Search Results (705)

Sub-internal limiting membrane (sub-ILM) hemorrhage is a distinct preretinal bleeding entity in which blood accumulates between the ILM and the retinal nerve fiber layer (RNFL), forming a sharply confined compartment. The ILM’s low permeability and lack of immune cell access create a stagnant microenvironment in which erythrocyte lysis leads to the accumulation of hemoglobin, heme, and iron, promoting the generation of reactive oxygen species. This oxidative burden poses a direct risk to retinal ganglion cells and Müller cell endfeet. Spectral-domain optical coherence tomography (SD-OCT) enables precise identification of sub-ILM blood through its characteristic dome-shaped elevation and hyperreflective contents, distinguishing it from subhyaloid and vitreous hemorrhage. Management options include observation, neodymium-doped yttrium–aluminum–garnet (Nd: YAG) laser membranotomy, pneumatic displacement, and pars plana vitrectomy (PPV). While small, extrafoveal hemorrhages may resolve spontaneously, prolonged blood entrapment is associated with increased retinal toxicity, tractional changes, and proliferative vitreoretinopathy (PVR). Early intervention generally results in faster clearance and improved visual outcomes, particularly for dense or foveal bleeding. Major gaps remain regarding cellular stress responses, biomarkers that predict irreversible damage, and the optimal timing of intervention. Standardized imaging criteria and evidence-based management algorithms are needed to guide individualized treatment. Full article

A waterspout was sighted in the offshore waters of Hong Kong in mid-October 2025, the second-latest occurrence of this weather phenomenon in a single year since 1959. Due to the close proximity of the phenomenon to Lamma Island in Hong Kong, detailed sighting information and photographs of the waterspout are available for analysis. This paper investigates the meteorological background of the event, the stability of the atmosphere, and weather radar images from two dual-polarization weather radar stations within the territory to determine the type and intensity of the observed waterspout and its formation mechanism. At that time, the atmosphere was rather unstable, with high values for CAPE and bulk Richardson number, along with an upper-level divergence area that provided updraft momentum for convective development. Detailed observations from these weather radar images showed that the waterspout was a rather weak system with relatively low radar reflectivity and generally weak Doppler velocities, although the velocity signatures, such as Doppler velocity couplets, and azimuthal shear were quite clear. The potential for an operational 2-kilometer ensemble prediction system (EPS) from the Hong Kong Observatory to indicate a favorable environment for waterspout development was also investigated. While the EPS cannot be expected to resolve the waterspout problem or reproduce its exact location and timing, it can capture weak low-level cyclonic anomalies and convergences near Lamma Island that would provide favorable conditions for the formation of waterspouts and are broadly consistent with the observed mesoscale environment. Full article

Background: Achieving adequate margins in pelvic bone tumor resection remains difficult, as conventional navigation provides no direct three-dimensional margin feedback. We proposed an innovative dangerous region generation method based on 3D image resampling and anisotropic distance transform, integrated with computer-assisted navigation, to enhance surgical margin accuracy. This study aimed to evaluate its oncological safety, functional outcomes, and perioperative efficacy in pelvic tumor surgery. Methods: The study was conducted on 19 patients (8 males, 11 females) with primary pelvic bone tumors between May 2018 and June 2024. The age range was 19 to 66 years (mean age: 62.67 years). Histological diagnoses included chondrosarcoma (n = 6), giant cell tumor (n = 4), osteosarcoma (n = 1), chordoma (n = 2), Ewing sarcoma (n = 3), spindle cell sarcoma (n = 1), chondromyxoid fibroma (n = 1), and peripheral nerve sheath tumor (n = 1). The feasibility of the dangerous region generation method for computer-assisted pelvic tumor resection surgery was assessed by general results, oncological and functional results. Results: All patients successfully underwent surgery with a mean operative time of 252 min and average intraoperative blood loss of 1358 mL. The mean hospital stay was 22 days, and all patients completed follow-up (mean, 37 months). Two patients developed postoperative wound complications, which resolved after debridement. Adequate surgical margins were achieved in all cases. The 5-year overall survival rate was 75.6%, increasing to 80.0% among patients with wide-margin resections. At the final follow-up, the mean MSTS score among 16 limb-salvage patients was 26.6, corresponding to an average functional recovery of 88.5%. Most patients exhibited a normal gait and were able to ambulate without assistive devices. Conclusions: This dangerous region generation method, when combined with computer-assisted techniques for pelvic bone tumor resection, is feasible and can achieve favorable clinical outcomes. Full article

Neuromuscular diseases are biologically diverse, clinically heterogeneous, and often difficult to diagnose and treat, highlighting the need for computational tools that can help resolve overlapping phenotypes and support timely, mechanism-informed interventions. This narrative review synthesizes recent advances in artificial intelligence (AI) and machine learning applied to neuromuscular diseases across diagnosis, outcome modeling, biomarker development, and therapeutics. AI-based approaches may assist clinical and genetic diagnosis from phenotypic data; however, early phenotype-driven tools have seen limited clinician adoption due to modest accuracy, usability challenges, and poor workflow integration. Electrophysiological studies remain central to diagnosing neuromuscular diseases, and AI shows promise for accurate classification of electrophysiological signals. Predictive models for disease outcome and progression—particularly in amyotrophic lateral sclerosis—are under active investigation, but most remain at an early stage of development and are not yet ready for routine clinical use. Digital biomarkers derived from imaging, gait, voice, and wearable sensors are emerging, with MRI-based quantification of muscle fat replacement representing the most mature and widely accepted application to date. Efforts to apply AI to therapeutic discovery, including drug repurposing and optimization of gene-based therapies, are ongoing but have thus far yielded limited clinical translation. Persistent barriers to broader adoption include disease rarity, data scarcity, heterogeneous acquisition protocols, inconsistent terminology, limited external validation, insufficient model explainability, and lack of seamless integration into clinical workflows. Addressing these challenges is essential to moving AI tools from the laboratory into clinical practice. We conclude with a practical checklist of considerations intended to guide the development and adoption of AI tools in neuromuscular disease care. Full article

This study investigates the vegetation dynamics and phenotypic differentiation of five triticale (×Triticosecale Wittm.) varieties under the region-specific agroecological conditions of Southern Dobruja, Bulgaria, across two growing seasons (2024–2025), with the aim of evaluating how local climatic variability shapes vegetation index patterns. UAV-based multispectral imaging was employed throughout key phenological stages to obtain reflectance indices, including NDVI, SAVI, EVI2, and NIRI, which served as indicators of canopy development and physiological status. NDVI was used as the primary reference index, and a baseline value (NDVIbase), defined as the mean NDVI across all varieties on a given date, was applied to evaluate relative varietal deviations over time. Multiple linear regression analyses were performed to assess the relationship between NDVI and baseline biometric parameters for each variety, revealing that varieties 22/78 and 20/52 exhibited reflectance dynamics most closely aligned with expected developmental trends in 2025. In addition, the relationship between NDVI and meteorological variables was examined for the variety Kolorit, demonstrating that relative humidity exerted a pronounced influence on index variability. The findings highlight the sensitivity of triticale vegetation indices to both varietal characteristics and short-term climatic fluctuations. Overall, the study provides a methodological framework for integrating UAV-based multispectral data with meteorological information, emphasizing the importance of region-specific, time-resolved monitoring for improving precision agriculture practices, optimizing crop management, and supporting informed variety selection. Full article

Classical beamforming (CBF) beamforming constrains the accuracy and quality of underwater acoustic imaging by producing wide main-lobes that reduce resolution, high sidelobes that cause leakage, and point-spread functions that blur targets. Existing approaches typically address only one of these issues at a time, limiting their ability to resolve multiple, interrelated problems simultaneously. In this study, we introduce a double-compression deconvolution high-resolution beamforming method designed to enhance multi-beam sonar imaging using an underwater uniform linear array. The proposed approach formulates imaging as a sparse deconvolution problem and suppresses off-target interference through two sparse constraints, thereby improving the sonar’s resolving capability. During sparse reconstruction, an auxiliary-parameter iterative shrinkage-threshold algorithm is employed to recover azimuthal sparse signals with higher accuracy. Simulations and controlled pool experiments demonstrate that, relative to classical beamforming, the proposed method significantly improves resolution, suppresses off-target interference, expands the imaging intensity dynamic range, and yields clearer target representations. This study provides an effective strategy to mitigate intrinsic limitations in high-resolution underwater sonar imaging. Full article

The three-dimensional borehole-to-surface transient electromagnetic (BSTEM) method plays a critical role in resolving subsurface conductivity structures under complex geological conditions. However, its application is often constrained by the high computational costs associated with large-scale simulations and fine temporal resolution. In this study, a time-parallel forward modeling strategy is employed by integrating the finite volume method (FVM) with the Multigrid Reduction-in-Time (MGRIT) algorithm. Maxwell’s equations are discretized in space using unstructured octree meshes, while the MGRIT algorithm enables parallelism along the time axis through coarse–fine temporal grid hierarchy and multilevel iterative correction. Numerical experiments on synthetic and field-scale models demonstrate that the MGRIT-based solver significantly reduces computational time compared to conventional direct solvers, particularly when a large number of processors are utilized. In a field-scale hematite mine model, the MGRIT-based solver reduces the total runtime by more than 40% while maintaining numerical accuracy. The method exhibits parallel scalability and is especially advantageous in problems involving a large number of time channels, where simultaneous time-step updates offer substantial performance gains. These results confirm the effectiveness and robustness of the proposed approach for large-scale 3D TEM simulations under complex conditions and provide a practical foundation for future applications in high-resolution electromagnetic modeling and imaging. Full article

The 3D reconstruction of vessel hulls is crucial for enhancing safety, efficiency, and knowledge in the maritime industry. Neural Radiance Fields (NeRFs) are an alternative to 3D reconstruction and rendering from multi-view images; particularly, tensor-based methods have proven effective in improving efficiency. However, existing tensor-based methods typically suffer from a lack of spatial coherence, resulting in gaps in the reconstruction of fine-grained geometric structures. This paper proposes a spatial multi-scale weighted NeRF (MDW-NeRF) for accurate and efficient surface reconstruction of vessel hulls. The proposed method develops a novel multi-scale feature decomposition mechanism that models 3D space by leveraging multi-resolution features, facilitating the integration of high-resolution details with low-resolution regional information. We designed separate color and density weighting, using a coarse-to-fine strategy, for density and a weighted matrix for color to decouple feature vectors from appearance attributes. To boost the efficiency of 3D reconstruction and rendering, we implement a hybrid sampling point strategy for volume rendering, selecting sample points based on volumetric density. Extensive experiments on the SVH dataset confirm MDW-NeRF’s superiority: quantitatively, it outperforms TensoRF by 1.5 dB in PSNR and 6.1% in CD, and shrinks the model size by 9%, with comparable training times; qualitatively, it resolves tensor-based methods’ inherent spatial incoherence and fine-grained gaps, enabling accurate restoration of hull cavities and realistic surface texture rendering. These results validate our method’s effectiveness in achieving excellent rendering quality, high reconstruction accuracy, and timeliness. Full article

This article presents a systematic review on methods for quantifying three-dimensional, time-resolved (3D+t) deformation and motion of human arteries from Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched Scopus, Web of Science, IEEE Xplore, Google Scholar, and PubMed on 19 December 2025 for in vivo, patient-specific CT or MRI studies reporting motion or deformation of large human arteries. We included studies that quantified arterial deformation or motion tracking and excluded non-vascular tissues, in vitro or purely computational work. Thirty-five studies were included in the qualitative synthesis; most were small, single-centre observational cohorts. Articles were analysed qualitatively, and results were synthesised narratively. Across the 35 studies, the most common segmentation approaches are active contours and threshold, while temporal motion is tracked using either voxel registration or surface methods. These kinematic data are used to compute metrics such as circumferential and longitudinal strain, distensibility, and curvature. Several studies also employ inverse methods to estimate wall stiffness. The findings consistently show that arterial strain decreases with age (on the order of 20% per decade in some cases) and in the presence of disease, that stiffness correlates with geometric remodelling, and that deformation is spatially heterogeneous. However, insufficient data prevents meaningful comparison across methods. Full article

Adhesive fracture in layered structures is governed by subsurface crack evolution that cannot be accessed using surface-based diagnostics. Methods such as digital image correlation and optical spectroscopy measure surface deformation but implicitly assume a straight and uniform crack front, an assumption that becomes invalid for interfacial fracture with wide crack openings and asymmetric propagation. In this work, terahertz time-domain spectroscopy (THz-TDS) is combined with double-cantilever beam testing to directly map subsurface crack-front geometry in opaque adhesive joints. A strontium titanate-doped epoxy is used to enhance dielectric contrast. Multilayer refractive index extraction, pulse deconvolution, and diffusion-based image enhancement are employed to separate overlapping terahertz echoes and reconstruct two-dimensional delay maps of interfacial separation. The measured crack geometry is coupled with load–displacement data and augmented beam theory to compute spatially averaged stresses and energy release rates. The measurements resolve crack openings down to approximately 100 μm and reveal pronounced width-wise non-uniform crack advance and crack-front curvature during stable growth. These observations demonstrate that surface-based crack-length measurements can either underpredict or overpredict fracture toughness depending on the measurement location. Fracture toughness values derived from width-averaged subsurface crack fronts agree with J-integral estimates obtained from surface digital image correlation. Signal-to-noise limitations near the crack tip define the primary resolution limit. The results establish THz-TDS as a quantitative tool for subsurface fracture mechanics and provide a framework for physically representative toughness measurements in layered and bonded structures. Full article

Metabolic dysfunction-associated steatotic liver disease (MASLD) is strongly linked to systemic metabolic disturbances and features a lipid-driven cascade that promotes hepatic inflammation and fibrosis. Choline insufficiency contributes to disease advancement by altering phospholipid turnover and redox homeostasis; however, its spatial and temporal regulatory roles throughout MASLD progression remain insufficiently defined. A 10-week high-fat, choline-deficient (HFCD) mouse model was established, and liver pathology was evaluated at weeks 6, 8, and 10. Time-resolved assessments combined untargeted metabolomics, magnetic resonance imaging–proton density fat fraction (MRI-PDFF), serum biochemistry, histological staining, immunofluorescence, and transmission electron microscopy to characterize dynamic alterations in lipid metabolism, redox status, inflammation, and fibrogenesis. The HFCD diet produced a clear temporal sequence of liver injury. Steatosis, phosphatidylcholine depletion, and early antioxidant loss appeared by week 6. By week 8, mitochondrial structural damage and pronounced cytokine elevation were evident. At week 10, collagen deposition and α-SMA activation signaled fibrotic progression. Metabolomics indicated significant disruptions in pathways related to ATP-binding cassette (ABC) transporters, one-carbon metabolism, and the tricarboxylic acid (TCA) cycle. Using integrated analytical strategies, this study suggests that choline deficiency may be associated with a time-dependent pathological cascade in MASLD, beginning with phospholipid destabilization and extending to altered mitochondria–endoplasmic reticulum crosstalk at mitochondria-associated membranes, alongside amplified oxidative–inflammatory responses, which collectively may contribute to progressive fibrogenesis as the disease advances. Full article

Automated livestock monitoring in wide-area grasslands is a critical component of smart agriculture development. Devices such as Unmanned Aerial Vehicles (UAVs), remote sensing, and high-mounted cameras provide unique monitoring perspectives for this purpose. The high-resolution images they capture cover vast grassland backgrounds, where targets often appear as small, distant objects and are extremely unevenly distributed. Applying standard detectors directly to such images yields poor results and extremely high miss rates. To improve the detection accuracy of small targets in high-resolution images, methods represented by Slicing Aided Hyper Inference (SAHI) have been widely adopted. However, in specific scenarios, SAHI’s drawbacks are dramatically amplified. Its strategy of uniform global slicing divides each original image into a fixed number of sub-images, many of which may be pure background (negative samples) containing no targets. This results in a significant waste of computational resources and a precipitous drop in inference speed, falling far short of practical application requirements. To resolve this conflict between accuracy and efficiency, this paper proposes an efficient detection framework named CAMS-AI (Clustering and Adaptive Multi-level Slicing for Aided Inference). CAMS-AI adopts a “coarse-to-fine” intelligent focusing strategy: First, a Region Proposal Network (RPN) is used to rapidly locate all potential target areas. Next, a clustering algorithm is employed to generate precise Regions of Interest (ROIs), effectively focusing computational resources on target-dense areas. Finally, an innovative multi-level slicing strategy and a high-precision model are applied only to these high-quality ROIs for fine-grained detection. Experimental results demonstrate that the CAMS-AI framework achieves a mean Average Precision (mAP) comparable to SAHI while significantly increasing inference speed. Taking the RT-DETR detector as an example, while achieving 96% of the mAP_50–95 accuracy level of the SAHI method, CAMS-AI’s end-to-end frames per second (FPS) is 10.3 times that of SAHI, showcasing its immense application potential in real-world, high-resolution monitoring scenarios. Full article

To address the problems of weak geometric features, low signal response amplitude, and insufficient spatial resolvability of near-surface defects in metal substrates, a high-resolution spatiotemporal-coded eddy-current array probe is proposed. The probe adopts an array topology with time-multiplexed excitation and adjacent differential reception, achieving a balance between high common-mode rejection ratio and high-density spatial sampling. First, a theoretical electromagnetic coupling model between the probe and the metal substrate is established, and finite-element simulations are conducted to investigate the evolution of the skin effect, eddy-current density distribution, and differential impedance response over an excitation frequency range of 1–10 MHz. Subsequently, a 64-channel M-DECA probe and an experimental testing platform are developed, and frequency-sweeping experiments are carried out under different excitation conditions. Experimental results indicate that, under a 50 kHz excitation frequency, the array eddy-current response achieves an optimal trade-off between signal amplitude and spatial geometric consistency. Furthermore, based on the pixel-to-physical coordinate mapping relationship, the lateral equivalent diameters of near-surface defects with different characteristic scales are quantitatively characterized, with relative errors of 6.35%, 4.29%, 3.98%, 3.50%, and 5.80%, respectively. Regression-based quantitative analysis reveals a power-law relationship between defect area and the amplitude of the differential eddy-current array response, with a coefficient of determination ${\mathrm{R}}^2=0.9034$ for the bipolar peak-to-peak feature. The proposed M-DECA probe enables high-resolution imaging and quantitative characterization of near-surface defects in metal substrates, providing an effective solution for electromagnetic detection of near-surface, low-contrast defects. Full article

Background/Objectives: Magnetic resonance imaging (MRI) can be used to assess muscle function while performing a motion task within the scanner. Quantitative measures such as contraction velocity and strain can be derived from the images. Cine phase contrast (PC) MRI for time-resolved imaging of muscle function relies on the consistently repeated execution of the motion task for several minutes until data acquisition is complete. This may be difficult for patients with neuromuscular dysfunctions. To date, this approach has been applied only in adults, but not pediatric populations. The aim of this pilot study was to investigate the feasibility of PC MRI for assessing calf muscle function during electrically evoked and voluntary motion in children with cerebral palsy (CP) using open-source hardware and software. Methods: Cine PC MRI was performed at 3T in ambulatory pediatric patients with CP and typically developing children under electrical muscle stimulation (EMS) (n = 14/13) and during voluntary plantarflexion (n = 4/4) using a home-built pedal with a force sensor. A visual feedback software was developed to enable synchronized imaging of voluntary muscle contractions. Muscle contraction velocity and strain were calculated from the MRI data. Data quality was rated by two readers. Results: During EMS, the velocity data quality was rated as sufficient in 21% of scans in patients compared with 82% of scans in controls. During the voluntary task, all patients demonstrated increased compliance and greater generated force output than during EMS. Voluntary motion imaging was successful in all controls but none of the patients, as motion periodicity in patients was worse during voluntary than during stimulated contraction. Conclusions: Cine phase-contrast MRI combined with EMS or voluntary motion proved challenging in pediatric patients with CP, particularly in those with more severe baseline muscle dysfunction or reduced tolerance to stimulation. In contrast, the approach was successfully implemented in typically developing children. Although the scope of the patient-based findings is limited by data heterogeneity, the method demonstrates considerable potential as a tool for monitoring treatment-related changes in muscle function, particularly in less severely affected patients. Further refinement of the EMS and voluntary motion protocols, together with a reduction in MRI acquisition time, is required to improve motion periodicity, tolerability, and consequently the overall success rate in the intended pediatric patient cohort. Full article

To obtain radar images of a group of small space objects or to resolve individual elements of complex space objects in near-Earth orbit, a radar system must have high spatial resolution. High range resolution is achieved by using complex probing signals with a wide spectrum bandwidth. Achieving high angular resolution for small or complex space objects is based on the inverse synthetic aperture antenna effect. Among the various classes of complex signals, only two have found practical application in Inverse Synthetic Aperture Radar (ISAR) systems so far: the Linear Frequency-Modulated signal (chirp) and the Stepped-Frequency signal. Over the coherent integration interval of the echo signals, which corresponds to the ISAR aperture synthesis time, the combined correlation characteristics of the signal ensemble are analyzed. A high level of integral correlation noise in the ensemble of probing signals degrades the quality of the radar image. Therefore, a probing signal with a Zero Autocorrelation Zone (ZACZ) is highly relevant for ISAR applications. In this work, through simulation, radar images of a complex space object were obtained using both chirp and ZACZ probing signals. A comparative analysis of the correlation characteristics of the echo signals and the resulting radar images of the complex space object was performed. Full article