Search Results (2,364)

Background/Objectives: Lisfranc joint injuries are complex midfoot pathologies frequently associated with subtle radiologic findings and delayed diagnosis. Although ligamentous disruption is considered the primary mechanism, the contribution of intrinsic osseous morphology remains insufficiently investigated. Previous studies have primarily relied on two-dimensional measurements and limited morphometric parameters. Therefore, this study aimed to provide a comprehensive three-dimensional (3D) computed tomography (CT) based morphometric evaluation of the medial and central columns of the Lisfranc joint and to determine whether specific bony parameters are associated with injury predisposition. Methods: A total of 48 CT scans, including 23 from patients with Lisfranc joint injuries and 25 from healthy controls without midfoot trauma, were retrospectively analyzed. For both groups, 3D models of the first three metatarsals (M1–M3) and cuneiforms (C1–C3) were reconstructed to measure bone length, articular surface areas, volumes, M1–M2/M2–M3 depth differences, and dorsal step-off (dorsal subluxation of M2 relative to C2). Correlations of these measurements with M2 length were additionally assessed in each group. Results: Comparisons between injury and healthy control groups revealed no significant differences in bony morphometrics (p > 0.05). Correlation analysis showed that a longer M2 were associated with greater cuneiform volumes and larger metatarsal articular surface areas (p < 0.05). Conclusions: This comprehensive 3D morphometric assessment of the Lisfranc joint indicates that intrinsic bony anatomy alone is unlikely to represent a primary predisposing factor for Lisfranc injuries. The observed positive relationship between M2 length and cuneiform articular surface areas and volumes demonstrates structural interdependence within the medial and central columns. Overall, injury susceptibility does not appear to be explained by variations in osseous morphology alone. Full article

The load of the elastic tooth drum-type pepper harvester is a key parameter affecting harvesting efficiency and quality. Real-time analysis and prediction of drum load are crucial for stabilizing harvester operation and optimizing performance. Existing research focuses on either machine vision-based image analysis, which is difficult to collect in the field, or parameter-mapping methods, which suffer from time lag. This study proposes a GARCH-KPCA-ATLSTM method for load prediction, combining the generalized autoregressive conditional heteroskedasticity (GARCH) model, kernel principal component analysis (KPCA), and attention-enhanced long short-term memory (ATLSTM). EMD is first applied to denoise and reconstruct the load signal, removing mechanical vibration and other interferences. Conditional heteroskedasticity is confirmed, and the GARCH series (one symmetric and three asymmetric models) is introduced to extract fluctuation features. KPCA reduces dimensionality, removing redundant information and saving 2.91 s in computation while slightly improving accuracy. Additive attention in LSTM emphasizes critical information, enhancing learning of nonlinear relationships and further improving prediction. Comparative experiments demonstrate the model’s reliability. The method achieves RMSE = 0.911, MAE = 0.682, MBE = −0.025, MAPE = 1.147%, R² = 0.968, with a runtime of 2.023 s, confirming high accuracy and stability. This study provides a theoretical and technical foundation for real-time load prediction of pepper harvesters. Full article

Three-Dimensional (3D) face reconstruction from monocular Red-Green-Blue (RGB) imagery remains a fundamental yet ill-posed challenge in computer vision, with applications in biometrics, augmented reality/virtual reality (AR/VR), and intelligent visual sensing systems. While deep learning has significantly improved reconstruction fidelity and realism, existing surveys primarily focus on network architectures in isolation, often overlooking how sensing conditions, data acquisition protocols, and geometric calibration influence reconstruction reliability and evaluation outcomes. This paper presents a sensor-aware, end-to-end review of deep learning-based 3D face reconstruction and introduces a unified modular framework that connects sensing hardware, data acquisition, calibration, representation learning, and geometric refinement within a coherent pipeline. The reconstruction process is organized into four stages: sensor-driven acquisition and calibration, landmark estimation and feature extraction, 3D representation and parameter regression, and iterative refinement via differentiable rendering. Within this framework, we examine how sensor characteristics, calibration accuracy, representation models, and supervision strategies affect reconstruction accuracy, perceptual quality, robustness, and computational efficiency. We further synthesize the reported results across widely used benchmarks using both geometric and perceptual metrics, highlighting trade-offs between reconstruction fidelity and deployment constraints. By integrating sensing-aware analysis with architectural evaluation, this survey provides practical insights for developing scalable and reliable 3D face reconstruction systems under real-world conditions. Full article

Femtosecond laser processing has become a powerful approach for high-precision micro- and nanofabrication in transparent materials, owing to its ultrashort pulse duration and minimized thermal effects. However, the limited predictability of processing depth remains a major obstacle to practical applications. Here, we present a morphology prediction framework for femtosecond Bessel laser processing of ZnS that integrates plasma physics modeling with deep learning. Through combined experimental measurements and plasma physics simulations, the influence of laser pulse energy on electron density evolution and material removal depth is systematically investigated. The results reveal the dominant roles of multiphoton ionization, avalanche ionization, and free-electron dynamics in deep-volume processing, and demonstrate the strong sensitivity of the processing morphology to the plasma distribution. Conventional plasma models can accurately reproduce the ablation diameter, yet exhibit significant limitations in predicting the processing depth. We propose a physics data-based framework for femtosecond Bessel beam processing, which integrates a depth-residual regression network conditioned on the peak electron density distribution to effectively learn and compensate for systematic modeling errors in plasma-based simulations. This strategy leads to excellent agreement between predicted and experimental processing depths and three-dimensional morphologies under various energy conditions. The model achieves a mean absolute error (MAE) of 4.9 nm at the pixel level for 3D crater reconstruction. Under rigorous crater-grouped cross-validation with Leave-One-Group-Out evaluation, the model achieves a mean R² of 0.74 across 8 independent craters, demonstrating reliable generalization to unseen energy conditions. These results demonstrate that incorporating physical priors into data-driven learning provides an effective pathway to overcoming accuracy limitations in modeling complex laser–matter interactions. This approach offers a reliable tool for quantitative prediction and parameter optimization in deep femtosecond laser processing of transparent materials and enabling highly controllable and reproducible micro- and nanofabrication for advanced photonic and three-dimensional optical applications. Full article

Background/Objectives: Temporal bone surgery in children is technically challenging due to their smaller anatomical structures, developmental differences, and the closer proximity of critical neurovascular structures. The limited availability of conventional training materials and pediatric cadaveric specimens has led to greater enthusiasm for simulation-based methods. The aim of this systematic review was to identify existing otologic simulation models and evaluate their anatomical accuracy, teaching effectiveness, and supporting evidence. Methods: In accordance with PRISMA guidelines, the PubMed, Embase, Scopus, and Cochrane Library databases were searched for studies reporting simulation tools for pediatric otologic surgery. Articles describing three-dimensional printed (3DP) models, virtual reality (VR) platforms, cadaver specimens, and animal models were included. Studies focusing on children and providing educational outcomes were selected. The extracted data were synthetized and analytically discussed. Results: Thirteen studies met the inclusion criteria: nine on 3DP models and four on VR environments. No research involving cadavers or animals was identified. 3DP models exhibited consistent anatomical accuracy and notable educational advantages. Five studies used surveys for their evaluations, and three relied on expert observer assessments. The studies including validation analyses showed a high correlation between printed models and computed tomography (CT) images. VR systems supported anatomical reconstruction and segmentation tasks, as well as guided simulation exercises. However, most of the research consisted of feasibility studies with limited participant groups. Conclusions: Simulation-based training with 3DP and VR models could be ethical and accurate methods for obtaining relevant skills in pediatric otologic surgery. The reviewed data suggest that these tools may be suitable as a first-line step within an integrated, multimodal training pathway prior to direct patient contact. Full article

Multi-line-scan camera systems provide high-frequency sampling and wide field-of-view coverage, making them valuable for three-dimensional measurement and dynamic reconstruction. However, their one-dimensional projection property introduces scale ambiguity and strong parameter coupling during calibration, which limits the consistency and stability of local optimization in multi-camera systems. To address this issue, this paper proposes a global calibration method based on physical constraints and hierarchical optimization. A unified imaging and motion model is constructed by incorporating physical scale constraints and structural priors, and geometric scale information is introduced into the joint optimization to reduce scale ambiguity and parameter coupling. Parameter normalization and staged optimization are further adopted to improve numerical stability for variables of different magnitudes and enable consistent estimation of multi-camera parameters within a unified framework. Simulation and experimental results show that the method achieves stable convergence under focal-length initialization perturbation, baseline deviation, and noise interference, with a three-dimensional reconstruction error below 0.67 mm and a convergence probability of at least 99.7%. These results indicate that the proposed method effectively reduces calibration uncertainty in multi-line-scan camera systems and supports high-precision online measurement and dynamic three-dimensional perception. Full article

Coastal reclaimed areas are characterized by complex strata and high groundwater levels, and pile foundations in such areas often suffer from insufficient uplift resistance. Compared with conventional cast-in-place piles, squeezed branch piles exhibit superior uplift performance; however, studies on squeezed branch piles in reclaimed areas remain limited. To investigate the uplift bearing performance of squeezed branch piles in the complex strata of coastal reclaimed areas, in situ full-scale uplift tests were conducted in the Shenzhen Binhai Avenue (Headquarters Base Section) traffic reconstruction project. Based on the actual physical and mechanical properties of the soil strata, a three-dimensional numerical model was established and validated against the load–displacement curves obtained from the in situ full-scale uplift tests. On this basis, the uplift bearing performance of squeezed branch piles, the differences in uplift bearing performance between branch and plate structures, and their applicable strata were analyzed. The plate structure and different branch configurations of squeezed branch piles exhibit distinct symmetric configuration characteristics, and these configuration differences influence the overall uplift bearing performance. The results show that the load–displacement curves of the uplift piles are generally smooth, without obvious abrupt rises or drops, exhibiting a gradual variation pattern, and the maximum pile-head displacements are all less than 100 mm. The mobilization of the bearing capacity of the branch and plate structures exhibits a distinct temporal and sequential pattern, with the plate structures at shallower embedment depths mobilized earlier than those at greater depths. Compared with conventional cast-in-place pile foundations, the presence of branches and plates endows squeezed branch piles with better elastic mechanical behavior and higher rebound ratios during unloading. Under identical stratum and loading conditions, the uplift bearing performance of the plate is 133% higher than that of the six-radial-branch configuration, while that of the six-radial-branch configuration is 34% higher than that of the four-radial-branch configuration. It is recommended to adopt the six-radial-branch configuration in clayey sandy gravel strata and the plate configuration in gravelly clayey soil and completely weathered coarse-grained granite strata, whereas neither branches nor plates are recommended in soil-like strongly weathered coarse-grained granite strata. Full article

Bone marrow(BM) is the primary site of hematopoiesis, supporting the self-renewal and differentiation of hematopoietic stem cells (HSCs). Its function depends on a highly complex microenvironment composed of stromal cells, vascular networks, extracellular matrix components, and dynamic biophysical signals. Traditional two-dimensional culture systems and animal models fail to adequately recapitulate the spatial architecture and dynamic regulatory processes of the human bone marrow niche, thereby limiting in-depth investigations into hematopoietic regulatory mechanisms, disease pathogenesis, and drug-induced bone marrow toxicity. In recent years, advances in microphysiological systems (MPS) have provided novel engineering approaches for the in vitro reconstruction of the bone marrow microenvironment. This review systematically summarizes current construction strategies for bone marrow MPS, including three-dimensional self-organized bone marrow organoids and microfluidic bone marrow-on-a-chip platforms. Particular attention is given to the roles of key cellular components, biomaterial scaffolds, vascularized architectures, and dynamic perfusion systems in biomimetic bone marrow engineering. In addition, we discuss strategies for constructing more complex models, such as vascular niches, vascularized bone tissue constructs, and bone metastasis models. Bone marrow MPS more faithfully recapitulate the hematopoietic microenvironment and provide a physiologically relevant in vitro platform for hematopoietic research, disease modeling, and drug evaluation, thereby supporting future advances in precision and regenerative medicine. Full article

Three-dimensional seed phenotyping requires imaging systems capable of achieving micron-level resolution across a centimeter-level field of view (FOV), a goal constrained by the resolution–FOV trade-off in conventional light field architectures. This paper presents a hardware–software co-optimized framework that integrates a reconfigurable optical system with computational imaging pipelines to address this limitation. At the hardware level, we develop a tunable-focus lens module that enables flexible adjustment of the effective focal length, combined with a custom-designed microlens array (MLA). A mathematical model is established to analyze the interdependencies among FOV, lateral resolution, depth of field (DOF), and system configuration, guiding the design of individual optical components. On the computational side, we propose a hybrid aberration correction strategy: first, a co-calibration of lens and MLA aberrations based on line-feature detection; second, a conditional generative adversarial network (cGAN) with attention-guided residual learning to enhance sub-aperture images, achieving a PSNR of 34.63 dB and an SSIM of 0.9570 on seed datasets. Experimentally, the system achieves a resolution of 6.2 lp/mm at MTF50 over a 2–3 cm FOV, representing a 307% improvement over the initial configuration (1.52 lp/mm). The reconstruction pipeline combines epipolar plane image (EPI) analysis with multi-view consistency constraints to generate dense 3D point clouds at a density of approximately 1.5 × 10⁴ points/cm² while preserving spectral and textural features. Validation on bitter melon and rice seeds demonstrates accurate 3D reconstruction and accurate extraction of morphological parameters across a large area. By integrating optical and computational design, this work establishes a reconfigurable imaging framework that overcomes the resolution–FOV limitations of conventional light field systems. The proposed architecture is also applicable to robotic vision and biomedical imaging. Full article

Wind turbine blades are subjected to complex environmental conditions during long-term operation, which may lead to structural degradation and performance loss. To ensure structural integrity, fatigue testing prior to deployment is essential. This paper proposes a vision-based method for measuring the full-cycle breathing deformation of wind turbine blades during fatigue testing. The method captures dynamic image sequences of the blade’s hotspot cross-section using industrial cameras and employs a feature-based template matching approach to reconstruct the three-dimensional coordinates of target points. Through coordinate transformation, the deformation trajectories are obtained, enabling quantitative analysis of the blade’s dynamic responses in both flapwise and edgewise directions. A dedicated hardware–software system was developed and validated through full-scale fatigue experiments. Quantitative comparison with strain gage measurements shows that the proposed method achieves mean absolute deviations of 0.84 mm and 0.93 mm in two independent experiments, respectively, with closely matched deformation trends under typical loading conditions. These results demonstrate that the proposed method can reliably capture the global deformation behavior of the blade with millimeter-level accuracy, while significantly reducing instrumentation complexity compared to conventional contact-based approaches. The proposed method provides an effective and practical solution for full-field dynamic deformation measurement in blade fatigue testing, offering strong potential for structural health monitoring and early damage detection in wind turbine systems. Full article

Accurate fruit localization and efficient harvesting are key challenges for agricultural robots, especially in dynamic orchard environments, where platform vibration, fruit occlusion, and computational resource limitations of embedded devices significantly impact system performance. To address these issues, this paper proposes a lightweight “fruit detection + harvesting” framework. First, by integrating MobileNetV4 and Triplet Attention mechanisms, an improved YOLOv8n network is designed, with the improved YOLOv8n Precision reaching 98.148% and FPS reaching 30 FPS on Jetson Nano, achieving a good balance between detection accuracy and computational efficiency suitable for edge deployment. Second, a strawberry three-dimensional coordinate reconstruction method based on weighted 3D centroid reconstruction is proposed, utilizing depth bias adjustment coefficients to improve spatial accuracy. Third, to address localization errors caused by vibration and platform motion, a dynamic compensation and temporal fusion strategy based on an Inertial Measurement Unit (IMU) is proposed. The rotation matrix estimated from IMU data is first used to correct camera pose variations. Then, an adaptive sliding window is employed to smooth the coordinate sequence. Finally, an Extended Kalman Filter (EKF) is applied to further refine the fused results by incorporating temporal dynamics, ensuring that the reconstructed three-dimensional coordinates in the robotic arm reference frame achieve higher stability and continuity. Experimental results in orchard scenarios show that compared with traditional methods, the system has higher localization accuracy, stronger robustness to dynamic disturbances, and higher harvesting efficiency. This work provides a practical and deployable solution for advancing intelligent fruit-harvesting robots. Full article

Background/Objectives: Transcatheter ablation assisted by three-dimensional (3D) electroanatomical mapping (EAM) is the elective treatment for atrioventricular nodal reentrant tachycardia (AVNRT) in children and adolescents. In this population of patients, the most frequently employed EAM strategies are the low-voltage bridge (LVB) strategy and sinus rhythm propagation mapping (SRPM). However, the exact pathophysiology and anatomy of the AVNRT reentrant circuits are still poorly understood. The aim of this study was to investigate the relationship between SRPM and LVB and to shed light on nodal physiology in children and adolescents affected by AVNRT. Methods: We retrospectively collected data on pediatric patients who underwent cryoablation for AVNRT assisted by high-density 3D EAM by using the LVB strategy; maps were reviewed by two independent electrophysiologists and the SRPM was described. SRPM was defined as typical when only one collision area was identified and atypical whenever either no or ≥ two collision areas were localized. Results: Twenty-eight consecutive patients (11.3 ± 3.3 years) were enrolled. All procedures were acutely successful. Overall, atypical SRPM was present in 10 patients (35.7%), and it did not correlate with the presence of multiple SPs or electrophysiological data. Moreover, we observed an imperfect concordance between SRPM and LVB (only in 10/18 patients). When SRPM and LVB were assessed in different locations, the LVB identified the effective cryoablation site in more cases than SRPM (4/8 vs. 1/8). Lastly, in cases of double collision, one collision area co-localized with the LVB and the effective cryoablation spot, whereas the other was located superiorly, closer to the His bundle. Conclusions: Atypical sinus rhythm propagation in the Koch’s triangle is a frequent finding in pediatric AVNRT patients. In this series, LVB showed closer concordance with the successful cryolesion site than retrospectively reconstructed SRPM. Full article

Background/Objective: Cardiac innervation plays a critical role in regulating myocardial function and enabling the heart to adapt to physiological and pathological conditions. Although the general features of sympathetic and parasympathetic innervation of the myocardium are well described, the spatial organisation of nerve fibres within the cardiac muscle remains incompletely characterised. This study aimed to develop and validate the SKUF (Slice–Keep–Unwrap–Fuse) protocol, a multimodal framework for mapping myocardial innervation through the integration of histological data and magnetic resonance imaging (MRI). Methods: The study was performed on the heart of a 7-year-old patient who died from rupture of a cerebral vascular malformation without evidence of cardiovascular disease. Prior to histological processing, post-mortem MRI was performed to provide a precise anatomical reference. The heart was sectioned into sequential transverse rings of 4 mm thickness, yielding 71 paraffin blocks. Histological sections (3 μm) were immunostained with antibodies against UCHL-1 to visualise nerve fibres and scanned using an Aperio AT2 system (20× magnification). Automated image analysis was conducted using the SVSSlide Processor module, which included tissue segmentation, colour-based nerve fibre detection, and sliding-window density mapping. Heatmaps were assembled into ring-based myocardial reconstructions and co-registered with MRI slices using combined rigid and deformable registration, followed by three-dimensional reconstruction of innervation patterns. Results: A higher density of nerve fibres was observed in the right ventricular myocardium compared with the left ventricle, whereas larger nerve trunks were identified in the epicardium of the left ventricle. Quantitative analysis revealed a pronounced longitudinal gradient of innervation, with minimal density in the apical region and progressive increases towards the mid-ventricular segments, where maximal density and spatial organisation of neural structures were observed. The atrioventricular groove exhibited the greatest heterogeneity of innervation due to the presence of large nerve trunks and ganglionated plexuses. Integration of histological maps with MRI enabled three-dimensional visualisation of spatial clusters of nerve fibres. Conclusions: The SKUF protocol provides a robust framework for integrating histological and MRI data to generate three-dimensional maps of myocardial innervation. This approach may facilitate the development of high-resolution anatomical atlases of cardiac innervation and support future studies of neurocardiac mechanisms of arrhythmogenesis and targeted neuromodulation. Full article

Surface defects in high-temperature continuous cast billets are critical factors affecting the quality of steel products. Owing to high-temperature radiation, heavy dust contamination, varying billet specifications, and background interference from oxide scales and water stains, existing online surface defect detection technologies for high-temperature continuous cast billets still suffer from limitations including high false-positive rates, inefficient identification of pseudo-defects, and the inability to simultaneously detect three-dimensional (3D) depth information alongside two-dimensional (2D) features. To solve these problems, this paper proposes a multi-dimensional online detection technology for surface defects in high-temperature continuous cast billets based on multi-information fusion. A four-channel multispectral image sensor and a corresponding three-light-source imaging system were developed. Furthermore, a defect sample augmentation method, a deep learning-based 2D recognition method, and a photometric stereo-based 3D reconstruction method were designed to mitigate problems of low detection accuracy and poor robustness caused by sample imbalance among different defect types. Finally, industrial applications were conducted on large-section continuous cast billets, beam blanks, and billets during the grinding process. According to the surface defect detection requirements of different continuous cast billets, multispectral multi-information fusion and traditional 2D defect imaging methods were adopted respectively. The results demonstrate high-precision online detection of surface defects in continuous cast billets, with favorable practical application effects. Full article

Amygdala dysfunction is implicated in stress-related affective disorders, and astrocytes are key regulators of amygdalar neuroplasticity. Here, we examined whether running exercise modulates astrocyte number, morphology, proliferation, and excitatory synaptic contacts in the basolateral amygdala (BLA) and central amygdala (CeA) in rats exposed to chronic unpredictable stress (CUS). Anhedonia-like behaviors were evaluated using the sucrose preference test, while anxiety-related behaviors were assessed using the elevated plus maze and open field tests. Unbiased stereological three-dimensional quantification was used to assess amygdalar volume and estimate astrocyte numbers in BLA and CeA, and immunofluorescence with morphological reconstruction was performed to quantify astrocytic complexity, proliferation, and astrocyte-associated PSD95⁺ puncta. Running exercise significantly increased sucrose preference in CUS rats, whereas elevated plus maze and open field measures were not significantly changed. CUS reduced astrocyte number and proliferation, and induced astrocytic morphological atrophy in both subregions. These alterations were reversed by running. Moreover, running increased the number of excitatory synapses contacted by astrocytes in the BLA and CeA of CUS rats. These findings suggest that running promotes astrocyte-mediated structural remodeling in amygdalar subregions, which may contribute to the regulation of anhedonia-like behavioral alterations associated with chronic stress. Full article