Radiographic Research Articles

Technique selection and technical developments for 2D dual-energy subtraction angiography on an interventional C-arm.

Dual-energy (DE) x-ray image acquisition has the potential to provide material-specific angiographic images in the interventional suite. This approach can be implemented with novel detector technologies, such as dual-layer and photon-counting detectors. Alternatively, DE imaging can be implemented on existing systems using fast kV-switching. Currently, there are no commercially available DE options for interventional platforms. This study reports on the development of a prototype fast kV-switching DE subtraction angiography system. In contrast to alternative approaches to DE imaging in the interventional suite, this prototype uses a clinically available interventional C-arm equipped with special x-ray tube control software. An automatic exposure control algorithm and technical features needed for such a system in the interventional setting are developed and validated in phantom studies. Fast kV-switching was implemented on an interventional C-arm platform using software that enables frame-by-frame specification of x-ray tube techniques (e.g., tube voltage/kV, pulse width/ms, tube current/mA). A real-time image display was developed on a portable workstation to display DE subtraction images in real-time (nominal 15 frame/s). An empirical CNR-driven automatic exposure control (AEC) algorithm was created to guide DE tube technique selection (kV pair, ms pair, mA). The AEC model contained a look-up table which related DE tube technique parameters and air kerma to iodine CNR, which was measured in acrylic phantom models containing an iodine-equivalent reference object. For a given iodine CNR request, the AEC algorithm estimated patient thickness and then selected the DE tube technique expected to deliver the requested CNR at the minimum air kerma. The AEC algorithm was developed for DE imaging performed without and with the application of anti-correlated noise reduction (ACNR). Validation of the AEC model was performed by comparing the AEC-predicted iodine CNR values with directly measured values in a separate phantom study. Both dose efficiency (CNR2/kerma) and maximum achievable iodine CNR (within tube technique constraints) were quantified. Finally, improvements in DE iodine CNR were quantified using a novel variant to the ACNR approach, which used machine-learning image denoising (ACNR-ML). The prototype system provided a continuous display of DE subtraction images. For standard DE imaging, the AEC-predicted iodine CNR values agreed with directly measured values to within 3.5%±1.6% (mean±standard deviation). When ACNR was applied, predicted iodine CNR agreed with measurement to within 2.1%±3.3%. AEC-generated DE techniques were typically (low/high energy): 63/125kV, 10/3.2ms, with varying mA values. When ACNR was applied, dose efficiency was increased by a factor of 9.37±2.08 and maximum CNR was increased by a factor of 3.29±0.21 relative to DE without denoising. Application of ACNR-ML yielded a greater increase in both the dose efficiency (16.11±2.99) and maximum CNR (4.46±0.31) compared to DE without denoising. A prototype DE subtraction angiography system using fast kV-switching was implemented on a clinically available interventional C-arm platform without modification of system hardware. The technical features presented in this work include a real-time image display, noise-reduction strategies, and a CNR-driven AEC algorithm. This prototype system demonstrates the feasibility of 2D dual-energy imaging for image-guided interventions.

Stress shielding influences shoulder function after reverse shoulder arthroplasty using a short stem at minimum 2 years follow-up and can be predicted using a preoperative planning software: A retrospective cohort study

Background The aim of the study was to assess if 3D CT-scan-based planification of distal filling ratio (DFR) is accurate when compared to postoperative DFR calculated on plain X-rays. A secondary aim was to investigate if an association between clinical outcomes and the degree of stress shielding (SS) exists. Methods Fifty patients with short-stem reverse shoulder arthroplasties, preoperative CT scans, and a minimum 24-month radiographic follow-up were included in the study. At 24 months follow-up, all patients were evaluated by assessing the postoperative filling ratios, the 3D DFRs, the simple shoulder test, Constant-Murley score, and visual analogue scale through a prospectively data collection and statistically analyzed. Results A correlation between the 3D DFR and SS onset (rs 0.54; P < 0.001), and between postoperative DFR and SS (rs 0.71; P < 0.001), was found. The 3D DFR and the postoperative DFR were correlated (rs 0.89; P < 0.0001). SS negatively affects the postoperative range of motion, decreasing the forward elevation of the shoulder. Conclusion The calculation of DFR based on 3D CT planning is a good predictor of humeral SS after short-stem RTAs. The presence of SS decreases clinical outcomes by lowering the anterior elevation of the shoulder. Level of evidence Case series.

Study of the TOFPET2c ASIC in time-of-flight detection of x-rays for scatter rejection in medical imaging applications

Objective.Integrating time-of-flight (ToF) measurements in radiography and computed tomography (CT) enables an approach for scatter rejection in imaging systems that eliminates the need for anti-scatter grids, potentially increasing system sensitivity and image quality. However, present hardware dedicated to the time-correlated measurement of x-rays is limited to a single pixel physically too large for the desired spatial resolution. A switch to highly integrated electronics and detectors is needed to progress towards detector arrays capable of acquiring images, while offering a timing resolution below 300 ps FWHM to achieve scatter rejection comparable to current anti-scatter grids.Approach.Using off-the-shelf scintillators, photodetectors and readouts designed for ToF positron emission tomography (PET) provides a preliminary evaluation of available highly integrated readout systems supporting detector arrays for ToF scatter rejection. The TOFPET2c ASIC from PETSys offers an established development platform necessary for fast and reliable results, with no known limitation regarding time-correlated detection of medical imaging x-rays (20-140 keV).Main results.Reliable photon detection down to 31 keV was achieved, reaching energy resolutions from 23% to 92% FWHM throughout the desired energy range. Optimal detector timing resolution (DTR) from 250 ps FWHM at 130 keV to 678 ps FWHM at 30 keV was reached. Strong time walk effects were observed, showing a time shift of 642 ps up to 1740 ps between events spanning the energies used in x-ray medical imaging.Significance.The TOFPET2c ASIC has shown its potential for ToF scatter rejection, but meets the time resolution requirement of 300 ps FWHM only for limited energies (110-140 keV). This significant timing degradation observed at lower energies limits the use of the TOFPET2c ASIC for ToF scatter rejection, but offers significant advancements regarding the understanding of the phenomenon arising from the time-correlated detection of medical imaging x-rays.

Recent Advances on Organic Scintillators with High Exciton Utilization Efficiency for X-ray Scintillation and Imaging.

Organic scintillators have rapidly emerged in recent years for X-ray scintillation and imaging, benefiting from their inherent advantages of abundant raw materials, low-temperature processing, high mechanical flexibility, and easy of large-scale fabrication. However, conventional organic scintillators suffer from weak X-ray absorption and inefficient exciton utilization, limiting their commercial viability. To overcome these challenges, new-generation organic scintillators have recently been developed with innovative emission mechanisms to ensure exciton utilization efficiency and the incorporation of heavy atoms to improve X-ray absorption. In recent years, these advancements have led to remarkable progress in high-performance X-ray scintillation and imaging. Here, we present a concept article on new-generation organic scintillators with high exciton utilization efficiency, focusing on molecular design, emission mechanisms, scintillation performance, and X-ray imaging applications. We also discuss future development trends in organic X-ray scintillators.

Increased risk of mortality in lung transplant patients with fragility fractures.

The prevalence of osteoporosis among lung transplant candidates has been estimated at 31% to 46%, and significant bone loss occurs after lung transplantation, predominantly in the first year, with increased risk of incident fractures. This study aimed to evaluate the prevalence of fragility fractures in a population of lung transplant recipients and the associated risk factors as well as mortality after a fragility fracture. This was a cross-sectional monocentric study that included patients with lung transplantation occurring < 10years and > 1year who were undergoing lung transplantation monitoring. All patients underwent bone mineral density evaluation by dual-energy X-ray absorptiometry and radiography to establish the presence of vertebral fractures. Mortality was assessed 2years after the last inclusion. We included 131 patients (82 men, 62.6%), with mean age 56.8 ± 10.8years. The mean time from lung transplantation to inclusion was 3.5 ± 3.5years. Overall, 35 (26.5%) patients had a diagnosis of fractures after transplantation; 67 fractures were confirmed (average of 2 per patient), including 48 (71.6%) vertebral fractures. Odds of low bone mineral density at the femoral neck, total hip and spine was associated with fracture: odds ratio 0.007 [0.0002-0.3], 0.001 [0.0002-0.05], and 0.03 [0.001-0.6], respectively. Fracture post transplantation was significantly associated with death (hazard ratio 2.32 [1.01-5.33]). This study confirmed a high prevalence of vertebral fracture in lung transplant patients. Fracture after lung transplant was associated with mortality. Bone fragility needs more attention to reduce the fracture risk.

Rib suppression-based radiomics for diagnosis of neonatal respiratory distress syndrome in chest X-rays

This study aims to refine a radiomics-based diagnostic approach for detecting neonatal respiratory distress syndrome (NRDS) and examines the influence of rib suppression on the diagnostic precision of radiomics models using neonatal chest X-ray (CXR) images. A total of 138 CXR images were collected in this study. The data was partitioned into training and validation subsets based on chronological order. We applied rib suppression to the CXR images and extracted and analyzed radiomic features from lung regions both before and after rib suppression. This approach was designed to identify NRDS, develop radiomics models, and assess the impact of rib suppression on model performance. To establish these radiomics models, six machine learning models were utilized in the study. The performance was evaluated using the area under the receiver operating characteristic curve (AUC). On the validation set, the models demonstrated significant improvements after rib suppression. Specifically, the Gradient Boosting Machine (GBM) achieved an AUC of 0.781 post-suppression compared to 0.556 pre-suppression. Notably, Linear Discriminant Analysis (LDA) and Logistic Regression (LR) performed particularly well when combining features from both scenarios, achieving AUCs of 0.762 and 0.756. The results indicate the feasibility of developing radiomics models for diagnosing NRDS and highlight the enhancement in model performance due to rib suppression. This study provides a promising new method for the imaging diagnosis and prognosis evaluation of neonatal respiratory distress syndrome, showcasing the potential of radiomics in pediatric imaging.

Deep learning in gonarthrosis classification: a comparative study of model architectures and single vs. multi-model methods

PurposeThis study aims to classify Kellgren–Lawrence (KL) osteoarthritis stages using knee anteroposterior X-ray images by comparing two deep learning (DL) methodologies: a traditional single-model approach and a proposed multi-model approach. We addressed three core research questions in this study: (1) How effective are single-model and multi-model deep learning approaches in classifying KL stages? (2) How do seven convolutional neural network (CNN) architectures perform across four distinct deep learning tasks? (3) What is the impact of CLAHE (Contrast Limited Adaptive Histogram Equalization) on classification performance?ApproachWe created a dataset of 14,607 annotated knee AP X-rays from three hospitals. The knee joint region was isolated using a YOLOv5 object detection model. The multi-model approach utilized three DL models: one for osteophyte detection, another for joint space narrowing analysis, and a third to combine these outputs with demographic and image data for KL classification. The single-model approach directly classified KL stages as a benchmark. Seven CNN architectures (NfNet-F0/F1, EfficientNet-B0/B3, Inception-ResNet-v2, VGG16) were trained with and without CLAHE augmentation.ResultsThe single-model approach achieved an F1-score of 0.763 and accuracy of 0.767, outperforming the multi-model strategy, which scored 0.736 and 0.740. Different models performed best across tasks, underscoring the need for task-specific architecture selection. CLAHE negatively impacted most models, with only one showing a marginal improvement of 0.3%.ConclusionThe single-model approach was more effective for KL grading, surpassing metrics in existing literature. These findings emphasize the importance of task-specific architectures and preprocessing. Future studies should explore ensemble modeling, advanced augmentations, and clinical validation to enhance applicability.

New insights with XRISM and Cloudy: A novel column density diagnostic

We present a simple yet powerful column density diagnostic for plasmas enabled by X-ray microcalorimeter observations. With the recent developments of the spectral simulation code inspired by the high spectral resolution of the X-Ray Imaging and Spectroscopy Mission (XRISM) and the Advanced Telescope for High Energy Astrophysics (Athena), we make predictions for the intensity ratio of the resolved fine-structure lines Lyα_1 and Lyα_2 of H-like ions. We show that this ratio can be observationally constrained and used as a plasma column density indicator. We demonstrate this with an XRISM observation of the high-mass X-ray binary Centaurus X-3. This diagnostic is useful for a wide range of X-ray emitting plasmas that are either collisionally or radiatively ionized.

Effects of X-ray-based diagnosis and explanation of knee osteoarthritis on patient beliefs about osteoarthritis management: A randomised clinical trial.

Although X-rays are not recommended for routine diagnosis of osteoarthritis (OA), clinicians and patients often use or expect X-rays. We evaluated whether: (i) a radiographic diagnosis and explanation of knee OA influences patient beliefs about management, compared to a clinical diagnosis and explanation that does not involve X-rays; and (ii) showing the patient their X-ray images when explaining radiographic report findings influences beliefs, compared to not showing X-ray images. This was a 3-arm randomised controlled trial conducted between May 23, 2024 and May 28, 2024 as a single exposure (no follow-up) online survey. A total of 617 people aged ≥45 years, with and without chronic knee pain, were recruited from the Australian-wide community. Participants were presented with a hypothetical scenario where their knee was painful for 6 months and they had made an appointment with a general practitioner (primary care physician). Participants were randomly allocated to one of 3 groups where they watched a 2-min video of the general practitioner providing them with either: (i) clinical explanation of knee OA (no X-rays); (ii) radiographic explanation (not showing X-ray images); or (iii) radiographic explanation (showing X-ray images). Primary comparisons were: (i) clinical explanation (no X-rays) versus radiographic explanation (showing X-ray images); and (ii) radiographic explanation (not showing X-ray images) versus radiographic explanation (showing X-ray images). Primary outcomes were perceived (i) necessity of joint replacement surgery; and (ii) helpfulness of exercise and physical activity, both measured on 11-point numeric rating scales (NRS) ranging 0 to 10. Compared to clinical explanation (no X-rays), those who received radiographic explanation (showing X-ray images) believed surgery was more necessary (mean 3.3 [standard deviation: 2.7] versus 4.5 [2.7], respectively; mean difference 1.1 [Bonferroni-adjusted 95% confidence interval: 0.5, 1.8]), but there were no differences in beliefs about the helpfulness of exercise and physical activity (mean 7.9 [standard deviation: 1.9] versus 7.5 [2.2], respectively; mean difference -0.4 [Bonferroni-adjusted 95% confidence interval: -0.9, 0.1]). There were no differences in beliefs between radiographic explanation with and without showing X-ray images (for beliefs about necessity of surgery: mean 4.5 [standard deviation: 2.7] versus 3.9 [2.6], respectively; mean difference 0.5 [Bonferroni-adjusted 95% confidence interval: -0.1, 1.2]; for beliefs about helpfulness of exercise and physical activity: mean 7.5 [standard deviation: 2.2] versus 7.7 [2.0], respectively; mean difference -0.2 [Bonferroni-adjusted 95% confidence interval: -0.7, 0.3]). Limitations of our study included the fact that participants were responding to a hypothetical scenario, and so findings may not necessarily translate to real-world clinical situations, and that it is unclear whether effects would impact subsequent OA management behaviours. An X-ray-based diagnosis and explanation of knee OA may have potentially undesirable effects on people's beliefs about management. ACTRN12624000622505.

MeerKAT discovery of gigahertz radio emission extending from Abell 3017 towards Abell 3016

Cosmic filaments are vast, faint structures that connect galaxy clusters, often challenging to detect directly. However, filaments between pre-merger cluster pairs become more visible due to gas heating and compression while the clusters are approaching, enabling detection in X-ray and radio wavelengths. The clusters Abell 3017 and Abell 3016 are located within such a large-scale filament. A prominent X-ray bridge has been detected connecting the two clusters and a potential galaxy group between them. The aim of this work is to investigate the existence of a radio bridge in the filament between Abell 3017 and Abell 3016, to explore other diffuse radio structures within this system, and to investigate the origins of these diffuse radio emission. We analysed MeerKAT L-band data to study the morphology and spectra of the diffuse radio structures in Abell 3016-Abell 3017. X-ray imaging and spectral analysis were carried out with archival and data. Additionally, correlations between radio (I_R) and X-ray surface brightness (I_X) were generated to explore the connections between thermal and non-thermal components in the diffuse radio emission. We detected a faint radio bridge with an average surface brightness of ∼ 0.1 μ Jy at 1280 MHz using MeerKAT. It connects Abell 3017 with a potential galaxy group and extends towards Abell 3016, aligning with the X-ray bridge. A high X-ray temperature of $7.09 ± 0.54$ keV detected in the bridge region suggests an interaction between Abell 3017 and the group. In Abell 3017, we identified two distinct components of diffuse radio emission: a radio mini-halo and an outer radio halo with a northern extension (N-extension hereafter). The radio surface brightness profile of Abell 3017 shows a steep inner component consistent with other mini-halos, and a faint outer component likely linked to an infalling subcluster. The I_ R -I_ X diagram indicates superlinear and sub-linear correlations for the mini-halo and N-extension, respectively. We proposed three plausible explanations for the origin of the radio bridge: (1) it is an inter-cluster radio bridge connecting the two clusters in a filament, enhanced by interactions with the embedded galaxy group; (2) it results from an interaction between Abell 3017 and the galaxy group after their primary apocentric passage, with the group currently falling back towards Abell 3017; (3) it is a cluster radio relic associated with a merger shock, appearing as a bridge due to its face-on orientation. In Abell 3017, the mini-halo is likely powered by gas sloshing, resulting from an offset merger that left the cluster's cool core intact. Turbulence from an infalling subcluster likely contributes to the formation of the outer radio halo.

Using Backdoor Attacks to Find Areas of Interest in Images

&lt;p dir="ltr"&gt;&lt;span&gt;The power of neural networks increases in popularity more and more everyday. However, as for any powerful and popular tool, the security is hard to gain, here it is also the case. In recent years, backdoor attacks have become more and more popular through malicious parties, being risky for both organisations and people. In this paper we discuss the main methods of prevention against this type of attack. We also provide an experiment, with the help of which we tried to see what part of an image influences its classification. Therefore, using an algorithm for identifying backdoor attacks we made an experiment intended to find the interest zone in X-ray images.&lt;/span&gt;&lt;/p&gt;&lt;div&gt;&lt;span&gt;&lt;br /&gt;&lt;/span&gt;&lt;/div&gt;

A comparative analysis of the binary and multiclass classified chest X-ray images of pneumonia and COVID-19 with ML and DL models

Abstract Background The highly infectious coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2, the seventh coronavirus. It is the longest pandemic in recorded history worldwide. Many countries are still reporting COVID-19 cases even in the fifth year of its emergence. Objective The performance of various machine learning (ML) and deep learning (DL) models was studied for image-based classification of the lungs infected with COVID-19, pneumonia (viral and bacterial), and normal cases from the chest X-rays (CXRs). Methods The K-nearest neighbour and logistics regression as the two ML models, and Visual Geometry Group-19, Vision transformer, and ConvMixer as the three DL models were included in the investigation to compare the brevity of the detection and classification of the cases. Results Among the investigated models, ConvMixer returned the best result in terms of accuracy, recall, precision, F1-score and area under the curve for both binary as well as multiclass classification. The pre-trained ConvMixer model outperformed the other four models in classifying. As per the performance observations, there was 97.1% accuracy for normal and COVID-19 + pneumonia-infected lungs, 98% accuracy for normal and COVID-19 infected lungs, 82% accuracy for normal + bacterial + viral infected lungs, and 98% accuracy for normal + pneumonia infected lungs. The DL models performed better than the ML models for binary and multiclass classification. The performance of these studied models was tried on other CXR image databases. Conclusion The suggested network effectively detected COVID-19 and different types of pneumonia by using CXR imagery. This could help medical sciences for timely and accurate diagnoses of the cases through bioimaging technology and the use of high-end bioinformatics tools.

M-KANUNet: enhanced defect segmentation in X-ray images of copper pipe welds via multi-scale representation and Kolmogorov–Arnold Networks

M-KANUNet: enhanced defect segmentation in X-ray images of copper pipe welds via multi-scale representation and Kolmogorov–Arnold Networks

Who requires dental treatment under general anesthesia due to pain and severe dental anxiety? Findings from panoramic X-ray images and anamnesis.

The aims were to describe the dental status and mental and somatic health profile of patients with severe dental anxiety requiring dental treatment under general anesthesia (GA) in Rogaland County, Norway (2018-2021), and to compare patients with and without reported abuse history. Dental status was assessed by panoramic X-rays. General health variables were collected from patient records. Statistical comparisons of patients with and without abuse experience by tests of association (significance level p < 0.05). Results: 38 women and 18 men (mean ± standard deviation [SD]: 37.9 ± 9.2 years) were included; 27 reported abuse experience. Dental assessment showed 4.6 ± 3.8 missing teeth, 4.8 ± 3.0 root remnants, 5.8 ± 3.7 teeth with caries and 2.6 ± 1.9 teeth with apical periodontitis, among patients with ≥1 of the respective findings. 57.1% used analgesics due to dental pain. 55.4% had comorbid psychiatric conditions; 35.7% used psychopharmaceuticals. There were no statistical differences in dental variables but the abuse experience group had higher frequencies of comorbid psychiatric disorders (p = 0.01) and mixed somatic conditions (p = 0.03). Patients with severe dental anxiety requiring dental treatment under GA have complex health problems. They need access to treatment under GA,as treatment of serious odontogenic conditions is otherwise unmanageable.

A Clinical Investigation of Hip Implant Migration and Wear

Abstract The prediction of survival rate probability for hip implants, based on clinical data acquired before and after surgery, incorporating patient-specific parameters, represents a pivotal advancement in enabling more precise risk assessment for potential complications, such as aseptic loosening and implant wear-related inflammation, on an individualized basis. This critical step marks a substantial progression toward the realization of digitized and personalized medicine. The objective of this study was to establish prediction aiding correlations between implant wear and migration data, derived from X-ray imaging of 149 patients diagnosed with hip arthritis, and the performance of hip implants. The patients underwent cementless hip replacement surgery, receiving implants consisting of ultra-high-molecular-weight polyethylene (UHMWPE) paired with titanium-aluminum-vanadium (Ti6Al4V) wedges. Over the course of a median follow-up period of 4 years, X-ray assessments were conducted to monitor the migration of the femoral head and acetabular components using Ein Bild Röntgen Analyse (EBRA). Clinical findings revealed a linear relationship between average migration and wear. Notably, it was observed that increased cup migration corresponded proportionally to greater wear values. Furthermore, in-depth analysis revealed significant distinctions based on gender and age. Specifically, the established relationship can confidently serve as a reliable predictive model for the behavior of hip implants in female subjects and individuals aged 50–60 years.

X-ray polarization from accretion disk winds

X-ray polarimetry is a fine tool for probing the accretion geometry and physical processes operating in the proximity of compact objects, such as black holes and neutron stars. Recent discoveries made by the Imaging X-ray Polarimetry Explorer question our understanding of the accretion picture. The observed high levels of X-ray polarization in X-ray binaries and active galactic nuclei are challenging to achieve within the conventional scenarios. We investigate the possibility that a fraction (or even all) of the observed polarized signal arises from scattering in the equatorial accretion disk winds, the slow and extended outflows, which are often detected in these systems via spectroscopic means. We find that wind scattering can reproduce the levels of polarization that are observed in these sources.

Pharmacological Treatment of Medication-Related Osteonecrosis of the Jaw (MRONJ) with Pentoxifylline and Tocopherol

Background: This study aimed to evaluate the efficacy of pentoxifylline and tocopherol therapy in patients with medication-related osteonecrosis of the jaw (MRONJ). Methods: During this study, 43 patients participated, including 21 women and 22 men with a mean age of 66.8 years, who showed 63 areas of osteitis altogether. The diagnosis was made based on X-ray imaging and histopathological findings. All the subjects received pharmacological treatment with pentoxifylline 400 mg and tocopherol 400 IU. The study scheme consisted of initial observation and two follow-up examinations every 5–6 months. MRONJ severity, peripheral blood parameters, and CRP levels were evaluated. The obtained results were statistically analyzed. Results: Complete remission occurred in 46% of the subjects, with a higher rate among those taking bisphosphonates intravenously compared to oral administration. The efficacy of pentoxifylline and tocopherol treatment was not influenced by gender or lesion location. Moreover, the worst response to treatment was observed in the group with the highest disease stage, as determined in the initial study. Conclusions: Pentoxifylline and tocopherol therapy in MRONJ was effective in patients taking oral and intravenous bisphosphonates, in patients with osteoporosis, and undergoing oncological treatment. This treatment approach allows surgery to be avoided or significantly reduced. The good response to pharmacotherapy observed in patients with early stages of MRONJ shows an urgent need to monitor the patients treated with bisphosphonates carefully to diagnose MRONJ at the initial phase.

Human identification through panoramic dental radiographs: a novel matching approach

Abstract Biometric person identification systems identify individuals using personal characteristics such as fingerprints, eyes or facial recognition. However, in some critical situations, such as fires, serious traffic accidents, earthquakes or serious injuries, these features can become ineffective. In certain situations, dental characteristics may become the only valid biometric feature for identification. In these cases, forensic dentists work by examining dental structures to establish a person's identity. Currently, studies are being carried out to develop an automated recognition system based on computer vision to assist forensic dentists. However, due to the difficulties in processing panoramic X-ray images and challenges in accessing the data, person matching studies with these images are limited. This paper presents a novel method for matching people based on panoramic X-ray images. Dental person recognition studies can proceed either by investigating the similarity of teeth or by examining the similarity of jaws. In this work, a new approach that uses keypoint descriptors to perform tooth-jaw matching is proposed. This approach offers a high match rate by allowing to search for dental features on a jaw-by-jaw basis and requires less computational complexity than tooth-to-tooth matching. Unlike jaw-to-jaw approaches, it is possible to match individual teeth. The method presented in this study provides a novel approach with significant matching accuracy and efficiency. By evaluating the effectiveness of these methods on panoramic images, the study contributes to forensic dental identification methods in scenarios where traditional biometric features may fall short.

Designing Polychromatic Luminescence in Mn2+-Doped Cs2NaLuCl6 Double Perovskite Crystals via Energy Transfer Engineering for Optical Thermometry and X-ray Imaging.

Metal halide double perovskites with splendid optical features have been considerably investigated for optoelectronic applications. Herein, a series of Mn2+-doped Cs2NaLuCl6 double perovskite crystals were prepared. Via adopting the density functional theory calculation, the effect of Mn2+ doping on the electronic structure of the Cs2NaLuCl6 compound was discussed. It was found that the Cs2NaLuCl6 crystal can emit intense blue light from the host self-trapped exciton (STE) emission. Excited by 320 nm, the STE and Mn2+ emissions were simultaneously observed in the resulting crystals. Owing to the efficient energy transfer from the STE to Mn2+, polychromatic luminescence was observed in final products. Moreover, taking advantage of the various responses of the emission intensities of the STE and Mn2+ to temperature, the thermometric characteristics of resulting crystals were investigated, and their maximum relative sensitivity is 0.99% K-1, which is hardly impacted by Mn2+ content. Furthermore, the prepared crystals exhibit good X-ray radioluminescence properties, with a low detection limitation of 0.99 μGyair s-1. Additionally, utilizing the designed crystal, flexible X-ray imaging with a high resolution of 20 lp mm-1 that can be operated in a high-temperature environment was realized. These results indicated that the Mn2+-doped Cs2NaLuCl6 double perovskite crystals are suitable for optical thermometry and X-ray imaging.

Utilization of a Deep Convolutional Neural Network for the Binary Classification of Chest X-Ray Pneumonia

Pneumonia remains a significant global health concern, necessitating efficient diagnostic tools. This study presents a novel Convolutional Neural Network (CNN) architecture, CuDenseNet, designed for the binary classification of Chest X-Ray (CXR) images as either having pneumonia or normal (healthy). Unlike models that rely on transfer learning from pre-trained architectures, CuDenseNet is trained from scratch and incorporates three parallel DenseNet paths of varying depths, enhancing feature extraction and classification accuracy. The model was evaluated on a combined dataset of 11,708 CXR images, achieving exceptional performance metrics of 99.1% accuracy, 99.7% precision, 99.1% recall, and an AUC of 99.7%. The comparative analysis demonstrates that CuDenseNet outperforms state-of-the-art pre-trained models such as VGG19 and ResNet50 while providing superior adaptability. These results underscore the potential of CuDenseNet as a robust and reliable tool for automated pneumonia diagnosis, with significant implications for clinical applications and future research in medical imaging.