Search Results (8,104)

Background: Age-related macular degeneration is a major cause of vision loss, and improved visualization of macular neovascularization (MNV) on OCT angiography (OCTA) could enhance clinical assessment. This study aimed to establish a simple and accessible image enhancement method. Methods: We retrospectively analyzed 24 eyes from 22 patients with MNV at the Doheny UCLA Eye Centers. Grayscale-inverted OCTA images were generated using the basic “Invert” function in ImageJ 1.51 23. Each original and inverted image pair was assessed for seven MNV-related features: structure and area within 3 × 3 mm, 6 × 6 mm and 12 × 12 mm scans, and presence of polypoidal lesions. Twenty-one ophthalmologists graded visibility using a standardized five-point scale. Paired comparisons were performed using the Wilcoxon signed-rank test. Results: Grayscale inversion significantly improved the visualization of MNV structure in 6 × 6 mm scans (mean difference: +0.67 ± 1.02; p = 0.008), 12 × 12 mm scans (+0.62 ± 1.07; p = 0.013), and detection of polypoidal lesions (+0.43 ± 0.98; p = 0.030). No significant differences were found for 3 × 3 mm structure (p = 0.793) or area-related features (all p > 0.3). Conclusions: Grayscale inversion may enhance MNV visibility and polypoidal lesion detection on OCTA. As this study relied solely on subjective assessments, future work should incorporate quantitative image analysis. Full article

Mechanical exfoliation remains the most common method for producing high-quality two-dimensional (2D) materials, but its inherently low yield requires screening large numbers of samples to identify usable flakes. Efficient optimization of the exfoliation process demands scalable methods to analyze deposited material across extensive datasets. While machine learning clustering techniques have demonstrated ~95% accuracy in classifying 2D material thicknesses from optical microscopy images, current tools are limited by slow processing speeds and heavy reliance on manual user input. This work presents an open-source, GPU-accelerated software platform that builds upon existing classification methods to enable high-throughput analysis of 2D material samples. By leveraging parallel computation, optimizing core algorithms, and automating preprocessing steps, the software can quantify flake coverage and thickness across uncompressed optical images at scale. Benchmark comparisons show that this implementation processes over 200× more pixel data with a 60× reduction in processing time relative to the original software. Specifically, a full dataset of2916 uncompressed images can be classified in 35 min, compared to an estimated 32 h required by the baseline method using compressed images. This platform enables rapid evaluation of exfoliation results across multiple trials, providing a practical tool for optimizing deposition techniques and improving the yield of high-quality 2D materials. Full article

Background/Objectives: Scapholunate ligament injuries represent one of the most challenging diagnostic problems in wrist surgery, with conventional radiographs often appearing normal despite significant ligamentous disruption. The optimal stress radiographic views for detecting these injuries remain incompletely defined. To systematically evaluate and compare the diagnostic utility of eight different stress radiographic views in detecting isolated scapholunate ligament disruption using a cadaveric model. Methods: Nine fresh-frozen cadaveric wrists underwent complete scapholunate ligament transection while preserving secondary stabilizers. Eight radiographic positions were evaluated: posteroanterior (PA) neutral, PA wrist extension, PA wrist flexion, PA radial deviation, PA ulnar deviation, anteroposterior (AP) clenched fist, AP neutral, and lateral neutral. Scapholunate gap measurements were obtained using calibrated digital software with 20 mm reference markers. Statistical analysis employed repeated-measures ANOVA with post hoc comparisons. Results: PA wrist extension demonstrated the greatest scapholunate gap widening (2.68 ± 0.84 mm, p = 0.006), followed by AP clenched fist views (2.32 ± 1.07 mm, p = 0.036). PA wrist flexion showed significant gap reduction (0.47 ± 0.44 mm, p < 0.001). Twenty-two percent of specimens demonstrated scapholunate angles exceeding 70° on lateral radiographs. Inter-specimen variability was observed, with gap measurements ranging from 1.2 to 4.8 mm across different positions. Conclusions: PA wrist extension and AP clenched fist views demonstrate superior diagnostic utility for detecting scapholunate ligament injuries compared to neutral radiographs. These stress radiographic techniques offer accessible, cost-effective alternatives to advanced imaging modalities for early detection of scapholunate ligament pathology in clinical practice. Full article

Line feature matching is a fundamental and extensively studied subject in the fields of photogrammetry and computer vision. Traditional methods, which rely on handcrafted descriptors and distance-based filtering outliers, frequently encounter challenges related to robustness and a high incidence of outliers. While some approaches leverage point features to assist line feature matching by establishing the invariant geometric constraints between points and lines, this typically results in a considerable computational load. In order to overcome these limitations, we introduce a novel Bayesian posterior probability framework for line matching that incorporates three geometric constraints: the distance between line feature endpoints, midpoint distance, and angular consistency. Our approach initially characterizes inter-image geometric relationships using Fourier representation. Subsequently, we formulate the posterior probability distributions for the distance constraint and the uniform distribution based on the constraint of angular consistency. By calculating the joint probability distribution under three geometric constraints, robust line feature matches are iteratively optimized through the Expectation–Maximization (EM) algorithm. Comprehensive experiments confirm the effectiveness of our approach: (i) it outperforms state-of-the-art (including deep learning-based) algorithms in match count and accuracy across common scenarios; (ii) it exhibits superior robustness to rotation, illumination variation, and motion blur compared to descriptor-based methods; and (iii) it notably reduces computational overhead in comparison to algorithms that involve point-assisted line matching. Full article

Introduction: Bayesian penalized likelihood (BPL) reconstruction algorithms, commercially implemented as Q.Clear (GE Healthcare), enhance image quality but may alter quantitative metrics. The impact of BPL on dopamine transporter (DAT) PET quantification, including ratios, remains unclear. This study investigates whether Q.Clear processing alters key metrics such as specific binding ratios (SBRs) and interregional ratios. Methods: We retrospectively analyzed 170 paired F-18 FP-CIT PET datasets reconstructed with conventional 3D-OSEM (baseline-DICOM) and Q.Clear (Q.Clear-DICOM). Quantification was performed using BTXBrain-DAT (Brightonix Imaging), yielding 57 specific binding ratios (SBRs), three asymmetry indices, and nine interregional ratios. Paired statistical tests, Bland–Altman plots, and reproducibility checks were conducted. Visual reads by two nuclear medicine physicians were also compared between datasets. Results: Q.Clear processing significantly altered all quantitative metrics (p < 0.001). SBR values changed in all 57 regions, with most high-uptake regions showing an increase and low-uptake regions showing a decrease. Striatal and caudate asymmetry indices showed significant differences (p < 0.0001), whereas the putamen index remained stable. All interregional ratios differed significantly, although Bland–Altman analysis indicated relative stability for ratios compared with asymmetric indices. BTXBrain-DAT showed perfect reproducibility on repeat analysis, and visual interpretation was unaffected by reconstruction method. Conclusions: Q.Clear (BPL) reconstruction substantially influences F-18 FP-CIT PET quantification, including ratios and asymmetry indices, while leaving visual interpretation unchanged. These findings highlight the need for caution when using image enhancement functions for quantitative analysis, particularly in clinical studies involving low-uptake regions or multicenter data comparisons. Full article

Background: First rib stress fractures (FRSFs) are exceptionally rare in skeletally immature athletes and are frequently overlooked because their symptoms mimic more common scapular conditions such as scapular dyskinesis or thoracic outlet syndrome. Early and accurate identification is critical to avoid delayed union, prolonged disability, and misdirected management. Case Presentation: We report a 12-year-old elite baseball pitcher with progressive scapular winging and audible snapping during pitching. Unlike typical posterior-type fractures near the costotransverse joint, imaging revealed a cortical discontinuity precisely at the serratus anterior enthesis, consistent with repetitive traction enthesopathy. High-resolution musculoskeletal ultrasound (MSK-US) identified cortical disruption with periosteal edema, and dynamic ultrasound reproduced the patient’s snapping and pain in real time, establishing a direct clinical–imaging correlation. Conservative three-phase rehabilitation (scapular stabilization, serratus anterior activation, and structured return-to-throwing) led to complete union and pain-free return to sport within 12 weeks. Discussion: This case highlights the superior diagnostic efficacy of MSK-US for FRSFs in adolescents. The posterior scanning approach facilitated bilateral comparison and growth plate assessment. Dynamic examination provided a functional correlation beyond static imaging, identifying a novel snapping mechanism. This underscores the value of MSK-US in visualizing not just anatomy but also pathophysiology. Conclusions: This is among the youngest documented cases of first rib stress fracture diagnosed with dynamic ultrasound. Its novelty lies in the following: (1) occurrence at the serratus anterior enthesis, (2) reproduction of snapping during provocative maneuvers, and (3) expansion of the etiological spectrum of scapular dyskinesis to include rib pathology. Dynamic ultrasound should be considered a frontline modality for adolescent throwers with unexplained periscapular pain. Full article

Background: Chronic and acute wounds are often colonized by polymicrobial biofilms, delaying healing and complicating treatment. Rapid, non-invasive detection of pathogenic bacteria is therefore crucial for timely and targeted therapy. This study investigated porphyrin-producing bacterial species using the handheld cureVision imaging system. Methods: In this study, 20 clinically relevant, porphyrin-producing bacterial species were cultured on δ-aminolevulinic acid (ALA)-supplemented agar and analyzed using the handheld cureVision imaging system under 405 nm excitation. Both Red-Green-Blue (RGB) and fluorescence images were acquired under ambient daylight conditions, and fluorescence signals were quantified by grayscale intensity analysis. Results: All tested species exhibited measurable red porphyrin-associated fluorescence, with the highest intensities observed in Klebsiella pneumoniae, Klebsiella oxytoca, Veillonella parvula, and Alcaligenes faecalis. A standardized detectability threshold of 0.25, derived from negative controls, enabled semi-quantitative comparison across species. Statistical analysis confirmed that the fluorescence intensities of all bacterial samples were significantly elevated compared to the control (Wilcoxon signed-rank test and sign test, both p < 0.001; median intensity = 0.835, IQR: 0.63–0.975). Conclusions: These results demonstrate that the cureVision system enables robust and reliable detection of porphyrin-producing wound bacteria, supporting its potential as a rapid, non-invasive diagnostic method for assessing wound colonization and guiding targeted clinical interventions. Full article

The successful launch of Korea Multipurpose Satellite-3/Advanced Earth Imaging Sensor System (KOMPSAT-3/AEISS) on 18 May 2012 allowed the Republic of Korea to meet the growing demand for high-resolution satellite imagery. However, like all satellite sensors, KOMPSAT-3/AEISS experienced temporal changes post-launch and thus requires ongoing evaluation and calibration. Although more than a decade has passed since launch, the KOMPSAT-3/AEISS mission and its multi-year data archive remain widely used. This study focused on the cross-calibration of KOMPSAT-3/AEISS with Sentinel-2A/Multispectral Instrument (MSI) by comparing the radiometric responses of the two satellite sensors under similar observation conditions, leveraging the linear relationship between Digital Numbers (DN) and top-of-atmosphere (TOA) radiance. Cross-calibration was performed using near-simultaneous satellite images of the same region, and the Spectral Band Adjustment Factor (SBAF) was calculated and applied to account for differences in spectral response functions (SRF). Additionally, Bidirectional Reflectance Distribution Function (BRDF) correction was applied using MODIS-based kernel models to minimize angular reflectance effects caused by differences in viewing and illumination geometry. This study aims to evaluate the radiometric consistency of KOMPSAT-3/AEISS relative to Sentinel-2A/MSI over Baotou scenes acquired in 2022–2023, derive band-specific calibration coefficients and compare them with prior results, and conduct a side-by-side comparison of cross-calibration and vicarious calibration. Furthermore, the cross-calibration yielded band-specific gains of 0.0196 (Blue), 0.0237 (Green), 0.0214 (Red), and 0.0136 (NIR). These findings offer valuable implications for Earth observation, environmental monitoring, and the planning and execution of future satellite missions. Full article

A 9.4T brain MRI is the highest resolution MRI scanner in the public market. It offers submillimeter brain imaging with exceptional anatomical detail, making it one of the most powerful tools for detecting subtle structural changes associated with neurological conditions. Current segmentation models are optimized for lower-field MRI (1.5T–3T), and they struggle to perform well on 9.4T data. In this study, we present the GA-MS-UNet++, the world’s first deep learning-based model specifically designed for 9.4T brain MRI segmentation. Our model integrates multi-scale residual blocks, gated skip connections, and spatial channel attention mechanisms to improve both local and global feature extraction. The model was trained and evaluated on 12 patients in the UltraCortex 9.4T dataset and benchmarked against four leading segmentation models (Attention U-Net, Nested U-Net, VDSR, and R2UNet). The GA-MS-UNet++ achieved a state-of-the-art performance across both evaluation sets. When tested against manual, radiologist-reviewed ground truth masks, the model achieved a Dice score of 0.93. On a separate test set using SynthSeg-generated masks as the ground truth, the Dice score was 0.89. Across both evaluations, the model achieved an overall accuracy of 97.29%, precision of 90.02%, and recall of 94.00%. Statistical validation using the Wilcoxon signed-rank test (p < 1 × 10⁻⁵) and Kruskal–Wallis test (H = 26,281.98, p < 1 × 10⁻⁵) confirmed the significance of these results. Qualitative comparisons also showed a near-exact alignment with ground truth masks, particularly in areas such as the ventricles and gray–white matter interfaces. Volumetric validation further demonstrated a high correlation (R² = 0.90) between the predicted and ground truth brain volumes. Despite the limited annotated data, the GA-MS-UNet++ maintained a strong performance and has the potential for clinical use. This algorithm represents the first publicly available segmentation model for 9.4T imaging, providing a powerful tool for high-resolution brain segmentation and driving progress in automated neuroimaging analysis. Full article

The area encompassing the Campi Flegrei and Vesuvio volcanoes, situated approximately 25 km apart and bisected by the city of Naples, Italy, is recognised as one of the most hazardous regions globally. In recent decades, the Campi Flegrei caldera has undergone significant changes in its monitored geophysical, geochemical and geodetical signals. The most recent, ongoing unrest began in 2005, resulting in an uplift of over 150 centimetres in the area of maximum uplift. Previous analyses of deformation data from ERS/ENVISAT (available up to 2010) and Sentinel-1 (available since 2015) Synthetic Aperture Radar (SAR) imagery, as well as global navigation satellite system data, have suggested that the shape of the deformation field at Campi Flegrei has remained constant and that the area around Vesuvio experienced a slight subsidence in the early 2000s, concurrently with a change in the sign of the ground deformation (from subsidence to uplift) at Campi Flegrei. This study presents and provides the ground displacement time series obtained from RADARSAT-2 images of the entire volcanic area from 2010 to 2015, thus filling the temporal gap between the ERS/ENVISAT and Sentinel-1 missions. The time series were generated using a bespoke procedure, based on the Sentinel Application Platform and the GMTSAR software. The validity of the displacement time series has been confirmed through comparison with continuous Global Positioning System data from the Neapolitan Volcanoes Continuous GPS network. Analysis of RADARSAT-2 ground displacements indicates that velocities in the vicinity of Vesuvio were no greater than a few millimetres per year, and no discernible deformation pattern is evident. Consequently, given the uncertainty in Differential Interferometry Synthetic Aperture Radar (DInSAR) measurements, there is no evidence to suggest deformation activity close to Vesuvio between 2010 and 2015. In contrast to Vesuvio, significant deformation is evident in the Campi Flegrei area. The shape of the ground displacement field remained constant between 2010 and 2015, within the uncertainty of DInSAR measurements. The mean upward velocity reaches a maximum of approximately 5 cm y⁻¹, while the mean eastward velocity reaches 2.4 cm y⁻¹. Full article

In this review paper, we briefly discuss the occurrence of oil spills and their behavior under natural sea conditions and clean-up methods, as well as their environmental and economic impacts. We discuss methodologies for oil spill modeling used to predict the fate of a spill under dynamic physical and chemical processes. Weathering processes such as evaporation, emulsification, spreading, dissolution, dispersion, biodegradation, and sedimentation are considered within easy-to-use modeling frameworks. We present simple models based on the principles of thermodynamics, mass transfer, and kinetics that under certain conditions can predict oil thickness, volume, area, composition, and the distribution of toxic compounds in water and air over time for various types of oil and their products. Modeling approaches for underwater oil jets, including applications related to the 2010 BP oil spill in the Gulf of Mexico, are reviewed. The influence of sea surface velocity and wind speed on oil spill mapping, spill location, oil spill trajectory over time, areas affected by light, medium, and heavy oil, and comparisons between satellite images and model predictions are demonstrated. Finally, we introduce several recently published articles on more recent oil spill incidents and the application of predictive models in different regions. We also discuss the challenges, advantages, and disadvantages of various models and offer recommendations at the end of the paper. Full article

Background/Objectives: Chronic stress is associated with long-lasting alterations in brain function, particularly affecting the dynamic interactions between large-scale neural networks during stress and recovery. In this study, we compared changes in brain functional connectivity between states of stress induction and recovery in individuals with chronic stress and investigate the effects of chronic stress on functional brain networks. Methods: We used functional magnetic resonance imaging and ROI-to-ROI analysis to analyze functional connectivity in chronic stress (n = 36). The participants performed the Montreal Imaging Stress Task followed by a recovery phase. Results: The results showed that during the stress induction phase, connectivity between the salience and dorsal attention networks increased, demonstrating enhanced attention and emotional regulation. In contrast, during the recovery phase, connectivity between the default mode and the frontoparietal networks increased, demonstrating cognitive and emotional recovery after stress. Notably, we found that salience network activation continued during the recovery phase, suggesting that individuals with chronic stress may exhibit a continual state of alertness even after stress. Conclusions: Thus, our findings show that chronic stress can lead to the reconstruction of functional networks during the stress response and recovery, contributing to our understanding of the neurobiological correlates of stress-related impairment. Full article

The findings of non-invasive, multi-analytical research on two wall paintings located in the Santuario della Beata Vergine dei Miracoli in Saronno (Varese, Italy)—The Marriage of the Virgin and The Adoration of the Christ Child—are presented in this paper. The authorship of the latter is up for controversy, while the former is unquestionably attributed to Bernardino Luini. The objective was to assess the compatibility of their color palettes through material comparison. A complementary suite of non-invasive techniques, including X-ray fluorescence (XRF), external reflection FTIR, Raman, visible reflectance spectroscopy and hyperspectral imaging, were employed to characterize pigments and surface materials without sampling. Results confirm the use of historically consistent pigments such as calcium carbonate, ochres, Naples yellow, smalt, azurite and lapis lazuli. Differences in the application of blue pigments—lapis lazuli in The Marriage of the Virgin and azurite in The Adoration of the Christ Child—may reflect workshop variation rather than separate authorship. Spectral imaging revealed pigment mixing and layering strategies, especially in skin tones and shadow modeling. This study underscores the significance of diagnostics as an interpretive instrument, capable of contextualizing Luini’s paintings within the context of Renaissance creative practice, providing a framework relevant to analogous inquiries. Full article

Bearings, as commonly used elements in mechanical apparatus, are essential in transmission systems. Fault diagnosis is of significant importance for the normal and safe functioning of mechanical systems. Conventional fault diagnosis methods depend on one or more vibration sensors, and their diagnostic results are often unsatisfactory under strong noise interference. To tackle this problem, this research develops a bearing fault diagnosis technique utilizing a multi-channel, multi-scale spatiotemporal convolutional cross-attention fusion network. At first, continuous wavelet transform (CWT) is applied to convert the raw 1D acoustic and vibration signals of the dataset into 2D time–frequency images. These acoustic and vibration time–frequency images are then simultaneously fed into two parallel structures. After rough feature extraction using ResNet, deep feature extraction is performed using the Multi-Scale Temporal Convolutional Module (MTCM) and the Multi-Feature Extraction Block (MFE). Next, these traits are input into a dual cross-attention mechanism module (DCA), where fusion is achieved using attention interaction. The experimental findings validate the efficacy of the proposed method using tests and comparisons on two bearing datasets. The testing findings validate that the suggested method outperforms the existing advanced multi-sensor fusion diagnostic methods. Compared with other existing multi-sensor fusion diagnostic methods, the proposed method was proven to outperform the five existing methods (1DCNN-VAF, MFAN-VAF, 2MNET, MRSDF, and FAC-CNN). Full article

This study investigated the morphometric characteristics of adenohypophyseal thyrotrophs and circulating thyroid hormone profiles in dromedary camels (Camelus dromedarius) in relation to age and lactation status. Clinically healthy Brela breed camels were divided into lactating female, and non-lactating female groups across two age categories (5–10 years and ≥11 years), with fifty animals per group. Blood samples were collected before slaughter and pituitary glands were collected post-slaughter and processed for immunohistochemical detection of thyroid-stimulating hormone (TSH) using anti-porcine TSHβ antibody, while morphometric measurements of thyrotrophs were conducted through image analysis. Plasma concentrations of TSH, triiodothyronine (T₃), and thyroxine (T₄) were quantified using validated ELISA and enzyme immunoassay kits. Group differences were analyzed using one-way ANOVA followed by post hoc comparisons, with statistical significance set at p < 0.05. Morphometric analysis revealed that lactating female camels exhibited significantly higher thyrotroph counts compared with non-lactating counterparts, whereas non-lactating females displayed larger cell and nuclear dimensions. Age influenced these patterns, with older camels showing hypertrophied thyrotrophs but reduced functional plasticity compared to younger animals. Plasma hormone assays demonstrated that non-lactating camels had higher TSH and T₄ concentrations, while lactating camels maintained elevated T₃ levels, suggesting enhanced peripheral conversion of T₄ to T₃ during milk production. Additionally, younger camels exhibited higher T₃ concentrations than older animals, indicating age-related decline in thyroidal activity. These findings highlight the dynamic regulation of the hypothalamic–pituitary–thyroid axis in camels, demonstrating how lactation and age shape thyroidal morphology and function to meet diverse physiological demands. These findings not only broaden the comparative endocrinology of underexplored species but also provide physiopathological insights relevant to farm animal management, lactation efficiency, and adaptive metabolism in harsh environments. Full article