribution of the aggregate within the ERAM. The results revealed that mixing temperature played a significant role in the diffusion and distribution between the EP and the aged asphalt mastic, thus impacting the mechanical properties of the material. Heating at 180 °C (the recommended mixing temperature of EP) resulted in a wider blending zone between the EP and the aged asphalt mastic compared to heating at 160 °C (the usual mixing temperature of ordinary reclaimed asphalt mixtures). The overall dispersion of the aggregate in the ERAM exhibited greater homogeneity in the vertical direction than in the horizontal direction. Adjusting the gradation of the RAP was found to be effective in reducing horizontal variability in the distribution of the coarse aggregate, fine aggregate, and air voids in the ERAM. Adjusting the RAP gradation further enhanced the vertical homogeneity in the distribution of the fine aggregate, while its impact on the vertical distribution of the coarse aggregate was minimal. Short-term aging led to increased variability in the distribution of the coarse aggregate, fine aggregate, and air voids within the ERAM. However, adjusting the gradation was effective in mitigating the adverse effects of short-term aging on both horizontal and vertical homogeneity in the aggregate distribution. Full article

Injecting CO₂ into tight oil reservoirs is a potential approach for enhanced oil recovery (EOR) and CO₂ sequestration. However, the effects of different pore-scales on EOR are poorly understood, and this has a significant impact on recovery. In this paper, a pore size correction model based on X-ray computerized tomography (CT) and nuclear magnetic resonance (NMR) was developed in order to establish the relationship between the pore radius and the transverse relaxation time. Different pore-scales are divided according to the cumulative distribution characteristics of the transverse relaxation time (T₂). CO₂ flooding and huff-n-puff experiments were conducted to investigate the dynamic displacement behaviors in different pore-scales. The results indicate that there are three pore-scales: micropores (T₂ < 0.3 ms), intermediate pores (0.3 ms < T₂ < 100 ms), and macropores (100 ms < T₂). However, there are also pseudo-sweep pores (PPs), equilibrium pores (EPs), and sweep pores (SPs) in the intermediate pores, depending on whether crude oil has been produced. Interestingly, the pressurization process causes some crude oil in the large pores to be squeezed into small pores. The recovery of CO₂ huff-n-puff (19.75%) is obviously lower than that of CO₂ flooding (51.61%). Specifically, it was observed that the micropores (−8%) and the pseudo-sweep pores (−37%) have a negative impact on oil recovery, whereas all pore-scales exhibit positive effects during CO₂ flooding. In addition, it was found that the critical pore radiuses of CO₂ flooding and huff-n-puff were 2.61 ms (0.15 µm) and 25 ms (1.5 µm), respectively, in the experiments, and that there is also more oil remaining in the macropores and the sweep pores during CO₂ huff-n-puff. These results provide a deeper understanding of the displacement behaviors of different pore-scales in tight oil reservoirs. Full article

This work presents a new approach to investigating water conduction properties in real three-dimensional (3D) voids of asphalt mixtures. Three different molding methods were employed for the same grade of asphalt mixture, and the three asphalt mixture specimens were scanned using X-ray Computerized Tomography (CT) to identify the real 3D void structure distribution inside the mixture. The real 3D behavior of void moisture conduction inside the mixture was simulated using the discrete lattice Boltzmann method and the BGK collision model. Three different molding methods were used to study the behavior of mesoscopic seepage inside the specimen. The results show that water conduction varies substantially in real 3D voids inside diverse molded objects. Regardless of flow and flow velocity, the Superpave Gyratory Compactor (SGC) method is extraordinarily close to the conduction qualities of the actual field core material. It shows that the Marshall molding method is inconsistent with the actual pavement molding method, and the SGC method can not only ensure that the reasonable void ratio is conducive to the thermal expansion and cold shrinkage space of the asphalt mixture but also prevents rainwater from entering the asphalt mixture. This work provides a new perspective for the study of water damage resistance and medium transmission characteristics of asphalt mixtures. Full article

In this investigation, an automotive component made of nylon as a structural element was studied by several characterization techniques to identify material properties. Firstly, a Fourier transform infrared spectroscopy (FTIR) was carried out to obtain information about composition, then, differential scanning calorimetry (DSC) was used to extract useful information on sample thermal behavior. The humidity and volatile materials percentage could be assessed by thermogravimetry analysis (TGA). Morphology and topography were carried out by optical microscopy, moreover, X-ray Tomography allows it to display the sample’s inner part. Characterization shows that the component could have been contaminated or exposed to conditions that promote degradation after the manufacturing process. Finally, computerized X-ray tomography displayed that both samples showed a difference in porosity in a fractured sample and a healthy sample. All the above implies a change in the mechanical integrity of the fractured material but might not omit the fact that it could have been subjected to any type of impact or mechanical effort. Full article

SARS-CoV-2 is a novel virus that has been affecting the global population by spreading rapidly and causing severe complications, which require prompt and elaborate emergency treatment. Automatic tools to diagnose COVID-19 could potentially be an important and useful aid. Radiologists and clinicians could potentially rely on interpretable AI technologies to address the diagnosis and monitoring of COVID-19 patients. This paper aims to provide a comprehensive analysis of the state-of-the-art deep learning techniques for COVID-19 classification. The previous studies are methodically evaluated, and a summary of the proposed convolutional neural network (CNN)-based classification approaches is presented. The reviewed papers have presented a variety of CNN models and architectures that were developed to provide an accurate and quick automatic tool to diagnose the COVID-19 virus based on presented CT scan or X-ray images. In this systematic review, we focused on the critical components of the deep learning approach, such as network architecture, model complexity, parameter optimization, explainability, and dataset/code availability. The literature search yielded a large number of studies over the past period of the virus spread, and we summarized their past efforts. State-of-the-art CNN architectures, with their strengths and weaknesses, are discussed with respect to diverse technical and clinical evaluation metrics to safely implement current AI studies in medical practice. Full article

This study proposes a deep-learning-based solution (named CapsNetCovid) for COVID-19 diagnosis using a capsule neural network (CapsNet). CapsNets are robust for image rotations and affine transformations, which is advantageous when processing medical imaging datasets. This study presents a performance analysis of CapsNets on standard images and their augmented variants for binary and multi-class classification. CapsNetCovid was trained and evaluated on two COVID-19 datasets of CT images and X-ray images. It was also evaluated on eight augmented datasets. The results show that the proposed model achieved classification accuracy, precision, sensitivity, and F1-score of 99.929%, 99.887%, 100%, and 99.319%, respectively, for the CT images. It also achieved a classification accuracy, precision, sensitivity, and F1-score of 94.721%, 93.864%, 92.947%, and 93.386%, respectively, for the X-ray images. This study presents a comparative analysis between CapsNetCovid, CNN, DenseNet121, and ResNet50 in terms of their ability to correctly identify randomly transformed and rotated CT and X-ray images without the use of data augmentation techniques. The analysis shows that CapsNetCovid outperforms CNN, DenseNet121, and ResNet50 when trained and evaluated on CT and X-ray images without data augmentation. We hope that this research will aid in improving decision making and diagnostic accuracy of medical professionals when diagnosing COVID-19. Full article

Diagnostic technologies using X-rays and/or acoustic emissions for concrete infrastructures containing internal pores, defects, and cracks have attracted considerable interest. However, computerized tomography (CT) for concrete is challenging due to its radiation shielding characteristics. Electrical impedance tomography (EIT), initially developed for medical use, has recently shown a potential for developing a macro-CT technique for concrete structures. This study derived EIT analytical solutions for rectangular cement-based samples and validated them with experimental data obtained from cubic mortar samples. The experimental validation of the three mathematical functions (Dirac delta, Heaviside step, and Gaussian) used as current injection models, the Gaussian function produced the lowest relative absolute error (4.02%). This study also explored appropriate experimental setups for cement-based materials, such as Shunt model, current flow paths, and potential distribution. Full article

Many clinical conditions require radiological diagnostic exams based on the emission of different kinds of energy and the use of contrast agents, such as computerized tomography (CT), positron emission tomography (PET), magnetic resonance (MR), ultrasound (US), and X-ray imaging. Pregnant patients who should be submitted for diagnostic examinations with contrast agents represent a group of patients with whom it is necessary to consider both maternal and fetal effects. Radiological examinations use different types of contrast media, the most used and studied are represented by iodinate contrast agents, gadolinium, fluorodeoxyglucose, gastrographin, bariumsulfate, and nanobubbles used in contrast-enhanced ultrasound (CEUS). The present paper reports the available data about each contrast agent and its effect related to the mother and fetus. This review aims to clarify the clinical practices to follow in cases where a radiodiagnostic examination with a contrast medium is indicated to be performed on a pregnant patient. Full article