Search Results (3,546)

Multiple sclerosis (MS), a chronic disease of the central nervous system, is known to cause structural and vascular changes in the retina. Although optical coherence tomography (OCT) and fundus photography can detect retinal thinning and circulatory abnormalities, these findings are not specific to MS. This study explores the potential of Infrared Scanning-Laser-Ophthalmoscopy (IR-SLO) imaging to uncover vascular morphological features that may serve as MS-specific biomarkers. Using an age-matched, subject-wise stratified k-fold cross-validation approach, a deep learning model originally designed for color fundus images was adapted to segment optic disc, optic cup, and retinal vessels in IR-SLO images, achieving Dice coefficients of 91%, 94.5%, and 97%, respectively. This process included tailored pre- and post-processing steps to optimize segmentation accuracy. Subsequently, clinically relevant features were extracted. Statistical analyses followed by SHapley Additive exPlanations (SHAP) identified vessel fractal dimension, vessel density in zones B and C (circular regions extending 0.5–1 and 0.5–2 optic disc diameters from the optic disc margin, respectively), along with vessel intensity and width, as key differentiators between MS patients and healthy controls. These findings suggest that IR-SLO can non-invasively detect retinal vascular biomarkers that may serve as additional or alternative diagnostic markers for MS diagnosis, complementing current invasive procedures. Full article

Aiming at addressing the defect of the data blindness of a LiDAR point cloud in transparent media such as glass in low illumination environments, a new method is proposed to realize covert target reconnaissance, identification and ranging using the fusion of a shimmering polarized image and a laser LiDAR point cloud, and the corresponding system is constructed. Based on the extraction of pixel coordinates from the 3D LiDAR point cloud, the method adds information on the polarization degree and polarization angle of the micro-light polarization image, as well as on the reflective intensity of each point of the LiDAR. The mapping matrix of the radar point cloud to the pixel coordinates is made to contain depth offset information and show better fitting, thus optimizing the 3D point cloud converted from the micro-light polarization image. On this basis, algorithms such as 3D point cloud fusion and pseudo-color mapping are used to further optimize the matching and fusion procedures for the micro-light polarization image and the radar point cloud, so as to successfully realize the alignment and fusion of the 2D micro-light polarization image and the 3D LiDAR point cloud. The experimental results show that the alignment rate between the 2D micro-light polarization image and the 3D LiDAR point cloud reaches 74.82%, which can effectively detect the target hidden behind the glass under the low illumination condition and fill the blind area of the LiDAR point cloud data acquisition. This study verifies the feasibility and advantages of “polarization + LiDAR” fusion in low-light glass scene reconnaissance, and it provides a new technological means of covert target detection in complex environments. Full article

Computer vision techniques such as three-dimensional digital image correlation (3D-DIC) and three-dimensional point tracking (3D-PT) have demonstrated broad applicability for monitoring the conditions of large-scale engineering systems by reconstructing and tracking dynamic point clouds corresponding to the surface of a structure. Accurate stereophotogrammetry measurements require the stereo cameras to be calibrated to determine their intrinsic and extrinsic parameters by capturing multiple images of a calibration object. This image-based approach becomes cumbersome and time-consuming as the size of the tested object increases. To streamline the calibration and make it scale-insensitive, a multi-sensor system embedding inertial measurement units and a laser sensor is developed to compute the extrinsic parameters of the stereo cameras. In this research, the accuracy of the proposed sensor-based calibration method in performing stereophotogrammetry is validated experimentally and compared with traditional approaches. Tests conducted at various scales reveal that the proposed sensor-based calibration enables reconstructing both static and dynamic point clouds, measuring displacements with an accuracy higher than 95% compared to image-based traditional calibration, while being up to an order of magnitude faster and easier to deploy. The novel approach has broad applications for making static, dynamic, and deformation measurements to transform how large-scale structural health monitoring can be performed. Full article

Background/Objectives: In recent years, lipids have emerged as critical regulators of different disease processes, being involved in cancer pathogenesis, progression, and outcome. Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI) has significantly expanded the technology’s reach, enabling spatially resolved profiling of lipids directly from tissue, including formalin-fixed paraffin-embedded (FFPE) specimens. In this context, MALDI matrix selection is crucial for lipid extraction and ionization, influencing key aspects such as molecular coverage and sensitivity, especially in such specimens with already depleted lipid content. Thus, in this work, we aim to explore the feasibility of mapping lipid species in FFPE clinical samples with MALDI-MSI using 6-aza-2-thiothymine (ATT) as a matrix of choice. Methods: To do so, ATT performances were first compared to those two other matrices commonly used for lipidomic analyses, 2′,5′-dihydroxybenzoic acid (DHB) and Norharmane (NOR), on lipid standards. Results: As a proof-of-concept, we then assessed ATT’s performance for the MALDI-MSI analysis of lipids in FFPE brain sections, both in positive and negative ion modes, comparing results with those obtained from other commonly used dual-polarity matrices. In this context, ATT enabled the putative annotation of 98 lipids while maintaining a well-balanced detection of glycerophospholipids (60.2%) and sphingolipids (32.7%) in positive ion mode. It outperformed both DHB and NOR in the identification of glycolipids (3%) and fatty acids (4%). Additionally, ATT exceeded DHB in terms of total lipid count (62 vs. 21) and class diversity and demonstrated performance comparable to NOR in negative ion mode. Moreover, ATT was applied to a FFPE glioblastoma tissue microarray (TMA) evaluating the ability of this matrix to reveal biologically relevant lipid features capable of distinguishing normal brain tissue from glioblastoma regions. Conclusions: Altogether, the results presented in this work suggest that ATT is a suitable matrix for pathology imaging applications, even at higher lateral resolutions of 20 μm, not only for proteomic but also for lipidomic analysis. This could enable the use of the same matrix type for the analysis of both lipids and peptides on the same tissue section, offering a unique strategic advantage for multi-omics studies, while also supporting acquisition in both positive and negative ionization modes. Full article

Experimental and simulation analysis was conducted on the effects of 532 nm nanosecond laser-induced thermal damage on the front-side illuminated CMOS detector. The study examined CMOS detector output images at different stages of damage, including point damage, line damage, and complete failure, and correlated these with microscopic structural changes observed through optical and scanning electron microscopy. A finite element model was used to study the thermal–mechanical coupling effect during laser irradiation. The results indicated that at a laser energy density of 78.9 mJ/cm², localized melting occurs within photosensitive units in the epitaxial layer, manifesting as an irreversible white bright spot appearing in the detector output image (point damage). When the energy density is further increased to 241.9 mJ/cm², metal routings across multiple pixel units melt, resulting in horizontal and vertical black lines in the output image (line damage). Upon reaching 2005.4 mJ/cm², the entire sensor area failed to output any valid image due to thermal stress-induced delamination of the silicon dioxide insulation layer, with cracks propagating to the metal routing and epitaxial layers, ultimately causing structural deformation and device failure (complete failure). Full article

This paper proposes an intelligent power adaptation framework for Free-Space Optics (FSO) communication systems operating under different weather conditions exploiting a deep learning (DL) analysis of received eye diagram images. The system incorporates two Convolutional Neural Network (CNN) architectures, LeNet and Wide Residual Network (Wide ResNet) algorithms to perform regression tasks that predict received signal quality metrics such as the Quality Factor (Q-factor) and Bit Error Rate (BER) from the received eye diagram. These models are evaluated using Mean Squared Error (MSE) and the coefficient of determination (${\mathrm{R}}^2$ score) to assess prediction accuracy. Additionally, a custom CNN-based classifier is trained to determine whether the BER reading from the eye diagram exceeds a critical threshold of ${10}^{-4}$; this classifier achieves an overall accuracy of 99%, correctly detecting 194/195 “acceptable” and 4/5 “unacceptable” instances. Based on the predicted signal quality, the framework activates a dual-amplifier configuration comprising a pre-channel amplifier with a maximum gain of 25 dB and a post-channel amplifier with a maximum gain of 10 dB. The total gain of the amplifiers is adjusted to support the operation of the FSO system under all-weather conditions. The FSO system uses a 15 dBm laser source at 1550 nm. The DL models are tested on both internal and external datasets to validate their generalization capability. The results show that the regression models achieve strong predictive performance, and the classifier reliably detects degraded signal conditions, enabling the real-time gain control of the amplifiers to achieve the quality of transmission. The proposed solution supports robust FSO communication under challenging atmospheric conditions including dry snow, making it suitable for deployment in regions like Northern Europe, Canada, and Northern Japan. Full article

To improve the accuracy of three-dimensional (3D) reconstruction under microscopic conditions for laser-induced breakdown spectroscopy (LIBS), this study developed a novel visual platform by integrating an industrial CCD camera with a microscope. A customized microscale calibration target was designed to calibrate intrinsic and extrinsic camera parameters accurately. Based on the pinhole imaging model, disparity maps were obtained via pixel matching to reconstruct high-precision 3D ablation morphology. A mathematical model was established to analyze how key imaging parameters—baseline distance, focal length, and depth of field—affect reconstruction accuracy in micro-imaging environments. Focusing on trace element detection in WC-Co alloy samples, the reconstructed ablation craters enabled the precise calculation of ablation volumes and revealed their correlations with laser parameters (energy, wavelength, pulse duration) and the physical-chemical properties of the samples. Multivariate regression analysis was employed to investigate how ablation morphology and plasma evolution jointly influence LIBS quantification. A nonlinear calibration model was proposed, significantly suppressing matrix effects, achieving R² = 0.987, and reducing RMSE to 0.1. This approach enhances micro-scale LIBS accuracy and provides a methodological reference for high-precision spectral analysis in environmental and materials applications. Full article

Titanium–aluminum–vanadium (Ti6Al4V) is a material chosen for spine, orthopedic, and dental implants due to its combination of desirable mechanical and biological properties. Lasers have been used to modify metal surfaces, enabling the generation of a surface on Ti6Al4V with distinct micro- and nano-scale structures. Studies indicate that topography with micro/nano features of osteoclast resorption pits causes bone marrow stromal cells (MSCs) and osteoprogenitor cells to favor differentiation into an osteoblastic phenotype. This study examined whether the biological response of human MSCs to Ti6Al4V surfaces is sensitive to laser treatment-controlled micro/nano-topography. First, 15 mm diameter Ti6Al4V discs (Spine Wave Inc., Shelton, CT, USA) were either machined (M) or additively manufactured (AM). Surface treatments included no laser treatment (NT), nanosecond laser (Ns), femtosecond laser (Fs), or nanosecond followed by femtosecond laser (Ns+Fs). Surface wettability, roughness, and surface chemistry were determined using sessile drop contact angle, laser confocal microscopy, X-ray photoelectron spectroscopy (XPS), and scanning electron microscopy (SEM). Human MSCs were cultured in growth media on tissue culture polystyrene (TCPS) or test surfaces. On day 7, the levels of osteocalcin (OCN), osteopontin (OPN), osteoprotegerin (OPG), and vascular endothelial growth factor 165 (VEGF) in the conditioned media were measured. M NT, Fs, and Ns+Fs surfaces were hydrophilic; Ns was hydrophobic. AM NT and Fs surfaces were hydrophilic; AM Ns and Ns+Fs were hydrophobic. Roughness (Sa and Sz) increased after Ns and Ns+Fs treatment for both M and AM disks. All surfaces primarily consisted of oxygen, titanium, and carbon; Fs had increased levels of aluminum for both M and AM. SEM images showed that M NT discs had a smooth surface, whereas AM surfaces appeared rough at a higher magnification. Fs surfaces had a similar morphology to their respective NT disc at low magnification, but higher magnification revealed nano-scale bumps not seen on NT surfaces. AM Fs surfaces also had regular interval ridges that were not seen on non-femto laser-ablated surfaces. Surface roughness was increased on M and AM Ns and Ns+Fs disks compared to NT and Fs disks. OCN was enhanced, and DNA was reduced on Ns and Ns+Fs, with no difference between them. OPN, OPG, and VEGF levels for laser-treated M surfaces were unchanged compared to NT, apart from an increase in OPG on Fs. MSCs grown on AM Ns and Ns+Fs surfaces had increased levels of OCN per DNA. These results indicate that MSCs cultured on AM Ns and AM Ns+Fs surfaces, which exhibited unique roughness at the microscale and nanoscale, had enhanced differentiation to an osteoblastic phenotype. The laser treatments of the surface mediated this enhancement of MSC differentiation and warrant further clinical investigation. Full article

Aiming to address the problems of asynchronous acquisition time of multiple sensors in the crop phenotype acquisition system and high cost of the acquisition equipment, this paper developed a low-cost crop phenotype synchronous acquisition system based on the PTP synchronization protocol, realizing the synchronous acquisition of three types of crop data: visible light images, thermal infrared images, and laser point clouds. The paper innovatively proposed the Difference Structural Similarity Index Measure (DSSIM) index, combined with statistical indicators (average point number difference, average coordinate error), distribution characteristic indicators (Charm distance), and Hausdorff distance to characterize the stability of the system. After 72 consecutive hours of synchronization testing on the timing boards, it was verified that the root mean square error of the synchronization time for each timing board reached the ns level. The synchronous trigger acquisition time for crop parameters under time synchronization was controlled at the microsecond level. Using pepper as the crop sample, 133 consecutive acquisitions were conducted. The acquisition success rate for the three phenotypic data types of pepper samples was 100%, with a DSSIM of approximately 0.96. The average point number difference and average coordinate error were both about 3%, while the Charm distance and Hausdorff distance were only 1.14 mm and 5 mm. This system can provide hardware support for multi-parameter acquisition and data registration in the fast mobile crop phenotype platform, laying a reliable data foundation for crop growth monitoring, intelligent yield analysis, and prediction. Full article

Lotus (Nelumbo nucifera Gaertn.) is a quintessential medicinal and edible plant, exhibiting marked differences in therapeutic effects among its various parts. The lotus seed constitutes a key component of this plant. Notably, the entire seed and the plumule display distinct medicinal properties. To investigate the “homologous plants with different effects” phenomenon in traditional Chinese medicine, this study established a Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI) method. This study employed immature lotus seeds as the experimental material, diverging from the mature seeds conventionally used. Conductive double-sided tape was employed for sample preparation, and complete longitudinal sections of the seeds were obtained, followed by MALDI-MSI analysis to identify and visualize the spatial distribution of characteristic secondary metabolites within the entire seeds. The results unveiled the diversity of metabolites in lotus seeds and their differential distribution across tissues, with pronounced distinctions in the plumule. A total of 152 metabolites spanning 13 categories were identified in lotus seeds, with 134, 89, 51, and 98 metabolites discerned in the pericarp, seed coat, cotyledon, and plumule, respectively. Strikingly, young lotus seeds were devoid of liensinine/isoliensinine and neferine, the dominant alkaloids of mature lotus seed plumule, revealing an early-stage alkaloid profile that sharply contrasts with the well-documented abundance found in mature seeds and has rarely been reported. We further propose a biosynthetic pathway to explain the presence of the detected benzylisoquinoline and the absence of the undetected bisbenzylisoquinoline alkaloids in this study. These findings present the first comprehensive metabolic atlas of immature lotus seeds, systematically exposing the pronounced chemical divergence from their mature counterparts, and thus lays a metabolomic foundation for dissecting the spatiotemporal mechanisms underlying the nutritional and medicinal value of lotus seeds. Full article

Image processing has been widely adopted as an effective technology for analyzing weld forming quality which is greatly affected by the welding process parameters. In this paper, an L₂₅(5³) orthogonal experiment is designed to investigate the effects of welding process parameters on the weld forming quality in laser welding of aluminum alloy. The weld characteristics including the weld width (WW), weld penetration (PD), weld area (WA) and weld porosity (WP) under the conditions of the different welding process parameters consisting of the laser power (LP), welding speed (WS) and defocus distance (DD) are extracted from the laser welding experiment based on image processing. The effectiveness of the weld characteristics extraction method is verified by comparing the extracted results with the measured results. It is found that the WW, PD and WA are all significantly influenced by the LP among the three welding process parameters while the influences of the three process parameters on the WP are insignificant. The DD has a significant influence on the PD and the WS has a significant influence on the WA. The corresponding significance of influence is lower than the significance of influence of LP. The analysis results are conducive to the optimization of laser welding process parameters and improvement of welding quality. Full article

Elevated extracellular potassium (K⁺) in the tumor microenvironment (TME) of breast and other cancers is increasingly recognized as a critical factor influencing tumor progression and immune suppression. Current methods for noninvasive mapping of the potassium distribution in tumors are limited. Here, we employed photoacoustic chemical imaging (PACI) with a solvatochromic dye-based, potassium-sensitive nanoprobe (SDKNP) to quantitatively visualize extracellular potassium levels in an orthotopic metaplastic breast cancer mouse model, Ccn6-KO. Tumors of three distinct sizes (5 mm, 10 mm, and 20 mm) were imaged using multi-wavelength photoacoustic imaging at five laser wavelengths (560, 576, 584, 605, and 625 nm). Potassium concentration maps derived from spectral unmixing of the photoacoustic images at the five laser wavelengths revealed significantly increased potassium levels in larger tumors, confirmed independently by inductively coupled plasma mass spectrometry (ICP-MS). The PACI results matched ICP-MS measurements, validating PACI as a robust, noninvasive imaging modality for potassium mapping in tumors in vivo. This work establishes PACI as a promising tool for studying the chemical properties of the TME and provides a foundation for future studies evaluating the immunotherapy response through ionic biomarker imaging. Full article

Pesticide residues in fruits and vegetables pose a serious threat to food safety. Traditional detection methods have defects such as complex operation, high cost, and long detection time. Therefore, it is of great significance to develop rapid, non-destructive, and efficient detection technologies and equipment. In recent years, the combination of spectroscopic techniques and imaging technologies with machine learning algorithms has developed rapidly, providing a new attempt to solve this problem. This review focuses on the research progress of the combination of spectroscopic techniques (near-infrared spectroscopy (NIRS), hyperspectral imaging technology (HSI), surface-enhanced Raman scattering (SERS), laser-induced breakdown spectroscopy (LIBS), and imaging techniques (visible light (VIS) imaging, NIRS imaging, HSI technology, terahertz imaging) with machine learning algorithms in the detection of pesticide residues in fruits and vegetables. It also explores the huge challenges faced by the application of spectroscopic and imaging technologies combined with machine learning algorithms in the intelligent perception of pesticide residues in fruits and vegetables: the performance of machine learning models requires further enhancement, the fusion of imaging and spectral data presents technical difficulties, and the commercialization of hardware devices remains underdeveloped. This review has proposed an innovative method that integrates spectral and image data, enhancing the accuracy of pesticide residue detection through the construction of interpretable machine learning algorithms, and providing support for the intelligent sensing and analysis of agricultural and food products. Full article

Background: Choroidal nevi are common, benign tumors. These tumors rarely cause adverse retinal sequalae, but when they do, they can lead to disruption of the outer retina and vision loss. In this paper, we used high-resolution retinal imaging modalities, optical coherence tomography (OCT) and adaptive optics scanning laser ophthalmoscopy (AOSLO), to longitudinally monitor retinal sequelae of a submacular choroidal nevus. Methods: A 31-year-old female with a high-risk choroidal nevus resulting in subretinal fluid (SRF) and a 30-year-old control subject were longitudinally imaged with AOSLO and OCT in this study over 18 and 22 months. Regions of interest (ROI) including the macular region (where SRF was present) and the site of laser photocoagulation were imaged repeatedly over time. The depth of SRF in a discrete ROI was quantified with OCT and AOSLO images were assessed for visualization of photoreceptors and retinal pigmented epithelium (RPE). Cell-like structures that infiltrated the site of laser photocoagulation were measured and their count was assessed over time. In the control subject, images were assessed for RPE visualization and the presence and stability of cell-like structures. Results: We demonstrate that AOSLO can be used to assess cellular-level changes at small ROIs in the retina over time. We show the response of the retina to SRF and laser photocoagulation. We demonstrate that the RPE can be visualized when SRF is present, which does not appear to depend on the height of retinal elevation. We also demonstrate that cell-like structures, presumably immune cells, are present within and adjacent to areas of SRF on both OCT and AOSLO, and that similar cell-like structures infiltrate areas of retinal laser photocoagulation. Conclusions: Our study demonstrates that dynamic, cellular-level retinal responses to SRF and laser photocoagulation can be monitored over time with AOSLO in living humans. Many retinal conditions exhibit similar retinal findings and laser photocoagulation is also indicated in numerous retinal conditions. AOSLO imaging may provide future opportunities to better understand the clinical implications of such responses in vivo. Full article

Fluid resuscitation after thermal injury is paramount to avoid burn shock and restore organ perfusion. Both over- and under-resuscitation can lead to unintended consequences affecting patient outcomes. While many studies have examined systemic effects, limited data exist on how fluid resuscitation impacts burn wound progression in the acute period. Furthermore, the mechanisms underlying burn wound progression remain not fully understood. This study used a swine model to investigate how varying resuscitation levels affect peri-burn wound dynamics. Twenty-seven female Yorkshire pigs were anesthetized, subjected to 40% total body surface area burn and 15% hemorrhage, then randomized (n = 9) to receive decision-support-driven (adequate, 2–4 mL/kg/%TBSA), fluid-withholding (under, <1 mL/kg/%TBSA), or high-constant-rate (over, >>4 mL/kg/%TBSA) resuscitation. Pigs were monitored for 24 h in an intensive care setting prior to necropsy. Laser Doppler Imaging (LDI) was conducted pre-burn and at 2, 6, 12, and 24 h post burn to assess perfusion. Biopsies were taken from burn, peri-burn (within 2 cm), and normal skin. RNA was isolated at 24 h for the qRT-PCR analysis of IL-6, CXCL8, and IFN-γ. At hour 2, LDI revealed increased peri-burn perfusion in over-resuscitated animals vs. under-resuscitated animals (p = 0.0499). At hour 24, IL-6 (p = 0.0220) and IFN-γ (p = 0.0253) were elevated in over-resuscitated peri-burn skin. CXCL8 showed no significant change. TUNEL staining revealed increased apoptosis in over- and under-resuscitated peri-burn skin. Differences in perfusion and cytokine expression based on resuscitation strategy suggest that fluid levels may influence burn wound progression. Full article