Search Results (9,517)

Hyperspectral imaging, in combination with microscopy, can increase material discrimination compared to standard microscopy. We explored the potential of discriminating pellet microplastic materials using a hyperspectral short-wavelength infrared (SWIR) camera, providing 100 bands in the 1100–1650 nm range, in combination with reflection microscopy. The identification of the most relevant spectral bands helps to increase system cost efficiency. The use of fewer bands reduces memory and processing requirements, and can also steer the development of sustainable, cost-efficient sensors with fewer bands. For this purpose, we present a genetic algorithm to perform band relevance analysis and propose novel algorithm optimizations. The results show that a few spectral bands (between 6 and 9) are sufficient for accurate (>80%) pixel discrimination of all 22 types of microplastic waste, contributing to sustainable development goals (SDGs) such as SDG 6 (‘clean water and sanitation’) or SDG 9 (‘industry, innovation, and infrastructure’). In addition, we study the impact of the classifier method and the width of the spectral response on band selection, neither of which has been addressed in the current state-of-the-art. Finally, we propose a method to steer band selection towards a more balanced distribution of classification accuracy, increasing its applicability in multiclass applications. Full article

Postoperative edema is a nearly universal consequence of aesthetic surgery, yet its clinical implications and potential progression to lymphedema remain underexplored. This review examines the prevalence, pathophysiology, diagnostic criteria, and management strategies for edema and lymphedema following aesthetic procedures. A comprehensive search of PubMed, Embase, and Cochrane databases identified studies involving adult patients undergoing aesthetic surgeries with documented postoperative edema or lymphedema. The review found that while edema is expected postoperatively and is generally self-limiting, persistent or disproportionate swelling may indicate early lymphedema. Risk factors include extensive liposuction, body contouring, and procedures involving lymphatic disruption. Despite its significance, lymphedema remains underdiagnosed due to a lack of standardized diagnostic criteria and low clinical suspicion. Emerging imaging modalities, such as indocyanine green lymphography, enhance early detection, while conservative treatments, such as manual lymphatic drainage, compression, and physical therapy, remain first-line interventions. Increased awareness among surgeons and incorporation of lymphatic-preserving techniques are vital to reducing morbidity. This review underscores the importance of distinguishing transient edema from chronic lymphedema and calls for further research to establish evidence-based guidelines for diagnosis, prevention, and management of postoperative lymphedema in aesthetic surgery. Full article

Yin Yang 1 (YY1) is a multifunctional transcription factor implicated in gene regulation, cell proliferation, and survival. While its role in breast cancer (BC) has been explored, its prognostic significance remains controversial. In this study, we evaluated nuclear YY1 expression in 276 BC tissue samples using immunohistochemistry (IHC), tissue microarrays (TMAs), and digital pathology (DP). Nuclear staining was quantified using Aperio ImageScope software, focusing on tumor regions to avoid confounding from stromal or non-tumor tissues. This selective and standardized approach enabled precise quantification of YY1 expression. Our results show elevated median YY1 expression in tumor vs. normal matched tissues (p < 0.001). The optimal cutoff for medium-intensity nuclear YY1 expression in tumor areas for overall survival (OS) was established by a receiver operating characteristic (ROC) curve (AUC = 0.718, 95% CI: 0.587–0.849, p = 0.008). In contrast, ROC curves showed no prognostic impact (AUC and p-value) for YY1 quantification in whole spots (tumor + normal). As a categorical variable, high YY1 expression was correlated with more aggressive BC features, including tumor size > 3 cm (57.7% vs. 44.2% p = 0.037), the triple-negative breast cancer (TNBC) molecular subtype (27.3% vs. 13.9% p = 0.026), and advanced prognostic stage (III) (31.8% vs. 16.7% p = 0.003), while as a continuous variable, YY1 was associated with higher histological (p = 0.003) and nuclear grades (p = 0.022). High YY1 expression was significantly associated with a reduced OS of BC patients, as shown by Kaplan–Meier curves (HR = 2.227, p = 0.002). Since YY1 was significantly enriched in TNBC, we evaluated its prognostic resolution in this subgroup. But, probably due to the small number of patients within this subset, our results were not statistically significant (HR = 1.317, 95% CI: 0.510–3.405, p = 0.566). Next, we performed multivariate Cox regression, confirming YY1 as an independent prognostic factor for overall survival (HR = 1.927, 95% CI: 1.144–3.247, p = 0.014). In order to improve prognostic value, we constructed a mathematical model derived from the multivariate Cox regression results, including YYI, AJCC prognostic stage (STA), and axillary lymph node dissection (ALN), with the following equation: h(t) = h₀(t) × exp (0.695 × YY1 + 1.103 × STA − 0.503 × ALN). ROC analysis of this model showed a better AUC of 0.915, similar sensitivity (83.3%), and much higher specificity (92%). Bioinformatic analysis of public datasets supported these findings in BC, showing YY1 overexpression in multiple cancer types and its association with poor outcomes in BC. These results suggest that YY1 may play a role in tumor progression and serve as a valuable prognostic biomarker in BC. DP combined with molecular data enhanced biomarker accuracy, supporting clinical applications of YY1 in routine diagnostics and personalized therapy. Additionally, developing a combined score based on the modeling of multiple prognostic factors significantly enhanced survival predictions, representing a practical tool for risk stratification and the guidance of therapeutic decisions. Full article

The determination of uncertainty in porosity analysis based on X-ray computed tomography (XCT) images is currently the focus of research. This study aims to contribute to that by investigating the variation in porosity analysis resulting only from the segmentation and data analysis and by focusing on metal parts produced by different additive manufacturing processes, partially fabricated with intended porosity. Samples manufactured from aluminum, titanium alloy and nickel-chromium-based feedstock by liquid metal jetting (LMJ), laser-based powder bed fusion (PBF-LB) and directed energy deposition (DED) were scanned by XCT. The reconstructed volumes were distributed to four operators with different experience levels using Avizo, Dragonfly, Image J/Fiji, IPSDK Explorer, and VG Studio Max for porosity analysis. It was found that for all parts, the majority of operators chose a global manual threshold for image segmentation. Depending on the characteristics of the pores in the investigated samples, relative standard uncertainties up to 12% and 38% were observed for the LMJ and PBF-LB parts. For the part produced by DED, which showed the lowest overall porosity, relative standard uncertainties between 70% and 89% were observed for different image qualities; all were affected by the presence of artefacts investigated on purpose. Full article

To directly address the important issue of MRI geometric distortions in stereotactic radiosurgery (SRS) planning, we performed a phantom study of sequence acquisition optimization. This study analyzed, in particular, the effects of clinically relevant gadolinium (Gd) concentration as filling solution for the phantom, as well as phase encoding reversal direction and flip angle on distortion. We created a rigid geometric grid phantom with 840 fiducial markers for distortion quantification on a 3T MRI scanner. To choose the optimal filling solution, an anthropomorphic RANDO phantom was employed, and 1 mmol/L gadolinium was chosen due to clinical relevance. An automated Python-based software (version 3.7.1) was developed for efficient detection and matching of phantom inserts between MRI and CT scans. A series of MRI acquisition parameter optimizations were systematically evaluated. The standard SRS protocol exhibited the highest average distortion of 1.301 mm. Notably, reversing the phase-encoding direction to anterior–posterior (AP) reduced the mean distortion to 0.725 mm, a 44.27% decrease, while the maximum distortion was reduced by 15.65%. The AP phase sequence maintained acquisition time, SAR, SNR, and CNR within acceptable limits. Additional distortion reduction was achieved by increasing the flip angle from 12° to 18°. In this work, we succeeded in significantly reducing the mean distortion observed in phantom images. As the gadolinium concentration used in the phantom is clinically similar to the gadolinium concentration observed in patients undergoing MRI scans with contrast agents, the achieved distortion reduction is prospectively reproducible in patients. Full article

Asphalt crack segmentation is essential for preventive maintenance but is sensitive to noise, viewpoint, and illumination. This study evaluates a minimally invasive strategy that augments standard RGB input with an auxiliary fourth channel—a crack-probability map generated by a multi-scale ensemble of classifiers—and injects it into segmentation backbones. Field imagery from unmanned aerial vehicles and action cameras was used to train and compare U-Net, ENet, HRNet, and DeepLabV3+ under unified settings; the probability map was produced by an ensemble of lightweight convolutional neural networks (CNNs). Across models, the four-channel configuration improved performance over three-channel baselines; for DeepLabV3+, the Intersection over Union (IoU) increased by 6.41%. Transformer-based classifiers, despite strong accuracy, proved less effective and slower than lightweight CNNs for probability-map generation; the final ensemble processed images in approximately 0.63 s each. Integrating ensemble-derived probability maps yielded consistent gains, with the best four-channel CNNs surpassing YOLO11x-seg and Transformer baselines while remaining practical. This study presents a systematic evaluation showing that probability maps from classifier ensembles can serve as an auxiliary channel to improve segmentation of asphalt pavement cracks, providing a novel modular complement or alternative to attention mechanisms. The findings demonstrate a practical and effective strategy for enhancing automated pavement monitoring. Full article

Three-dimensional (3D) modeling and printing technologies are increasingly used in pediatric surgery, offering improved anatomical visualization, surgical planning, and personalized approaches to complex conditions. Compared to standard imaging, patient-specific 3D models—virtual or printed—provide a more intuitive spatial understanding of congenital anomalies, tumors, and vascular anomalies. This review compiles evidence from pediatric surgical fields including oncology, abdominal, and thoracic surgery, highlighting the clinical relevance of 3D applications. The technological workflow—from image segmentation to computer-aided design (CAD) modeling and multimaterial printing—is described, emphasizing accuracy, reproducibility, and integration into hospital systems. Several clinical cases are presented: neuroblastoma, cloacal malformation, conjoined twins, and two cases of congenital diaphragmatic hernia (one with congenital pulmonary airway malformation, CPAM). In each, 3D modeling enhanced anatomical clarity, increased surgeon confidence, and supported safer intraoperative decision-making. Models also improved communication with families and enabled effective multidisciplinary planning. Despite these advantages, challenges remain, such as production time, cost variability, and lack of standardization. Future directions include artificial intelligence-based automation, expanded use of virtual and mixed reality, and prospective validation studies in pediatric cohorts. Overall, 3D modeling represents a significant advance in pediatric precision surgery, with growing evidence supporting its safety, clinical utility, and educational value. Full article

There are two major problems that researchers must contend with when dealing with machine learning in the medical field. The first being the ever-changing nature of what is considered good practice, and the lack of available data to train. The change in opinion on what is considered good practice requires an ongoing effort to update the machine learning models. This requires a concept called continual learning, which requires that researchers must combat against the problem of a model forgetting previously learned information and the balancing of bigger classes and newer smaller classes. Usually, when new information is introduced, a model must be retrained, which threatens the previously gained knowledge. The training is then difficult because of the lack of data. However, when dealing with medications they can become irrelevant to use. When such things happen when dealing with the standard machine learning models, the entire model needs to be retrained in order to remove the specific medication. This causes even more difficulties, because patient data are heavily protected and there is the chance that the dataset will not be available for training again in the future. While most papers focus on medical imaging and diagnosis, medicine does not end with diagnosis. We have an elderly population that is growing and not enough doctors are are available. To have everyone be able to see specialists, or even a doctor, is becoming even harder. To combat these issues, we need to have models in use that we can update continuously to help bridge the gap of care. We propose a method that can be trained continuously in order to easily remove outdated medications. Full article

Complex Regional Pain Syndrome (CRPS) is a chronic pain disorder with several sensory, autonomic, motor, and trophic symptoms. Diagnosis is based on clinical criteria like the Budapest Criteria, but there are limitations to those criteria, especially for pediatric cases and different clinical presentations. Technical testing—including laboratory tests, electrophysiological studies, sensory and autonomic function tests, and more advanced imaging—provides supportive, but not definitive, evidence. Biomarkers such as certain microRNAs, inflammatory mediators, and autoantibodies may offer the potential for improved diagnostic accuracy, although they have not yet been adequately validated. New imaging techniques, including ultrasound elastography and neuroimaging, have identified both peripheral and central pathophysiological changes in CRPS. We can improve our diagnosis of CRPS by integrating standardized clinical criteria with technical evaluations and biomarker improvements; this should serve to make diagnosis earlier, reduce diagnostic delay, and promote individualized treatment. Full article

The enzymatic coagulation of milk, crucial in cheese production, entails the hydrolysis of κ-casein and subsequent micelle aggregation. Conventional assessment standards, such as the Berridge method, depend on visual inspection and are susceptible to operator bias. Recent methods for the identification of milk-clotting time rely on optical, ultrasonic, and image-based technologies. In the present work, the composition of milk was evaluated through standard methods from ISO and AOAC. Milk coagulation time (MCT) was measured through viscosimetry, Berridge’s operator-driven technique, and a machine learning approach employing computer vision. Coagulation was additionally observed using the Optigraph, which measures micellar aggregation through near-infrared light attenuation for immediate analysis. Sheep milk samples were analysed for their composition and coagulation characteristics. Coagulation times, assessed via Berridge (BOB), demonstrated high correlation (R² = 0.9888) with viscosimetry (Visc) and machine learning (ML). Increased levels of protein and casein were linked to extended MCT, whereas lower pH levels sped up coagulation. The calcium content did not have a notable impact. Optigraph assessments validated variations in firmness and aggregation rate. Principal Component Analysis (PCA) identified significant correlations between total solids, casein, and MCT techniques. Estimates from ML-based MCT closely align with those from operator-based methods, confirming its dependability. This research emphasises ML as a powerful, automated method for evaluating milk coagulation, presenting a compelling substitute for conventional approaches. Full article

Objectives: Among the spectrum of spinal injuries, Spinal Cord Injury Without Radiographic Abnormality (SCIWORA) occupies a unique and challenging position. SCIWORA presents diagnostic and therapeutic challenges due to its broad clinical and radiological heterogeneity. While most children recover favorably with conservative treatment, a subset may require surgery based on imaging findings. The findings underscore the need for standardized diagnostic criteria, MRI-based classification systems, and evidence-based treatment algorithms to improve consistency in care and long-term neurological outcomes. Methods: A systematic search of PubMed, Cochrane, Scopus, and Embase databases was performed through June 2025 following PRISMA guidelines. Inclusion criteria encompassed studies of pediatric SCIWORA (age < 18 years) reporting demographics, clinical and radiological features, management, and outcomes. Results: Sixty studies encompassing a total of 848 pediatric patients were included. The mean patient age was 9.33 years (±2.52), with a slight male predominance. The most common trauma mechanisms were road traffic accidents (40.3%), sports injuries (22%), and falls (18.8%). MRI findings were available in 399 cases: 46% had intraneural lesions (Type IIb), 39% showed no abnormality on MRI (Type I, or “real SCIWORA”), 9% had combined lesions (Type IIc), and 6% had extraneural abnormalities (Type IIa). Neurological severity at presentation was primarily ASIA Grade A (46.25%), but follow-up data showed substantial improvement, with ASIA E (normal function) increasing to 49.78%. Overall, 66.2% of patients experienced neurological improvement, while 33.8% remained stable. Conservative treatment was employed in 95.41% of cases. Only 4.59% underwent surgery, which was typically reserved for MRI-positive lesions demonstrating spinal instability or compression. Conclusions: Pediatric SCIWORA remains an uncommon but potentially devastating injury, with an outcome highly dependent on MRI findings and initial neurological status. This systematic review aims to clarify the contemporary understanding of pediatric SCIWORA, delineating “real” SCIWORA from other SCIWORA-like entities, and synthesizing the latest evidence regarding epidemiology, mechanisms, clinical presentation, MRI findings, and management in children. Full article

Background: The deep head of the masseter muscle (DHMM) is an underrecognized anatomical structure, frequently absent from standard anatomical references and often overlooked in maxillofacial surgical planning. Its morphological variability, spatial complexity, and relationship with neurovascular structures carry significant implications for imaging interpretation, diagnosis, and surgical outcomes. Objective: The objective of this paper is to synthesize current anatomical, embryological, and radiological knowledge on the DHMM, and to introduce a refined morphological classification with direct clinical and surgical relevance. Methods: A comprehensive literature review was performed, incorporating cadaveric dissections, radiological imaging (MRI, DTI, HRUS, CT), and clinical case reports. Emphasis was placed on anatomical variability, radiological detectability, and surgical accessibility. Based on these findings, a three-type classification with clinically relevant subtypes was formulated and correlated with imaging features and procedural risk. Results: The DHMM can be categorized into three principal types: Type I—classical form with fascial separation; Type II—fused with the medial pterygoid; Type III—segmented into two muscular bellies. Each type may present a subtype b, characterized by neurovascular penetration, which significantly increases surgical risk and alters procedural strategy. MRI and high-resolution ultrasonography were identified as the most reliable modalities for in vivo differentiation, with HRUS providing additional value for dynamic and volumetric assessment. Conclusions: Recognition of DHMM morphology, including high-risk neurovascular subtypes, is essential for accurate diagnosis, surgical planning, and prevention of complications. The proposed classification offers a reproducible framework for imaging standardization, surgical risk stratification, and integration into anatomical atlases and clinical guidelines. Full article

We developed an artificial intelligence (AI)-based size detection system by combining image recognition and weight analysis to address inconsistent sizing in manually processed sashimi products. Using a custom imaging setup and YOLOv11_obb, the system detects sashimi pieces and accounts for orientation variations. It measures their size based on their area and weight, ensuring compliance with quality standards. This system reduces human error, identifies out-of-spec products at an early stage, and prevents defective shipments. The developed system demonstrated high detection accuracy, although its classification precision needs to be enhanced. The system is a promising tool for enhancing efficiency and quality control in seafood processing environments. Full article

Extreme ultraviolet (EUV) photomask inspection is a critical step in semiconductor manufacturing, requiring high-resolution, high-throughput solutions to detect nanometer-scale defects. Traditional actinic imaging systems relying on complex optics have a high cost of ownership and require frequent upgrades. An alternative is lensless imaging techniques based on ptychography, which offer high-fidelity reconstruction but suffer from slow throughput and high data demands. In particular, the ptychographic standard solver—the iterative Difference Map (DifMap) algorithm—requires many measurements and iterations to converge. We propose Ptycho-LDM, a hybrid framework integrating DifMap with a conditional Latent Diffusion Model for rapid and accurate phase retrieval. Ptycho-LDM alleviates high data acquisition demand by leveraging data-driven priors while offering improved computational efficiency. Our method performs coarse object retrieval using a resource-constrained reconstruction from DifMap and refines the result using a learned prior over photomask patterns. This prior enables high-fidelity reconstructions even in measurement-limited regimes where DifMap alone fails to converge. Experiments on actinic patterned mask inspection (APMI) show that Ptycho-LDM recovers fine structure and defect details with far fewer probe positions, surpassing the DifMap in accuracy and speed. Furthermore, evaluations on both noisy synthetic data and real APMI measurements confirm the robustness and effectiveness of Ptycho-LDM across practical scenarios. By combining generative modeling with physics-based constraints, Ptycho-LDM offers a promising scalable, high-throughput solution for next-generation photomask inspection. Full article

Background: Unilateral lung agenesis (ULA) is a rare congenital anomaly characterized by the complete absence of one lung, often accompanied by cardiovascular, skeletal, or gastrointestinal malformations. Despite its clinical significance, evidence of prevalence, anatomical variants, and outcomes remain fragmented. This systematic review aimed to synthesize existing data on ULA’s prevalence, anatomical classifications, diagnostic approaches, and clinical implications. Methods: Following PRISMA 2020 guidelines, five databases (MEDLINE, Web of Science, CINAHL, Scopus, and EMBASE) were searched from inception to January 2024. Inclusion criteria encompassed case reports, case series, and observational studies on ULA in humans. Risk of bias was assessed using the Joanna Briggs Institute (JBI) checklist. Narrative synthesis was performed due to methodological heterogeneity. Results: Thirty-two studies (137 participants) were included. Right-sided ULA predominated (58%), with poorer prognoses due to mediastinal distortion. Cardiovascular anomalies (40%) were the most common comorbidity. Diagnostic modalities included chest radiography (85%), CT (70%), and bronchoscopy (25%). Schneider-Boyden scale was used to classify the included studies. Risk of bias assessment revealed 65% of studies as low risk, 28% as moderate, and 7% as high risk. Conclusions: ULA necessitates multidisciplinary management, particularly in cases with associated anomalies. Left-sided ULA correlates with better outcomes, emphasizing the role of early imaging. Limitations include reliance on case reports and inconsistent reporting of anatomical variants. Future research should adopt standardized classifications and longitudinal designs to improve evidence quality. Open science framework (OSF): 10.17605/OSF.IO/XVQSP. Full article