Search Results (1,989)

Surgical navigation and augmented reality (AR) are widely used in neurosurgery, spinal surgery, and orthopedics. However, their use in minimally invasive abdominal and thoracic soft-tissue surgery is limited, as tracking deformable, mobile organs is challenging. Recent advances in AR may address these challenges to improve intraoperative navigation. This systematic review, registered in PROSPERO (2024) and based on PRISMA guidelines, analyzes literature from 2014 to 2024 about AR in minimally invasive abdominal and thoracic soft-tissue surgery. It identifies target organs, describes AR hardware and software, and evaluates accuracy levels, usability outcomes, clinical benefits, technical limitations, and research needs. Searches of PubMed, Web of Science, and Embase for English-language studies found 1297 records, of which only 28 (2%) met the inclusion criteria. Nearly half (n =12; 42%) focused on liver surgery; none on gynecologic surgery. The AR devices varied in tracking methods, image processing, visualization, and display. Overall, AR improved anatomical guidance and procedural planning, especially in complex surgeries. Integration with robotic systems may further boost visualization, precision, and workflow, though challenges remain in standardization, large-cohort validation, and workflow integration. Full article

Background: Diabetic foot ulcers (DFUs) represent a major chronic complication of diabetes mellitus, often leading to severe infection, amputation, and reduced quality of life. Among various factors affecting DFUs, plantar pressure plays a pivotal role in ulcer formation and recurrence. Despite growing interest in this domain, few studies have comprehensively evaluated the research landscape concerning plantar pressure in the context of DFUs from a bibliometric perspective. Aim: To conduct a comprehensive bibliometric analysis and visualization of global research trends, hotspots, and collaborative networks in the field of plantar pressure-related diabetic foot studies from 2000 to 2024. Methods: A systematic search was conducted in the Web of Science Core Collection (WoSCC) on 16 February 2025, for articles published between 2000 and 2024 using terms related to “diabetic foot” and “plantar pressure”. A total of 2518 records were retrieved, from which 2110 English-language articles and reviews were included. Bibliometric and visual analyses were performed using Microsoft Excel 2021, VOSviewer (v1.6.20), CiteSpace (v6.4.R1), Charticulator, and Scimago Graphica. Analyses included publication trends, country/institution/author collaborations, journal distributions, keyword co-occurrence and clustering, citation bursts, and reference co-citation networks. Results: A total of 2110 publications were identified, showing an overall increase in annual publication output from 2000 to 2024, with some year-to-year fluctuations. The United States led in publication volume (678 articles), citation frequency, and H-index, followed by the United Kingdom and China. Armstrong, David was the most prolific and also had the highest H-index among the listed authors, while the University of Amsterdam was the leading institution. “Journal of Wound Care” had the highest publication count, whereas “Diabetes Care” ranked first in citation frequency. Keyword analysis revealed major research clusters including “diabetic foot”, “plantar pressure”, “wound healing”, “offloading”, and “negative pressure wound therapy”. Recent trends show an increased focus on microcirculation, regenerative medicine, customized footwear, and wound care technologies. Conclusions: The bibliometric analysis reveals research trends and current hotspots in plantar pressure management for diabetic foot ulcers, with a particular focus on managing plantar pressure through personalized offloading strategies and custom footwear. These findings highlight the practical value of tailoring interventions to individual patient needs, emphasizing the importance of biomechanical factors in ulcer prevention and healing. Full article

Side-scan sonar (SSS) serves as the primary perceptual instrument for Autonomous Underwater Vehicles (AUVs) in large-scale marine search and rescue (SAR) operations. However, the detection of critical targets is frequently hindered by severe hydro-acoustic noise, the spatial discontinuity of wreckage, and the weak visual signatures of small targets. To surmount these challenges, this paper presents WPG-DetNet. First, we introduce a Wavelet-Embedded Residual Backbone (WERB) to reconstruct the conventional downsampling paradigm. By substituting standard pooling with the Discrete Wavelet Transform (DWT), this architecture explicitly disentangles high-frequency noise from structural information in the frequency domain, thereby achieving the adaptive preservation of edge fidelity for large human-made targets while filtering out speckle interference. Then, addressing the distinct challenge of discontinuous aircraft wreckage, the framework further incorporates a Debris Graph Reasoning Module (D-GRM). This module models scattered fragments as nodes in a topological graph to capture long-range semantic dependencies, transforming isolated instance recognition into context-aware scene understanding. Finally, to bridge the gap between AI and underwater physics, we design a Shadow-Aided Decoupling Head (SADH) equipped with a physics-informed geometric loss. By enforcing mathematical consistency between target height and acoustic shadow length, this mechanism establishes a rigorous discriminative criterion capable of distinguishing weak-echo human bodies from seabed rocks based on shadow geometry. Experiments on the SCTD dataset demonstrate that WPG-DetNet achieves a mean Average Precision ($mA{P}_{50}$) of 97.5% and a Recall of 96.9%. Quantitative analysis reveals that our framework outperforms the classic Faster R-CNN by a margin of 12.8% in $mA{P}_{50}$ and surpasses the Transformer-based RT-DETR-R18 by 5.6% in high-precision localization metrics ($mA{P}_{50:95}$). Simultaneously, WPG-DetNet maintains superior efficiency with an inference speed of 62.5 FPS and a lightweight parameter count of 16.8 M, striking an optimal balance between robust perception and the real-time constraints of AUV operations. Full article

This paper presents a comprehensive systematic review examining the application of augmented reality (AR) and sensor technologies for visualizing ionizing radiation in virtual training environments. The review methodology involved systematic identification and analysis of the relevant literature based on predetermined criteria including publication type, year of publication, application domain, and technological approach. The literature search encompassed publications from 2011 to 2021 across four major academic databases: Web of Science, Google Scholar, IEEE Xplore, and Scopus. Through rigorous screening following PRISMA 2020 guidelines, 23 research articles met the inclusion criteria for detailed analysis. From 404 initial database records, 360 were excluded during title/abstract screening (primarily for lacking AR components, radiation focus, or training applications) and 4 during full-text assessment (all for lacking sensor integration). The findings reveal that AR-based ionizing radiation visualization has been successfully implemented across diverse domains, including nuclear facility operations, medical procedures, CERN research activities, and educational and monitoring applications. The analysis identified multiple dimensions of impact, encompassing distinct benefits, emerging opportunities, and implementation challenges associated with AR deployment for ionizing radiation training. Each of these dimensions is comprehensively examined and documented within this review. Additionally, this study identifies critical research gaps that currently limit the full potential of AR technology in supporting ionizing radiation training programs. These gaps are systematically analyzed and discussed to establish clear directions for future research endeavors in this emerging field. Full article

In unmanned ground vehicle (UGV) swarm systems, comprehensive environmental awareness is critical for coordinated operations. Yet they are frequently deployed in occlusion-rich, constrained environments where multi-agent visual fusion is essential. However, existing methods are critically limited by offline-calibrated extrinsic parameters, hindering flexible deployment, and by a strong co-visibility assumption, which fails under severe occlusion. To overcome these constraints, we introduce an end-to-end, calibration-free framework for the joint registration of cameras and subjects. Our approach begins with a single-view module that estimates subjects’ poses and appearance features. Subsequently, a novel graph-based pose propagation module (GPPM) treats UGVs’ cameras as nodes in a graph, connecting them with edges when they share co-visible subjects identified via appearance matching. Breadth-first search (BFS) then finds the shortest registration path from any camera to a designated root camera, enabling pose propagation via local co-visibility links and global alignment of all subjects into a unified bird’s-eye-view (BEV) space. This strategy relaxes the stringent requirement of full co-visibility with the root node. A multi-task loss function is proposed to jointly optimize pose estimation and feature matching. Trained and evaluated on a synthetic dataset with occlusions (CSRD-O) collected by a UGV swarm system, our framework achieves mean camera pose errors of 1.57 m/8.70° and mean subject pose errors of 1.40 m/9.14°. Furthermore, we demonstrate a scene monitoring task using a UGV swarm system. Experiments show that the proposed method generates robust BEV estimates even under severe occlusion and low inter-view overlap. This work presents a purely visual, self-calibrating multi-view fusion perception scheme, demonstrating its potential to support cooperative perception, task-oriented monitoring, and collective situational awareness in UGV swarm systems. Full article

The State of Health (SOH) of a battery is an important indicator for measuring the performance degradation of batteries. In view of the deficiencies of existing SOH estimation methods in feature processing and model accuracy, this paper conducts research on high-precision SOH estimation methods for lithium-ion batteries. A BiLSTM model optimized by the Sparrow Search Algorithm (SSA) is adopted for SOH estimation. The SSA-BiLSTM model is constructed, and the experiments are conducted on multiple types of battery datasets, such as NCM811 and LFP, and the cross-validation strategy is used to evaluate the model’s performance. The experimental results show that the SOH prediction system software developed based on this model has the functions of rapid estimation and three-dimensional trend visualization. The paper verifies the functions of the SOH prediction system software developed by the model, which has practical reference significance for the development and application of SOH estimation systems in energy storage scenarios. Full article

This paper develops a rigorous mathematical and computational framework for four-dimensional chess defined on the discrete hypercubic lattice $\{1,\dots , 8{\}}^4$. We formalize piece movement using displacement sets in ${\mathbb{Z}}^4$, define adjacency via the Chebyshev metric, and analyze the resulting move graphs for rooks, bishops, knights, queens, and kings. We establish exact mobility formulas, parity invariants, and connectivity properties, consolidating known product-graph results for rooks and kings while introducing a boundary-sensitive analysis of the four-dimensional knight verified by exhaustive enumeration. The mathematical framework is complemented by a fully implemented 4D chess engine and interactive visualization environment rendering all 64 (z,w)-slices of the hypercube simultaneously. The system supports full move legality, generalized special rules, multi-king checkmate detection, and reproducible state enumeration. Performance measurements and exploratory branching-factor estimates are obtained through reproducible random playouts using the publicly available implementation. We contextualize this ruleset within existing work on move graphs on ${\mathbb{Z}}_n^m$, higher-dimensional leapers, spectral properties of grid graphs, toroidal analogs, and multidimensional visualization. Exploratory qualitative feedback (N = 18) is included to examine whether the visualization design is interpretable and navigable in practice, providing feasibility-oriented observations on how slice-based 4D projection and layered board rendering are perceived by non-expert users in an exploratory context. Together, the mathematical results, implemented engine, and visualization form a coherent foundation for the study of strategy, complexity, and human interaction in four-dimensional game systems. The framework provides a basis for future investigations into spectral analysis of move graphs, symmetry-aware search, hierarchical planning, and educational applications in high-dimensional geometry. Full article

Necrotizing (abscessing) lymphadenopathy is a clinically relevant condition with a broad differential diagnosis, including acute bacterial infections, mycobacterial disease, zoonoses, fungal and parasitic infections, autoimmune disorders, and malignancies with central necrosis. Early and reliable differentiation between these causes is important to avoid misdiagnosis and to guide appropriate therapy. This review summarizes the pathophysiological mechanisms, typical imaging features, and diagnostic value of contrast-enhanced ultrasound (CEUS) in necrotizing lymphadenopathy. Representative clinical vignettes illustrate the disease spectrum and correlate CEUS patterns with underlying pathology. The literature review was narrative and based on targeted searches of PubMed/MEDLINE and Google Scholar focusing on CEUS in necrotizing lymphadenopathy. A brief literature overview highlights current evidence, limitations, and research gaps. Conventional B-mode ultrasound (BMUS) and Doppler typically demonstrate enlarged hypoechoic or heterogeneous nodes with reduced central vascularity but lack specificity for necrosis. CEUS provides real-time visualization of nodal microvascular perfusion, which may support clearer differentiation between viable tissue and necrotic or abscess cavities. Common but non-specific CEUS patterns include central non-enhancement with a peripheral hyperemic rim in abscesses, irregular avascular cores in tuberculous lymphadenopathy, patchy non-enhancing areas in autoimmune conditions, and heterogeneous enhancement with ill-defined necrosis in malignant nodes. CEUS can support biopsy targeting, facilitate drainage procedures, and enable radiation-free follow-up. CEUS may offer diagnostic and interventional advantages in the evaluation of necrotizing lymphadenopathy, offering more consistent characterization of nodal necrosis compared with conventional sonography. While most evidence focuses on tuberculosis and malignancy, growing experience with zoonotic and autoimmune diseases suggests broader utility. Most currently available evidence derives from observational studies and small case series, highlighting the need for prospective multicenter validation. Standardization of CEUS criteria, integration into multiparametric ultrasound protocols, and multicenter validation are needed to establish CEUS as a routine component in the diagnostic work-up of necrotizing lymphadenopathy. Full article

Background: Chronic Recalcitrant Plantar Fasciopathy (CRPF) is resistant to conservative treatments and has historically been managed with Open Plantar Fasciotomy (OPF). This systematic review aims to evaluate the role of the Gastrocnemius Release Procedures (GRPs) in treating CRPF, focusing on its indications, surgical techniques and clinical outcomes. Methods: A systematic literature search was conducted following PRISMA guidelines using MEDLINE, Cochrane and Scopus. Studies pertinent to the topic were screened, and those that reported clinical outcomes of GRPs in patients with CRPF were retrieved. The quality assessment was carried out using the Newcastle–Ottawa Scale. Results: Eighteen studies met the inclusion criteria, analyzing a total of 901 patients with a mean follow-up of 27.8 months. Indications for performing GRPs subsisted if conservative treatment failed to relieve pain and if Isolated Gastrocnemius Contracture (IGC) was present. All GRPs significantly reduced pain, with Visual Analogue Scale (VAS) scores decreasing from a mean of 7.3 pre-operatively to 2.56 post-operatively (64.93% reduction). American Orthopaedic Foot & Ankle Society (AOFAS) scores improved from 50.1 to 84.7 on average. Ankle dorsiflexion increased by an average of 7.75°. Patient satisfaction was high, with an average rate of 85% (range 61.6% to 100%). Minor complications were reported but resolved in most cases. Conclusions: Indications for performing GRPs still need to be clarified, and the best surgical technique remains to be defined. Nevertheless, the GRP seems to offer sustained pain relief and functional improvement in patients with CRPF. Full article

Unmanned underwater vehicles (UUVs) play a pivotal role in marine applications such as resource exploration, maritime search and rescue. However, communication signal loss remains a critical bottleneck, constraining UUV autonomous operation and mission reliability across four dimensions: navigation, coordination, monitoring, and planning. To address these challenges in communication-denied environments, this paper proposes a UUV digital twin system utilizing motion prediction technology, such as virtual mapping, prediction, and autonomous decision support. Based on a four-layer architecture—comprising the Physical Entity Layer, Virtual Entity Layer, Twin Data & Connectivity Layer, and Services Layer, the system achieves full-state mapping and real-time visualization. Specifically, a hybrid prediction model integrating Transformer and Convolutional Neural Networks (CNN) architectures is developed to extract multi-scale features for resistance prediction, which serves as the critical basis for UUV motion state forecasting. Experimental validation confirms the system’s capability for real-time resistance tracking and high-precision prediction, providing a robust foundation for autonomous navigation control and energy management. These results advance the development of specialized UUV digital twin systems and establish a robust foundation for their engineering applications. Full article

Exposure to nature has been associated with benefits to human well-being, commonly evaluated using standardized psychological assessments and, more recently, neuroimaging modalities such as Electroencephalography (EEG), functional Magnetic Resonance Imaging (fMRI), and functional Near-Infrared Spectroscopy (fNIRS). This systematic review and meta-analysis addresses the following questions. (1) How is the impact of nature on well-being studied using psychological and neuroimaging modalities and what does it reveal? (2) What are the challenges and opportunities for the deployment of wearable neuroimaging modalities to understand the impact of nature on the brain’s health and well-being? A search on PubMed, IEEE Xplore, and ClinicalTrials.gov (March 2024) identified 33 studies combining neuroimaging and psychological assessments during exposure to real, virtual or imagined natural environments. Studies were analyzed by tasks, populations, neuroimaging modality, psychological assessment, and methodological quality. Most studies were conducted in Asia (n = 23 or 70%). Healthy participants were the dominant target population (70%). In total, 61% of the studies were conducted in natural settings, while 39% used visual imagery. EEG was the most common modality (82%). STAI (n = 8) and POMS (n = 8) were the most common psychological assessments. Only seven studies included clinical populations. Two separate meta-analyses of nine studies with explicit experimental and control groups revealed a significant positive effect of nature exposure on psychological outcomes (Hedges’ g = 0.30; p = 0.0021), and a larger effect on neurophysiological outcomes (Hedges’ g = 0.43; p = 0.0004), both with moderate-to-high heterogeneity. Overall, exposure to nature was associated with reductions in negative emotions in clinical populations. In contrast, healthy populations showed a more balanced psychological response, with nature exposure being associated with both increases in positive emotions and reductions in negative emotions. Notably, 88% of the studies presented methodological weaknesses, highlighting key opportunities for future neuroengineering research on the neural and psychological effects of nature exposure. Full article

Background: Esophagectomy remains a technically demanding oncologic procedure with substantial morbidity, despite ongoing advances in minimally invasive and robotic techniques. Limitations in intraoperative visualization and anatomical recognition contribute to complications such as nerve injury and bleeding. Artificial intelligence (AI)-based intraoperative video analysis has emerged as a potential adjunct to enhance surgical perception and safety, but its application in esophagectomy has not been comprehensively reviewed. Methods: A systematic review was conducted in accordance with PRISMA guidelines. PubMed, Scopus, and Web of Science were searched without a lower date limit to identify eligible studies published up to January 2026, capturing early and contemporary applications of intraoperative AI in esophagectomy. Human studies involving any surgical approach were included. Data on the AI task, methodology, validation strategy, performance metrics, and reported clinical outcomes was extracted. Risk of bias was assessed using the ROBINS-I tool. Results: Six studies met the inclusion criteria, predominantly evaluating AI-driven analysis of intraoperative video during minimally invasive or robotic esophagectomy. Reported applications included real-time anatomical structure recognition, recurrent laryngeal nerve segmentation, detection of excessive nerve traction, instrument and event recognition, and surgical phase identification. Across studies, AI systems demonstrated performance comparable to expert surgeons for selected tasks and achieved real-time or near–real-time inference. One study reported earlier detection of excessive recurrent laryngeal nerve traction compared to conventional nerve integrity monitoring. However, most studies were retrospective, single-center, and feasibility-focused, with limited external validation and minimal assessment of patient-centered clinical outcomes. Conclusions: Artificial intelligence-based intraoperative analysis in esophagectomy is increasingly achievable and may enhance anatomical recognition, intraoperative risk detection, and procedural awareness. Nevertheless, current evidence remains preliminary, heterogeneous, and largely exploratory. Prospective, multicenter studies with standardized reporting and clinically meaningful outcome evaluation are required before routine implementation. Until such data is available, AI should be regarded as a complementary intraoperative tool rather than a standalone clinical decision-making system. Full article

Visual information should be presented clearly and effectively so that it is quickly and easily understood. The same principle applies to different types of maps and plans. This study explores the relationship between a map’s design and how users interact with it when searching for specific targets. Focusing on a digital tourist city map, we employed an eye-tracking technology to investigate how different cartographic designs (pictorial-based versus typography-based) influence visual search. As the need for visually appealing designs becomes an important part of the user experience, we further explored the observers’ perceptions of the maps’ visual appeal. The results show that the typography-based maps enabled a more effective visual search than the pictorial, as measured by search time, fixation count, and the number of fixations before locating the target. A greater amount of visual attention was directed towards the typography-based maps, as measured by completion time and several eye-tracking metrics during the observers’ evaluation of the maps’ visual appeal. Based on the results, this study highlights the practical implications of effective map design in enhancing users’ navigation and their visual engagement with cartographic data. Full article

Background/Objectives: Interstitial ectopic pregnancy is a rare and potentially life-threatening condition, accounting for 1–6% of ectopic pregnancies. Its location complicates diagnosis and management, and no standardized treatment guidelines exist. Fertility-preserving, minimally invasive approaches have been proposed as alternatives to medical therapy or radical surgery. This systematic review evaluates the safety and effectiveness of hysteroscopic treatment, focusing on uterine preservation and reproductive outcomes. Methods: This systematic review was conducted according to PRISMA guidelines and registered in PROSPERO (CRD420251249508). Web of Science, Scopus, and PubMed were searched from inception to January 2026. Eligible articles included case reports and case series describing interstitial pregnancies managed hysteroscopically, alone or combined with minimally invasive treatments, without medical therapy. Study quality was assessed using the JBI Checklist. Results: Eight studies comprising 21 patients were included. Mean gestational age at diagnosis was 55 days, and mean β-hCG level was 7981 IU/L (range 1440–32,000 IU/L). Hysteroscopic management was successful in 16 of 21 cases (76%). Five patients required rescue therapy. Reduced residual myometrial thickness was the main factor associated with treatment failure. Mean time to β-hCG normalization was 32 days. Conclusions: Hysteroscopic management is a safe and effective minimally invasive option for clinically stable patients with interstitial ectopic pregnancy. It allows direct visualization, targeted tissue removal, and preservation of uterine integrity and fertility, with limited morbidity. Ultrasound guidance is generally sufficient, reserving laparoscopy for high-risk cases. These findings support hysteroscopy as a fertility-preserving strategy, though larger prospective studies are needed to confirm long-term reproductive outcomes. Full article

Background and Objectives: Corneal allogeneic intrastromal ring segments (CAIRS) are designed to decrease and stabilize the extent of corneal ectasia in keratoconus patients. This systematic review and meta-analysis evaluate the effectiveness of different surgical techniques for CAIRS preparation and the adjunctive use of corneal cross-linking. Materials and Methods: Following the PRISMA statement and checklist, a comprehensive search was conducted in Embase, Medline, and the Cochrane Controlled Trials Register, through the use of a systematic search approach in accordance with the Cochrane Collaboration guidelines. Results: Eighteen studies, involving 567 eyes of 459 patients, met the inclusion criteria. At one month postoperatively, CAIRS implantation significantly improved uncorrected visual acuity (UCVA) (−0.45 logMAR, 95% CI [−0.59 to −0.31], p < 0.001) and best corrected visual acuity (BCVA) (−0.36 logMAR, 95% CI [−0.46 to −0.25], p < 0.001). These improvements remained significant after one year (UCVA: −0.39 logMAR, 95% CI [−0.48 to −0.30], p < 0.001; BCVA: −0.34 logMAR, 95% CI [−0.50 to −0.18], p < 0.001). Similarly, mean simulated keratometry (Kmean) decreased by −4.42 D (95% CI [−5.94 to −2.90], p < 0.001) and maximum keratometry (Kmax) by −3.88 D (95% CI [−6.71 to −1.05], p < 0.001) at one month, with sustained reductions at one year (−3.59 D, 95% CI [−4.35 to −2.84], p < 0.001 and −3.73 D, 95% CI [−4.91 to −2.55], p < 0.001). No significant differences in surgical outcome have been observed between the different surgical techniques. Conclusions: CAIRS implantation appears to be an effective treatment option for keratoconus, regardless of the technique used for segment preparation or the addition of corneal cross-linking. No approach demonstrated clear clinical superiority over others in the first year after surgery. Full article