Search

High-performance and low-cost metal halide perovskite scintillator materials have important applications in X-ray detection and imaging. However, large-sized perovskite scintillator panel with high transmittance, low toxicity and long-term stability is still lacking. Herein, Eu2+ doped cesium alkaline earth chloride nanocrystals (Eu2+: CsCaCl 3 , Eu2+: CsSrCl 3 , and Eu2+: Cs 2 BaCl 4 NCs) embedded in glasses through conventional melt-quenching and subsequent heat-treatment were developed. These NCs doped glasses exhibited highly efficient and narrowband photoluminescence in blue region. Benefitting from the large X-ray absorption coefficient and high photoluminescence quantum yied, these Eu2+: CsCaCl 3 NCs doped glass scintillator shows light yield of ∼9300 photons/MeV, detection limit of ∼213.8 μGy/s, and spatial resolution of 30.0 lp/mm. These results demonstrated that glasses containing Eu2+ doped cesium alkaline earth chloride nanocrystals are promising for X-ray detection and imaging. [ABSTRACT FROM AUTHOR]

Fracture detection is one of the most commonly used and studied aspects of artificial intelligence (AI) in medicine. In this systematic review and meta-analysis, we aimed to summarize available literature and data regarding AI performance in fracture detection on plain radiographs and various factors affecting it. We systematically reviewed studies evaluating AI algorithms in detecting bone fractures in plain radiographs, combined their performance using meta-analysis (a bivariate regression approach), and compared it with that of clinicians. We also analyzed the factors potentially affecting algorithm performance using meta-regression. Our analysis included 100 studies. In 83 studies with confusion matrices, AI algorithms showed a sensitivity of 91.43% and a specificity of 92.12% (Area under the summary receiver operator curve = 0.968). After adjustment and false discovery rate correction, tibia/fibula (excluding ankle) fractures were associated with higher (7.0%, p=0.004) AI sensitivity, while more recent publications (5.5%, p=0.003) and Xception architecture (6.6%, p<0.001) were associated with higher specificity. Clinicians and AI showed similar specificity in fracture identification, although AI leaned to higher sensitivity (7.6%, p=0.07). Radiologists, on the other hand, were more specific than AI overall and in several subgroups, and more sensitive to hip fractures before FDR correction. Currently available AI aids could result in a significant improvement in care where radiologists are not readily available. Moreover, identifying factors affecting algorithm performance could guide AI development teams in their process of optimizing their products. • Studies assessing AI in fracture detection have high degrees of bias. • AI showed a pooled sensitivity and specificity of >90% in detecting fractures. • Various factors, including fracture site and architecture affect AI's performance. • Radiologists remain superior to algorithms in fracture detection on X-rays. [ABSTRACT FROM AUTHOR]

Computerized disease detection systems (CDDs) have proven effective for automatic screening in recent years. Among the standard procedures in hospitals for faster and more accurate diagnosis is medical imaging-based disease screening. We aim to develop a CDD that detects COVID-19 using chest X-rays pre-trained vision transformers (PVTs). This scheme includes the following steps: (1) collecting images and resizing them, (2) implementing PVT for feature extraction, and (3) binary classifying the results and validating the proposed schemes. To prove the merit of the developed scheme, 4800 images (2400 normal and 2400 COVID-19) are analyzed. MLP classifiers verify the PVT performance using patch sizes of 6, 12, and 24. A patch size 24 results in 97.5% accuracy for the proposed CDD system. When patch sizes are increased to 12, accuracy increases to over 98%. For this specific task, smaller patch sizes are more effective. These high-accuracy results demonstrate the effectiveness of the developed scheme for detecting COVID-19 in chest X-rays. [ABSTRACT FROM AUTHOR]

The healthcare system in India faces an acute shortage of medical staff, significantly impacting the nation's ability to provide sufficient healthcare services. X-ray reports are paramount to orthopaedic surgeons for making critical patient care decisions. Implementing automated systems for detecting bone fractures offers a potentially efficient solution to supplement the limited workforce. However, these systems encounter substantial hurdles, such as inconsistent image quality and the risk of incorrect diagnosis due to the limitations of current technology. The research provides a specialised tool for identifying bone fractures with high precision (97% accuracy) and an excellent overall rating (F1 score of 0.98), showing it can reliably detect fractures. The assessment of this model is augmented by visual tools like heatmaps and performance graphs, providing an in-depth analysis of its operational effectiveness. Furthermore, creating a user-friendly interface is intended to streamline the adoption of this tool in clinical settings. Notwithstanding its demonstrated precision, the model must navigate data-related challenges, precisely data complexity and the representation of different categories, to prevent skewed outcomes. Clarifying the model's decision-making process and adaptability to various clinical situations are also critical. The study emphasises the need for thorough testing to ensure the model's dependability in diagnosing fractures before being deployed effectively in the medical field. [ABSTRACT FROM AUTHOR]

[Display omitted] Amyloid- β (A β) plaques from Alzheimer's Disease (AD) can be visualized ex vivo in label-free brain samples using synchrotron X-ray phase-contrast tomography (XPCT). However, for XPCT to be useful as a screening method for amyloid pathology, it is essential to understand which factors drive the detection of A β plaques. The current study was designed to test the hypothesis that A β -related contrast in XPCT could be caused by A β fibrils and/or by metals trapped in the plaques. Fibrillar and elemental compositions of A β plaques were probed in brain samples from different types of AD patients and AD models to establish a relationship between XPCT contrast and A β plaque characteristics. XPCT, micro-Fourier-Transform Infrared spectroscopy and micro-X-Ray Fluorescence spectroscopy were conducted on human samples (one genetic and one sporadic case) and on four transgenic rodent strains (mouse: APPPS1, ArcA β , J20; rat: TgF344). A β plaques from the genetic AD patient were visible using XPCT, and had higher β -sheet content and higher metal levels than those from the sporadic AD patient, which remained undetected by XPCT. A β plaques in J20 mice and TgF344 rats appeared hyperdense on XPCT images, while they were hypodense with a hyperdense core in the case of APPPS1 and ArcA β mice. In all four transgenic strains, β -sheet content was similar, while metal levels were highly variable: J20 (zinc and iron) and TgF344 (copper) strains showed greater metal accumulation than APPPS1 and ArcA β mice. Hence, a hyperdense contrast formation of A β plaques in XPCT images was associated with biometal entrapment within plaques. The role of metals in Alzheimer's disease (AD) has been a subject of continuous interest. It was already known that amyloid- β plaques (A β), the earliest hallmark of AD, tend to trap endogenous biometals like zinc, iron and copper. Here we show that this metal accumulation is the main reason why A β plaques are detected with a new technique called X-ray phase contrast tomography (XPCT). XPCT enables to map the distribution of A β plaques in the whole excised brain without labeling. In this work we describe a unique collection of four transgenic models of AD, together with a human sporadic and a rare genetic case of AD, thus exploring the full spectrum of amyloid contrast in XPCT. [ABSTRACT FROM AUTHOR]

The growth of the CsI(Tl) scintillators deposited on glass substrates with proper wavelength matching the mainstream semiconductor circuits is crucial for X-ray imaging industry. But the coupling loss between the scintillators and silicon based photo sensors has limited the performance. So fabricating CsI(Tl) films on monocrystalline silicon is greatly important for next-generation high performance X-ray image devices. However, the lattice and thermal mismatch between CsI(Tl) and Si always deteriorates the morphology and structure, and thus degrades the property of the CsI(Tl) scintillation converters. Here, by utilizing crystalline graphene(Gr) as a buffer layer, the van der Waals epitaxial growth of CsI(Tl) film on Si(111) substrate is reported and its advanced applications are demonstrated. The introduced graphene buffer layer extremely frees the stress between CsI(Tl) and Si substrate. Therefore, the CsI(Tl) films show perfect micro-columnar and crystalline structures, and then, exhibit much higher light output and signal to noise ratio, and better modulation transfer functions and a bar pattern X-ray image compared to that on bare Si(111) substrate. This facile method not only lays the foundation for the epitaxy of the alkali halide crystals, including CsI(Tl), onto Si-based detectors and its applications in radiation detection, but also may broaden a new perspective of deposition of CsI(Tl) scintillators into flexible substrates. [ABSTRACT FROM AUTHOR]

This article explore lung cancer using a hybrid deep learning (DL) model. Thus, this article offers a hybrid CNN along with the SVM classification method with tuned hyperparameters, which is the orthogonal Convolution neural network-support vector machine OCNN-SVM model. Each lung image may be automatically categorized and analyzed by this system to determine whether cancer cells are present. CNN has fewer parameters and is easier to train than a fully linked network with an exact count of hidden units. SVM has also been used to remove irrelevant data that has an adverse effect on accuracy. The effectiveness of this method is assessed in this research, and the findings show that the proposed orthogonal Convolution neural network-support vector machine (OCNN-SVM) model has been successful in categorizing lung images. [ABSTRACT FROM AUTHOR]

[Display omitted] Tissue-equivalent pure organic semiconducting crystals (OSCs) have unique advantages in direct X-ray detectors (DXDs), especially for biological tissue fluoroscopy, but their low carrier mobility and inherent weak absorption restrict the limit-of-detection (LoD) and sensitivity of DXDs. High-mobility OSCs theoretically facilitate charge collection and performance leaps, however, they are rare and suffer from poor solubility due to high conjugation, leading to nearly impossible crystal growth from solution and subsequent device applications. Here we report an ingenious solution-processed crystal-growth and high-performance DXD using 2,6-diphenylanthracene (2,6-DPA), a high-mobility OSC we developed recently. In contrast to previous OSCs, high-mobility 2,6-DPA exhibits low dark current density and large photoconductive gain, resulting in record-breaking LoD of <85 nGy air s−1 and sensitivity of >103 μC Gy air −1 cm−2. Compared with semiconductors containing high- Z atoms (Z is atomic number), the accuracy of 2,6-DPA based DXDs is not affected by near-edge absorption effects. Moreover, the non-linear relationship between irradiation current and dose rate is confirmed as a high injection effect. High mobility and ingenious crystal growth strategy make 2,6-DPA an ideal active material for DXDs and also provide the possibility for more optoelectronic applications. [ABSTRACT FROM AUTHOR]

Pore detection by x-ray computed tomography (CT) is widely used for additively manufactured (AM) parts. The ability of a CT device to reliably detect pores of a certain shape and size is still being investigated, though. Typical methods to evaluate the error of CT-based pore detection utilize reference objects or microscope images of cross-sections. This work improves the cross-section method by directly matching the two-dimensional (2D) plane depicted in the microscope image to the corresponding plane within the three-dimensional (3D) scan. For this purpose, a specially designed test part was scanned for a first time before preparing a cross-section and a second time afterward. The test part's design allowed to identify the cross-section's plane parameters relative to the part's local coordinate system in the second scan. The plane parameters were then transferred to the first CT scan in which pores had been detected to identify voxels that lay within the plane that was to become the cross-section. An image was extracted from this plane that directly matched a microscope image of the cross-section. Comparing CT and microscope images highlighted that CT's relative lack of resolution may lead to relevant errors when analyzing pore area and pore form. • Used additively manufactured test parts to assess CT's ability to detect pores. • Deployed micrographs of cross sections as reference. • Matched actual micrographs and virtual micrographs from CT. • Investigated CT settings' influence on ability to detect pores. • Found that CT reliably detects pores with an area of about 4 × 4 voxels. [ABSTRACT FROM AUTHOR]

Micron/sub-micron hard X-ray imaging is an important development direction of X-ray detection technology. Scintillation screens with excellent X-ray stopping power and high light output are desired to obtain good imaging quality. Europium-doped lutetium oxide (Lu 2 O 3 :Eu) film with micro-columnar structure is an ideal candidate for this application. In this study, micro-columnar structured Lu 2 O 3 :Eu films were prepared on quartz glass substrates by laser chemical vapor deposition (LCVD) method. The influences of preparation conditions on structure and morphology properties of films were investigated by X-ray diffraction (XRD) and scanning electron microscopy (SEM). Photoluminescence and scintillation properties of the films, including photoluminescence excitation (PLE), photoluminescence (PL), PL decay, X-ray excitation luminescence (XEL), and afterglow curves, were recorded. The relationships between structure, morphology, luminescence properties of films, and preparation conditions were investigated and discussed as well. The preparation conditions include laser power, oxygen flow rate, and precursor evaporation temperature. In addition, dual-layer Lu 2 O 3 :Eu film was prepared for the first time by just turning off the laser. [ABSTRACT FROM AUTHOR]

Compared with single-crystal scintillator, the glass scintillators have the benefits of low cost, big size, straightforward manufacturing method, and adjustable component. In this work, a succession of diaphanous gallogermanate glass scintillators doped with Tb3+ or Eu3+ were manufactured using melt-quenching technique. The thermal, structural, photoluminescent, and scintillating properties were studied. For photoluminescent properties, 12 mol% Tb3+-doped glass sample has high internal quantum efficiency (87.8%) and no obvious concentration quenching phenomenon can be observed. For scintillating properties, the optimal doping concentration of Tb3+ and Eu3+ are 4 mol% and 8 mol%, respectively. The integral intensity of X-ray excited luminescence of Tb3+-doped sample is 73.1% of that of Bi 4 Ge 3 O 12 scintillator, while the ratio of Eu3+-doped sample is 26.5%. The radiation damage of 4 mol% Tb3+-doped sample resulted by high power X-ray could be repaired through heat-treatment, while 8 mol% Eu3+-doped sample exhibits fine stability that the transmittance keeps constant after exposed to high power X-ray. Our research indicates Tb3+ or Eu3+ doped gallogermanate glass might be candidate for X-ray detection of slow events. [ABSTRACT FROM AUTHOR]

The CsPbX 3 perovskites have demonstrated promising applications in the field of X-ray detection. Appropriate element doping to substitute Pb in CsPbX 3 not only improves the photoresponse performance of the resulting material but also reduces the Pb content for achieving environmental protection. Herein, X-ray detectors based on Sr-doped CsPb 1-x Sr x Br 3 thick films were developed. The effects of Sr doping concentration were investigated. The incorporation of Sr increased the density of the CsPbBr 3 thick film and modulated the bandgap of the materials. CsPb 1-x Sr x Br 3 exhibited good optical responses at different bias voltages and X-ray doses. The X-ray response improved as the Sr-doping concentration increased. Therefore, the partial substitution of Sr into CsPbBr 3 is suitable for reducing the Pb content in X-ray detectors. Furthermore, the development of CsPb 1-x Sr x Br 3 thick films provides a new strategy for the detection of X-rays. [ABSTRACT FROM AUTHOR]

In this research work, a new deep learning model named VGG-COVIDNet has been proposed which can classify COVID-19 cases from normal cases over X-Rays and CT scan images of lungs. Medical practitioners use the X-Rays and CT scan images of lungs to identify whether a person is infected from COVID or not. In present times, it is very important to give real time COVID prediction with high reliability of results. Deep learning models equipped with machine learning support have been found very influential in accurate prediction of COVID or Non-COVID cases in real time. However, there are some limitations associated with the performance of these model which are model size, achieving good balance of model size and accuracy, and making a single model fitting well for both X-Ray and CT Scan image datasets. Keeping in mind these performance constraints, this new model (VGG-COVIDNet) has been proposed for real time prediction of COVID cases with good balance of model size and accuracy working well for both type of datasets (CT Scan and X-Ray). In order to control model size, an improved version of VGG-16 architecture has been proposed which contains only 13 convolutional layers and 5 fully connected layers. Multiple dropout layers have been added in the proposed architecture which can drop some percentage of features and applies random transformations to decrease the model over-fitting issue. Keeping in mind the primary goal to increase the model accuracy the proposed model has been trained on different datasets with ReLU activation function which is one of the best non-linear activation functions. Four different capacity datasets with CT scan and X-Ray images have been used to validate the performance of proposed model. The proposed model gives an overall accuracy of more than 90% on both types of input datasets i.e. X-Ray and CT Scan. [ABSTRACT FROM AUTHOR]

• Global Context Feature Extraction (GCFE) module is proposed, which can extract multi-scale global contextual information. • A Dual Scale Feature Aggregation (DSFA) module is proposed to fuse the features from different scales. • A learnable Gabor convolution layer is designed to enhance its ability to capture the edge and contour information of object. • A Spatial Attention (SA) mechanism is designed to further enhance the spatial structure information of object. Prohibited Object Detection (POD) in X-ray images plays an important role in protecting public safety. Automatic and accurate POD is required to relieve the working pressure of security inspectors. However, the existing methods cannot obtain a satisfactory detection accuracy, and especially, the problem of object occlusion also has not been solved well. Therefore, in this paper, according to the specific characteristics of X-ray images as well as low-level and high-level features of Convolutional Neural Network (CNN), different feature enhancement strategies have been elaborately designed for occluded POD. First, a learnable Gabor convolutional layer is designed and embedded into the low layer of the network to enhance the network's capability to capture the edge and contour information of object. A Spatial Attention (SA) mechanism is then designed to weight the output features of the Gabor convolutional layer to enhance the spatial structure information of object and suppress the background noises simultaneously. For the high-level features, Global Context Feature Extraction (GCFE) module is proposed to extract multi-scale global contextual information of object. And, a Dual Scale Feature Aggregation (DSFA) module is proposed to fuse these global features with those of another layer. To verify the effectiveness of the proposed modules, they are embedded into typical one-stage and two-stage object detection frameworks, i.e., Faster R-CNN and YOLO v5L, obtaining POD-F and POD-Y methods, respectively. The proposed methods have been extensively evaluated on three publicly available benchmark datasets, namely SIXray, OPIXray and WIXray. The experimental results show that, compared with existing methods, the proposed POD-Y method can achieve a state-of-the-art detection accuracy. And POD-F can also achieve a competitive detection performance among the two-stage detection methods. 1 1 https://github.com/Open-my-paper-code/POD. [ABSTRACT FROM AUTHOR]

Pr3+ doped high density germanate glasses were prepared by the melt-quenching method. The physical and luminescent properties were investigated. The glass containing BaF 2 represented maximum phonon energy of 810 cm−1, and the glass density was greater than 6 g/cm3. The glass exhibited good radiation resistance under 2 h of X-ray irradiation. Intense blue, green emissions and weak red emissions were observed when the glass was excited by X-ray, and the blue fluorescence lifetimes were in the range of 9.15–12.59 μs The results show that Pr3+ doped germanate glass could be a potential scintillating material in the field of X-ray detection for fast events. [ABSTRACT FROM AUTHOR]

COVID-19 had caused the whole world to come to a standstill. The current detection methods are time consuming as well as costly. Using Chest X-rays (CXRs) is a solution to this problem, however, manual examination of CXRs is a cumbersome and difficult process needing specialization in the domain. Most of existing methods used for this application involve the usage of pretrained models such as VGG19, ResNet, DenseNet, Xception, and EfficeintNet which were trained on RGB image datasets. X-rays are fundamentally single channel images, hence using RGB trained model is not appropriate since it increases the operations by involving three channels instead of one. A way of using pretrained model for grayscale images is by replicating the one channel image data to three channel which introduces redundancy and another way is by altering the input layer of pretrained model to take in one channel image data, which comprises the weights in the forward layers that were trained on three channel images which weakens the use of pre-trained weights in a transfer learning approach. A novel approach for identification of COVID-19 using CXRs, Contrast Limited Adaptive Histogram Equalization (CLAHE) along with Homomorphic Transformation Filter which is used to process the pixel data in images and extract features from the CXRs is suggested in this paper. These processed images are then provided as input to a VGG inspired deep Convolutional Neural Network (CNN) model which takes one channel image data as input (grayscale images) to categorize CXRs into three class labels, namely, No-Findings, COVID-19, and Pneumonia. Evaluation of the suggested model is done with the help of two publicly available datasets; one to obtain COVID-19 and No-Finding images and the other to obtain Pneumonia CXRs. The dataset comprises 6750 images in total; 2250 images for each class. Results obtained show that the model has achieved 96.56% for multi-class classification and 98.06% accuracy for binary classification using 5-fold stratified cross validation (CV) method. This result is competitive and up to the mark when compared with the performance shown by existing approaches for COVID-19 classification. [ABSTRACT FROM AUTHOR]

[Display omitted] Ultralong phosphorescent materials have numerous applications across biological imaging, light-emitting devices, X-ray detection and anti-counterfeiting. Triplet-state molecular phosphorescence typically accompanies the singlet-state fluorescence during photoluminescence, and it is still difficult to achieve direct triplet photoemission as ultralong room temperature phosphorescence (RTP). Here, we have designed Zn-IMDC (IMDC, 4,5-imidazoledicarboxylic acid) and Cd-IMDC, two-dimensional (2D) hydrogen-bond organized metal–organic crystalline microsheets that exhibit rarely direct ultralong RTP upon UV excitation, benefiting from the appropriate heavy-atom effect and multiple triplet energy levels. The excitation-dependent and thermally stimulated ultralong phosphorescence endow the metal–organic systems great opportunities for information safety application and temperature-gated afterglow emission. The well-defined 2D microsheets present color-tunable and anisotropic optical waveguides under different excitation and temperature conditions, providing an effective way to obtain intelligent RTP-based photonic systems at the micro- and nano-scales. [ABSTRACT FROM AUTHOR]

In recent years, copper-based halide scintillators have attracted tremendous attention due to their excellent luminescent properties and low manufacturing costs. Herein, a high-performance and low-cost Cs 5 Cu 3 Cl 6 I 2 scintillator is prepared by simple mechanical grinding. The mixed-halide Cs 5 Cu 3 Cl 6 I 2 phosphor exhibits a blue emission centered at 475 nm with a large stokes shift, originating from the self-trapped exciton emission of Cu sites. The photoluminescence quantum yield (PLQY) of Cs 5 Cu 3 Cl 6 I 2 can be increased to 88.4% from 20.4% by the efficient suppression of the anion vacancy defects. In addition, the Cs 5 Cu 3 Cl 6 I 2 scintillator shows a high steady-state X-ray to light conversion efficiency of about 57000 photons/MeV, good X-ray linear response, and low detection limit of 71.9 nGy air /s. The X-ray imaging results based on the Cs 5 Cu 3 Cl 6 I 2 scintillator screen display a high spatial resolution of 9.0 line-pairs per millimeter (lp/mm). Furthermore, Cs 5 Cu 3 Cl 6 I 2 exhibits good radiation stability under a total dose of 113.58 Gy air. Overall, the Cs 5 Cu 3 Cl 6 I 2 scintillator prepared by mechanical grinding method has the advantages of low cost, high efficiency, and good radiation resistance, suggesting its huge potential in X-ray detection and imaging. [ABSTRACT FROM AUTHOR]

Two-dimensional (2D) perovskite single crystals have risen to be prominent in the domain of optoelectronic materials due to their exceptional characteristics including notably low ion migration and defect density. A distinguishing feature is the strategic inclusion of larger organic amine spacer, alternately inserted between inorganic lead halide octahedral layers. This spacer effectively mitigates ion migration, even under higher bias voltages, which is particularly advantageous for X-ray detection. However, the simultaneous realization of multiple functions within this realm remains a formidable challenge. In this work, we have synthesized a high-quality organic spacer-incorporated single layered 2D perovskite single crystal of [CYP]PbBr 4 (CYP = 1-cyclohexylpiperazine). Our findings reveal the impressive potential of [CYP]PbBr 4 in the domain of X-ray detection, as evidenced by the ultrahigh X-ray sensitivity, long-term stability, and astonishingly low detection limit of 1.72 nGy air s-1. Notably, [CYP]PbBr 4 also emits bright broadband yellow light with quantum yield of 30.3%, and the fabricated white LED achieves a high Color Rendering Index of 94.1, which surpasses that of commercially available white LED based on YAG: Ce3+ (< 80). [Display omitted] • [CYP]PbBr 4 shows the spectral-selective photoconductivity, specifically, it is sensitive to UV-light illumination below about 400 nm but almost blind to the standard visible light (above 400 nm), showcasing the potential in visible-blind ultraviolet photodetection. • The X-ray photoconductor device, featuring an Au- [CYP]PbBr 4 -Au structure, has demonstrated outstanding sensitivity and minimal detection limit of 1.72 nGy air s-1 and exhibites enduring stability toward X-ray over 1500 min without additional protective shell. • This compound display bright broadband yellow light emissionwith moderate photoluminescence quantum yield of 30.3%. Most notably, the fabricated white LED achieves an extraordinary Color Rendering Index (CRI) of 94.1. • We believe our findings will provide valuable insights into the rationa design of new 2D organic-inorganic hybrid halides for advanced X-ray detection and solid-state lighting applications. [ABSTRACT FROM AUTHOR]

This work demonstrated a perovskite intermediate assisted hot-pressing method to fabricate FAPbBr 3 polycrystalline wafer X-ray detectors with near-single-crystal performance. The DMSO vapor released from the decomposition of FAPbBr 3 ·DMSO during the hot-pressing process will promote the in-situ growth of FAPbBr 3 crystal grains and improve the crystallinity, resulting in remarkable X-ray detection performance. [Display omitted] • FAPbBr 3 ·DMSO intermediate perovskite phase assisted hot-pressing approach. • In-situ FAPbBr 3 crystal growth promoted by DMSO vapor from FAPbBr 3 ·DMSO. • Quality improvement of polycrystalline perovskite wafers by hot-pressing process. • Polycrystalline FAPbBr 3 with X-ray detection properties similar to single crystals. Polycrystalline perovskite wafers featured in customizable in dimensions and thickness, represent a frontier in mass production of X-ray detectors. Nevertheless, inherent low crystallinity, elevated defect density, and grain boundaries in polycrystalline wafers typically impair the detection performance. Herein, a novel hot-pressing approach employing the perovskite intermediate phase FAPbBr 3 ·DMSO was demonstrated to improve the quality and X-ray detection performance of polycrystalline perovskite wafers. The in-situ growth of FAPbBr 3 wafers were promoted via dimethyl sulfoxide (DMSO) vapor released from the decomposition of FAPbBr 3 ·DMSO phase during the hot-pressing process, resulting in compact morphology, large grain size, superior crystallinity and diminished defect density. The resulted wafers exhibit a high ion activation energy (E a) of 0.45 eV and a substantial mobility-lifetime product (μτ) of 7.41 × 10−4 cm2 V−1. These advancements equip FAPbBr 3 wafer-based detectors with remarkable sensitivity of 3694.6 μC Gy air −1 cm−2, low detection limit (LoD) of 43.8 nGy air s−1, and stable operational performance, comparable to that of single-crystal alternatives. Moreover, the detectors exhibit exceptional X-ray imaging capabilities with a spatial resolution of 4.41 lp mm−1. Thus, the thermally induced decomposition characteristic of perovskite intermediate phase presents a novel avenue for the amelioration of polycrystalline perovskite wafers, heralding a leap forward in X-ray detection performance. [ABSTRACT FROM AUTHOR]

Electrospun ZnO/Bi 2 O 3 /PVA-coated glass samples were fabricated using electrospinning method, with varying ZnO molarities (0 M, 5 M, and 7 M) and Bi 2 O 3 weight percentages (wt%) to assess their potential for x-ray detection and measurement. Sample morphology and elemental composition analysis revealed well-distributed nanofiber strands on the glass substrate, with even dispersion of elements within the nanofiber across all samples. The effective atomic number (Z eff) of the sample is consistently enhanced with the addition of Bi 2 O 3 and higher ZnO molarity, where sample with 7 wt% Bi 2 O 3 own a greater Z eff value (41.56–44.12) than sample with 5 wt% Bi 2 O 3 (37.22–40.54). All samples except Sample A0 and B0 exhibited strong absorbance between wavelength range of 360 nm–400 nm. Sample A0 and B0 yielded energy band gaps (E g) of 2.39 eV and 2.37 eV, respectively, whereby samples with ZnO exhibit energy gaps of E g = 3.29 eV (Sample A1), E g = 3.27 eV (Sample A2), E g = 3.25 eV (Samples B1 and B2). All samples underwent x-ray exposure at various tube voltages (40–60 kVp) to assess their attenuation ability for x-ray detection and measurement. Sample B2 (5 wt% Bi 2 O 3 and 7 M ZnO) exhibited the most favorable linear response, while Sample B1 (5 wt% Bi 2 O 3 and 5 M ZnO) displayed favorable energy dependency. Thus, the electrospun ZnO/Bi 2 O 3 /PVA-coated glass with these compositions are proposed as potential dosimetry material due to their favorable linear response and energy dependency characteristics. • Fabrication of electrospun ZnO/Bi 2 O 3 /PVA-coated glass with varied ZnO molarities and Bi 2 O 3 percentages. • FESEM and EDX analyses show uniform nanofiber distribution and element dispersion. • Electrospun ZnO/Bi 2 O 3 /PVA-coated glass, 5 wt% Bi 2 O 3 , 5 M or 7 M ZnO, collected 4 h, emerges as promising dosimeter. [ABSTRACT FROM AUTHOR]

Organic polymers are light weight, low toxic and environmentally stable candidates of interest in X-ray detection application. But low attenuation and high recombination rate of charge carriers cause low sensitivity is major limitation of these detectors. In this work, organic polymers (PS/PMMA) composites were prepared with high-Z inorganic BiI 3 by simple dry mixing technique. The organic-inorganic hybrid further embedded with conductive carbon filler (MWCNT, CB, GP) to improve the charge collection of the samples. Resistivity and mobility of the samples were studied with help of Hall measurements and mobility-lifetime was calculated by Hecth equation and found (2.1 ± 0.2) × 10−3 cm2V−1. The elemental analysis of the samples had been done by XPS analysis. The X-ray investigations done by using dental X-ray source and the sensitivity of the samples increases from 3.4 to 200 μGy−1 cm−3 by incorporating CB filler with a low leakage current of order of 33.3 pA/cm2. • The composite exhibits a high SNR of 192 with low noise equivalent dose of 1.9 nGy−1 Hz−0.5 • The sensitivity has been increased by 100-fold for hybrid after embedding carbon filler at a low bias of 32V. • A novel solvent free technique to synthesis organic-inorganic hybrid has been used. • The prepared polymer composite has low leakage current density (3.33 pA/cm2) at low bias compared to α-selenium (10 pA/mm2). [ABSTRACT FROM AUTHOR]

This study reports on the synthesis of porous silicon (PS) and porous silicon doped with lead (PS–Pb) using an electrochemical method with a primary focus on optimizing key synthesis parameters to enhance material properties. During the synthesis, hydrofluoric acid (HF) and ethanol ratios were maintained at 4:1, which was crucial in achieving the desired structural properties. A structural analysis of the synthesized nanocomposites was conducted using Field Emission Scanning Electron Microscopy-Energy Dispersive X-ray Spectroscopy (FESEM-EDX). This structural analysis validated the successful incorporation of lead (Pb) into the samples. Among the key aspects of this study were the evaluation of the I–V characteristics of the PS-Pb nanocomposites. Based on the findings of I–V measurements, an increase in the bias voltage was observed, which was directly correlated with an increase in measured current, indicating significant changes in electrical properties as a result of Pb doping. Furthermore, the responses of these materials to X-ray pulse irradiation under various conditions were successfully measured and compared, enhancing the understanding of their potential as radiation detectors. The optimal electrochemical conditions for synthesizing PS and Pd-PS were identified as 90 V, 100 mA, 1 s, and 100 V, 100 mA, 0.5 s, respectively. As a result of optimizing electrochemical synthesis parameters, lead-doped porous silicon (Pb-PS) exhibited a marked reduction in pore size, decreasing from an average of 420.88 nm in undoped PS to 244.54 nm in Pb-PS. This structural refinement correlated with improved electrical properties; I–V measurements demonstrated that the current response at a bias voltage of 0.3 V improved from 1.6 × 10 − 5 A to 6.23 × 10 − 4 An under identical conditions. Furthermore, these materials responded to X-ray radiation and showed enhanced sensitivity, with Pb-PS detectors achieving a lower response time and higher current under X-ray exposure compared to undoped PS. These findings open up new avenues for employing these nanocomposites in advanced applications, particularly in fields that require precise and efficient radiation detection, such as medical imaging and environmental monitoring. This work represents a significant contribution to the field, illustrating the potential of these custom-engineered materials for the advancement of modern healthcare and detection technologies. • Advanced Fabrication: Successful lead integration into porous silicon matrix significantly enhances material properties. • Enhanced Conductivity: Pb-PS shows improved electrical conductivity and current responses. • Superior X-ray Detection Capabilities: Increased X-ray sensitivity in Pb-PS indicates high-performance detection potential. • Synthesis Optimization: Optimized electrochemical etching parameters for superior PS and Pb-PS X-ray detection. • Expanded Applications : Pb-doped porous silicon offers advancements in safety and diagnostics applications. [ABSTRACT FROM AUTHOR]

The development of Eu2+-activated oxide materials with high efficiency, fast decay and narrow bandwidth emission in the visible region is still challenging for the field of luminescence and scintillation applications. Generally, Eu2+ in oxide hosts can emit intense and broad 5d-4f emission in the visible region, but efficient emitting with stable bivalence of Eu is rare in inorganic oxide system. In this work, a series of ASL:Eu2+ (Sr 1-x La x Mg x Al 12-x O 19) powder samples with various La, Mg doping ratios were designed and synthesized to modulate the UV or X-ray excited luminescence properties, including redshift, quantum yield, and decaying lifetime. Moreover, an ASL:Eu2+ crystal with the optimal ratio x = 1/3 was grown, its scintillation performance was compared with standard Bi 4 Ge 3 O 12 crystal sample and evaluated in detail. These results indicate that the ASL:Eu2+ crystal is potential scintillator as a kind of X-ray detection and provide a reference for the further development of high-performance Eu-activated oxide scintillation materials. • The La, Mg dopants in SrAl 12 O 19 host promotes the red shift of Eu2+ emission under UV excitation. • The ASL:Eu2+ shows the self-trapped excitons radiation in XEL spectra. • The light yield of the as-grown ASL:Eu2+ crystal was determine to be 111.6 p.e./MeV. [ABSTRACT FROM AUTHOR]

The Low Gain Avalanche Detector (LGAD) is a promising technology for soft X-ray imaging at the next generation light sources as well as for particle tracking applications in high energy physics experiments. However, the lack of a thin entrance window is a limiting factor for deploying LGADs in some applications. In order to exploit the unique scientific imaging opportunities at the new XFELs, finely segmented detectors that can detect soft X-rays with energies as low as 30 eV are needed. The sensors must be able to provide an internal gain of ∼10 to amplify the generated small signal to be above the noise floor of the readout electronics and must have an extremely shallow entrance window to allow the absorption of soft X-rays in the active volume of the sensor. In 2020, we proposed a novel thin entrance window LGAD device concept. We have now produced the first wafer run. We will describe the design and simulation of the new device, as well as test results. Bench test measurements on single-pixel test structures show gain of 7 for shallow absorption. [ABSTRACT FROM AUTHOR]

A simple method of in-situ growth using anodized aluminum oxide templates is used to prepare a high-resolution pixelated scintillator array Cs 5 Cu 3 Cl 6 I 2 with enhanced light direction limitation for X-ray imaging, The Cs 5 Cu 3 Cl 6 I 2 @AAO film performs excellent stability under long-term X-ray irradiation, making it a reliable option for cost-effective pixelated indirect X-ray imaging. [Display omitted] • A perovskite array scintillation film Cs 5 Cu 3 Cl 6 I 2 @AAO via an in-situ growth strategy was fabricated. • A spatial resolution of approximately 20 lp mm−1 and a detection limit of 0.152 μGy·s−1 were achieved. • Excellent stability under long-term X-ray irradiation of Cs 5 Cu 3 Cl 6 I 2 @AAO was studied. Lead-free halide perovskites have shown promising application for indirect X-ray detection as fascinating scintillator. The fabrication of pixelated scintillator films leveraging directional confinement allows high-resolution imaging, yet process complexity and the potential crystal structure damage pose challenges that compromises the corresponding scintillator performance. In this work, a facile in-situ strategy for growing scintillation perovskite of Cs 5 Cu 3 Cl 6 I 2 within anodic aluminum oxide (AAO) membrane is developed as scintillator Cs 5 Cu 3 Cl 6 I 2 @AAO film. The as-fabricated pixelated scintillator array with an enhanced light directional confinement for high-resolution X-ray imaging is demonstrated. The corresponding film achieves a spatial resolution of approximately 20 lp mm−1 and a detection limit of 0.152 Gy·s−1. Moreover, the Cs 5 Cu 3 Cl 6 I 2 @AAO film performs excellent stability under long-term X-ray irradiation, making it a reliable option for cost-effective pixelated indirect X-ray imaging. [ABSTRACT FROM AUTHOR]

The perovskite scintillators have been extensively studied recently for their merits of tunable emission spectra and simple preparation processes. However, the practical applications of perovskite scintillator-based X-ray image sensor are still impeded by inadequate radioluminescence, poor environmental stability, and low imaging resolution. Herein, we demonstrate a scalable co-firing method to fabricate high-quality lead-free Cs 3 Cu 2 I 5 perovskite scintillator and an Indium (In)-doping strategy is introduced to enhance its radioluminescence performance at the same time. The In-doped Cs 3 Cu 2 I 5 obtains a high PLQY of 77.9% and a relative light output of 53372 ph/MeV, which are 0.34 and 1.08 times higher than those of the undoped counterpart, respectively. The X-ray detection limit of the In:Cs 3 Cu 2 I 5 can reach 150.55 nGy air /s, 36.53 times lower than the requirement for X-ray medical diagnosis. The synthesized scintillator also shows superior stability under continuous high dose X-ray irradiation of 6800 μGy air /s for 120 minutes, maintaining 95% of its initial radioluminescence intensity. Furthermore, a large-area (300 cm2) flexible perovskite scintillator film is prepared, which owns a much competitive resolution of 10 lp/mm and less distortion in X-ray imaging. This work provides a practical path for the wide application of perovskite scintillator in the field of X-ray detection and imaging in near future. [Display omitted] • A co-firing method for lead-free indium doped Cs 3 Cu 2 I 5 perovskite scintillators has been proposed. • The indium doped Cs 3 Cu 2 I 5 shows superior environmental and radiation stability. • A large-area flexible scintillator film is prepared for high-resolution imaging. [ABSTRACT FROM AUTHOR]

[Display omitted] • MAPbBr 3 NCs are in-situ space-confined encapsulated in metal–organic frameworks. • bMOF⊃MAPbBr 3 realizes room-temperature scintillation and exceptional X-ray imaging. • bMOF⊃MAPbBr 3 shows enhanced stability against various stimuli and X-rays. • The role of the MOF and the mechanism of improved performance are elucidated. The development of perovskite nanocrystals (NCs) based composites with enhanced stability and exceptional photoelectric properties is of great significance for their application in scintillators for X-ray imaging, but it remains challenging. Herein, we demonstrate a novel and stable scintillator, achieved through a host–guest strategy involving the confinement of perovskite NCs, e.g., MAPbBr 3 NCs, in metal–organic frameworks (MOFs). The host MOF, bio-MOF-100 (denoted as bMOF), facilitates the in-situ space-confined formation of MAPbBr 3 NCs while providing quantum confinement, surface passivation, and protection to these guests. This host–guest strategy results in high exciton binding energy, bright and efficient luminescence, and significantly enhancing their stability against various factors such as air, heat, UV, solvents and X-ray irradiation. Consequently, this advancement prompts the transition of their application scenarios from the colloidal state to the solid state. The bMOF⊃MAPbBr 3 scintillator exhibits a linear response to X-ray with a detection limit determined to be 170 nGy air s−1. Moreover, the bMOF⊃MAPbBr 3 –PMMA scintillator screen demonstrates high-quality X-ray imaging with an impressive spatial resolution of 14.7 lp mm−1. This work provides a new avenue for the development of perovskite NCs-based host–guest composites and paves the way for the broader implementation in solid-state optoelectronic applications. [ABSTRACT FROM AUTHOR]

Low Gain Avalanche Diodes (LGADs) represent the state-of-the-art in timing measurements and will instrument future timing detectors at the High Luminosity Large Hadron Collider (HL-LHC) experiments. While conceived as a sensor for charged particles, the intrinsic gain of LGADs makes it possible to detect low energy X-rays with good energy resolution and excellent timing (tens of picoseconds). Using the Stanford Synchrotron Radiation Lightsource (SSRL) at SLAC, several LGADs designs were characterized with energies from 5 to 35 keV. The SSRL provides 10 ps pulsed X-ray bunches separated by 2.1 ns intervals, and with an energy dispersion (Δ E/E) of 1 × 10-4. LGADs fabricated by Hamamatsu Photonics (HPK) and Brookhaven National Laboratory (BNL) with different thicknesses ranging from 20 µm to 50 µm and different gain layer designs were read out a two stage fast amplification circuit and digitized with a high bandwidth, high sampling rate oscilloscope. PIN devices from HPK were characterized as well. A systematic and detailed characterization of the devices' energy linearity, resolution and timing resolution as a function of X-ray energy was performed for different biasing voltages at room temperature. [ABSTRACT FROM AUTHOR]

The silicon-on-insulator pixel (SOIPIX) detector is a unique monolithic-structure imaging device currently being developed by the SOIPIX group led by the High Energy Accelerator Research Organization (KEK). The detector team at KEK Photon Factory (PF) is also developing an X-ray camera using INTPIX4NA with a 14.1 × 8.7 mm2 sensitive area and 425,984 (832 column × 512 row matrix) pixels, with a pixel size of 17 × 17 µm2. The detector has high resolution and sensitivity for low-intensity X-rays, making it suitable for imaging in optical systems with lower X-ray intensities, such as an X-ray zooming microscope using two Fresnel zone plates (FZPs), which is also under development at PF. To enable imaging under such conditions, we developed a detector cooling system using a Peltier element to support longer exposure time (0.5 s per frame). Additionally, we developed a new readout system using DAQ boards developed by PF, equipped with SiTCP-XG (network controller implemented on field-programmable gate array) that supports 10 Gbps Ethernet for high-frame-rate imaging at several hundred hertz. The new X-ray camera was tested at the PF BL-14A, BL-14B, and AR-NE1A experimental stations, and the resolution and sensitivity characteristics were confirmed. Given these confirmed characteristics, this X-ray camera is suitable for X-ray imaging using 5–20 keV X-rays under low-intensity, low-contrast conditions. These conditions are ideal for capturing soft tissues with poor contrast, objects with fine structures, and specimens vulnerable to radiation damage. • SOIPIX INTPIX4NA detector based X-ray camera was developed at KEK Photon Factory. • INTPIX4NA detector has a 14.1 × 8.7 mm2 sensitive area (17 μ m pitch 832 × 512 pixel matrix). • This is suit for imaging with 5–20 keV X-ray under low-intensity/contrast conditions. • 10GbE DAQ system and Peltier based detector cooling system were also developed. • The resolution and sensitivity characteristics were tested/confirmed at KEK PF. [ABSTRACT FROM AUTHOR]

XRPIX is the monolithic X-ray SOI (silicon-on-insulator) pixel detector, which has a time resolution better than 10 μ s as well as a high detection efficiency for X-rays above 10 keV. XRPIX is planned to be installed on future X-ray satellites. To mount on satellites, it is essential that the ADC (analog-to-digital converter) be implemented on the detector because such peripheral circuits must be as compact as possible to achieve a large imaging area in the limited space in satellites. Thus, we developed a new XRPIX device with the on-chip ADC, and evaluated its performances. As the results, the integral non-linearity was evaluated to be 6 LSB (least significant bit), equivalent to 36 eV. The differential non-linearity was less than 0.7 LSB, and input noise from the on-chip ADC was 5 e −. Also, we evaluated end-to-end performance including the sensor part as well as the on-chip ADC. As the results, energy resolution at 5.9 keV was 294 ± 4 eV in full-width at half maximum for the best pixel. [ABSTRACT FROM AUTHOR]

With the extensive application of object detection in intelligent security, the demand for detecting prohibited items in X-ray images has become increasingly stringent. Unlike natural images, X-ray images present unique challenges such as complex backgrounds and mutual occlusion between prohibited and normal items. Consequently, applying traditional detection methods to X-ray images remains a significant challenge. To tackle these challenges, we have developed a unique frequency-aware dual-stream transformers (FDTNet) that is specifically designed for analyzing X-ray images. The FDTNet consists of two streams: one handles the original image, while the other deals with an image that has been enhanced with frequency domain features. In order to achieve precise detection of prohibited items, we introduce a frequency-aware module (FAM) that enhances the representation of prohibited items by utilizing information from the frequency domain. This FAM can be easily integrated into other backbones or detectors as it is a plug-and-play module. Additionally, to enhance the fusion of feature maps from both streams, we utilize a global and channel attention module (GCA) that aggregates texture representations for spatial feature streams. Our evaluation of the proposed FDTNet on the OPIXray datasets and PIDray datasets demonstrates that our detection mAP achieves 88.02 and 68.2, respectively. Extensive experiments conducted on publicly available datasets provide substantial evidence that our proposed network significantly improves the detection of prohibited items compared to state-of-the-art methods. [Display omitted] • The dual-stream design is used to extract RGB features and frequency features respectively • Global and channel attention module enhances the features generated by the RGB stream using attention mechanisms. • Frequency-aware module encodes frequency features, enabling better capture frequency information. [ABSTRACT FROM AUTHOR]

To effectively solve the problems of low detection accuracy caused by low quality image discriminative features of X-ray weld defects, lack of intuitive representation of the defect size of existing detection algorithms, and the strong subjectivity of the detection model artificial parameter adjustment, an X-ray weld defect detection and size measurement algorithm based on neural network self-optimization is proposed. Firstly, a high-performance detection model for X-ray weld defects is constructed, and the detection accuracy is comprehensively improved through a series of featured module designs with the capabilities of feature information enhancement and multi-scale information fusion. Secondly, a model optimization strategy is proposed to obtain the optimal hyperparameter components of the model through adaptive optimization to enhance the model's self-learning capability. Finally, by constructing the mapping relationship between the actual size of defects and the screen resolution, the size measurement algorithm of weld defects is designed, and the integrated technology of defect detection and size measurement is realised. Experimental results show that the proposed algorithm achieves good results even on a small-scale X-ray weld seam defect dataset. Compared to other classical and advanced detection models used in the experiments, mAP@0.5 is improved by an average of 16.1% and mAP@.5:.95 by an average of 10.7%. The image processing speed reaches up to 68 frames per second, and the error between the size calibration and manual actual measurement is less than 0.1 cm, which can meet the real-time detection requirements for weld seam defects in practical industrial production. In this research, the specific contributions are as follows:: • We construct a high-performance X-ray weld defect detection model to improve the detection efficiency. • We propose an HCOA model self-optimization strategy for high-dimensional hyperparameter evolution of deep neural networks. • We design an algorithm to measure the sizes of welding defects which can provide support for defect grade assessment. • Our method compared with other models, mAP@0.5 is improved by an average of 16.1% and mAP@.5:.95 by an average of 10.7%. • The image processing speed reaches up to 68 frames per second, the size error is less than 0.1cm. [ABSTRACT FROM AUTHOR]

Chest X-ray image contains sufficient information that finds wide-spread applications in diverse disease diagnosis and decision making to assist the medical experts. This paper has proposed an intelligent approach to detect Covid-19 from the chest X-ray image using the hybridization of deep convolutional neural network (CNN) and discrete wavelet transform (DWT) features. At first, the X-ray image is enhanced and segmented through preprocessing tasks, and then deep CNN and DWT features are extracted. The optimum features are extracted from these hybridized features through minimum redundancy and maximum relevance (mRMR) along with recursive feature elimination (RFE). Finally, the random forest-based bagging approach is used for doing the detection task. An extensive experiment is performed, and the results confirm that our approach gives satisfactory performance compare to the existing methods with an overall accuracy of more than 98.5%. [ABSTRACT FROM AUTHOR]

This study investigated the use of inorganic cadmium selenide nanoplatelets (CdSe NPLs) to enhance the performance of X-ray detectors. The active layer of the detector comprised a bulk heterojunction composed of PCDTBT:PC 71 BM: CdSe NPLs with three different aspect ratios (ARs = 3:1, 1:1, and 6:1). The CdSe NPLs, synthesized with a thickness of five monolayers, were controlled by adjusting the molar mass ratios of Cd(OAc) 2 and Cd(OAc) 2 ∙2 H 2 O. Each detector was characterized by analyzing its series resistance, collection irradiation, dark current density, detection sensitivity, charge mobility, and defect density via the collected charges. The detector containing CdSe NPLs with an aspect ratio of 1:1 demonstrated the most favorable performance, exhibiting improved carrier generation and transport properties, resulting in a 23.36 % increase in sensitivity compared with the detector without CdSe NPLs. Through experimentation, the optimal content of CdSe NPLs in the active layer was determined to be 1 wt%, yielding the highest sensitivity of 3.96 × 103 μC∙Gy−1∙cm−2. This study underscores the potential of CdSe NPLs as promising materials for X-ray detector applications. • Utilized CdSe nanoplatelets (NPLs) to enhance X-ray detector performance. • Demonstrated 23.36 % sensitivity increase with optimized CdSe NPLs (AR = 1:1). • Revealed CdSe NPLs altered surface morphology, enhancing light absorption. • Highlighted potential of CdSe NPLs for improving various optoelectronic devices. [ABSTRACT FROM AUTHOR]

Lead-free halides, with the advantages of non-toxicity and high stability, have broad application prospects. Here, we studied the synthesis and luminescent properties of the Sb-doped Rb 2 ZnCl 4 and explored their utilizations for white light-emitting diode (WLED) and X-ray detection. The as-synthesized Rb 2- x Zn 1- x Sb x Cl 4 single crystals exhibit bright red emission centered at 740 nm with a large full width at half maximum (FWHM) of 220 nm, and the maximum photoluminescence quantum yield (PLQY) is determined to be 59.7 % for the sample with x = 0.01. The assembled WLED achieves a high color rendering index (CRI) of 93.6 and a low correlated color temperature (CCT) of 3755 K. Under continuous X-ray irradiation for 600 s at a dose rate of 26.5 Gy min−1, the irradiation luminescence intensity of Rb 1.99 Zn 0.99 Sb 0.01 Cl 4 did not decrease, indicating that the single crystal has a high tolerance to X-ray irradiation. Our work demonstrates that Zn halides are also a promising lead-free family for multiple optoelectronic applications. • Significantly improve the luminescence properties of Rb 2 ZnCl 4 by doping with Sb. • The effect of Sb doping concentration on luminescence properties of Sb-doped Rb 2 ZnCl 4. • Sb-doped Rb 2 ZnCl 4 show high stability in WLED and X-ray detection applications. [ABSTRACT FROM AUTHOR]

Landmark detection using X-ray imaging is vital for disease screening, treatment, and prognosis. It provides a framework for subsequent tasks, including segmentation, classification, and target detection. Existing landmark detection methods exhibit limits with the increasing number of X-ray examiners. Not only they serve specific data types, but also their ability to learn the complete semantic information from this dataset is limited, potentially affecting their widespread adoption. We address these challenges by proposing a universal landmark detection model for multidomain X-ray imaging, UniverDetect. By progressively acquiring local semantic information, global semantic insights, and anatomical structure knowledge at various levels, the model ensured that the detected landmarks were closely aligned with the ground-truth labels. UniverDetect consists of three key components. The landmark detection module (LDM) utilizes a U-net network equipped with our innovative pyramid depthwise separable (PDS) convolution module for initial landmark detection. The landmark refinement module (LRM) integrates a fine-tuning module comprising continuously extended convolution blocks. Finally, the landmark correction module (LCM) incorporates a graph convolutional network (GCN) to rectify offset errors during partial landmark detection. An inherent feature of this model is its domain- generalization capability, which enables continuous learning across diverse domains. This model can concurrently learn from eight domains, covering 118 landmarks within a diverse dataset of 5969 images. Extensive experiments on multiple datasets demonstrate that this method consistently outperforms state-of-the-art approaches. This study presents a versatile and effective solution to reduce doctors' workload while providing precise quantitative analysis. [ABSTRACT FROM AUTHOR]

• Presents a novel framework combining residual network (ResNet) with bidirectional long short-term memory network (BiLSTM) for enhanced terahertz signal analysis. • Introduces a sophisticated method for automatic defect detection and interface localization in non-metallic materials, surpassing traditional manual analysis in efficiency and accuracy. • Achieves interface positioning accuracy surpassing 80 µm in coating sample thickness, demonstrating superior performance to conventional approaches. • Provides robust validation against X-ray CT results, revealing an error margin of only 1.07% to 5.39% in detecting adhesive layer defects. This manuscript presents a framework that integrates a residual network (ResNet) with a bidirectional long short-term memory network (BiLSTM) for effective feature extraction and interface positioning in terahertz signal analysis. This innovative approach employs spatial and temporal feature extraction modules to process terahertz signals, enabling the automatic detection of interfaces and defects in both coating and bonded structure samples. The experimental results indicate that the interface positioning accuracy of the method aligns with the manual analysis outcomes for coating samples exceeding 80 µm in thickness. Furthermore, it exhibits a high degree of consistency with X-ray CT detection results when detecting defects in the adhesive layer, with an error margin ranging from 1.07 % to 5.39 %. Significantly, we have also conducted preliminary analyses on actual samples, further underscoring the robustness and generalizability of our model. This method offers an efficient automated tool for terahertz signal analysis and holds promise for industrial detection applications. Future research will aim to broaden the range of samples and application scenarios, thereby increasing the technology's practicality in quality control and production line detection. [ABSTRACT FROM AUTHOR]

Low-dose X-rays in the order of milligrays (mGy) are employed in diagnostic radiology. This poses a challenge, considering commercially used dosimeters have limitations in detecting low-dose X-rays. Accordingly, the goal of this research was to fabricate a nitro blue tetrazolium-doped polyvinyl alcohol (PVA/NBT) film dosimeter that could respond to low-dose X-rays while also investigating the effects of introducing copper(II) and bismuth(III) ions on the film's detecting ability. The films were synthesized by the solvent casting method and then exposed to X-ray radiation at doses in the range of 0–2.626 mGy. Optical density and UV–Vis transmittance measurements were carried out to identify changes in the film's optical characteristics brought on by X-ray radiation. In addition, changes in the film's surface morphology and chemical structure were examined by scanning electron microscopy (SEM) and FTIR spectroscopy. According to the results of the optical density measurement, introducing copper(II) ions to the film increased its sensitivity and response linearity. In contrast, the opposite was shown in the case of bismuth(III)-doped films. According to FTIR analysis, film X-ray irradiation caused the PVA to degrade. The development of grain structures on the film surface might be related to the reduction of the copper(II) and bismuth(III) ions. This study discovered that copper(II) ion-doped PVA/NBT film has promising low-dose X-ray detection properties. [Display omitted] • Cu 2 + and Bi 3 + were doped to PVA/NBT film to increase its sensitivity to X-rays. • PVA/NBT and metal ion-doped PVA/NBT films were prepared via solvent casting method. • The UV–Vis spectrum of the film shifted in response to X-ray exposure. • Copper(II)-doped PVA/NBT film has promising low-dose X-ray detection properties. [ABSTRACT FROM AUTHOR]

Metal halide perovskite single crystal (SC) has attracted wide attentions in the field of photoelectric detection. All-inorganic perovskite SCs are much more stable than the hybrid counterparts, but its rapid fabrications usually end up low quality. We proposed a modified solvent-evaporation method that can rapidly obtain smooth and transparent high-quality CsPbBr 3 single crystal with a surface roughness of only 5 nm in a few hours. In this method, the lattice phase of the SC and the growth rate is precisely controlled by the solution temperature, which is raised to the narrow range above the cubic-to-tetragonal phase transition temperature. This precisely controlled solvent temperature allows the CsPbBr 3 SC growing immediately into cubic phase, and limits the volatilization rate of solvent, thus inhibiting the defect density. The SCs grown this way are of high crystallinity, as the half-height width of the (100) and (200) peaks of XRD rocking curve is 0.0154° and 0.0176°, respectively. Characterization of photoelectric properties shows great potential for applications in X-ray detection and photodetection. • CsPbBr 3 single crystals were grown by a modified evaporative solvent method. • The crystal quality is very high crystallinity as the half-height width of the rocking curve as low as 0.0176°. • The effect of growth temperature on crystal quality is investigated. • The growth time of large size (3 mm) CsPbBr 3 single crystals is reduced to 10 h. [ABSTRACT FROM AUTHOR]

The backscatter X-ray system makes an image by detecting scattered particles from an object in the opposite direction by Compton scattering. This system has the advantage of detecting drugs or explosives composed of organic substances. In this study, we developed a backscatter X-ray detection system. The 6-ch DAQ system is able to store acquired data for 50 μs as 8 bytes and the 6-ch high voltage power supply board provides adjustable power from 0 to 1600 V. Using this detection system, we varied the tube voltage from 80 to 160 kV and observed backscatter X-ray images of two plastic phantoms at 160 kV. The results indicate a need to optimize the speed of the collimator and data acquisition time of the DAQ system to improve image quality. The backscatter X-ray imaging technology exhibits high scalability, making it applicable not only to security screening but also for medical and industrial purposes. [ABSTRACT FROM AUTHOR]

In this paper, we synthesized silver nanoclusters using bovine serum albumin (BSA) as a template (BSA@AgNCs). Then, we anchored hydroxyphenyl fluorescein (HPF) to yield HPF-BSA@AgNCs. When exposed to X-rays, hydroxyl (∙ OH) radicals generated by radiolysis of water react with HPF to produce fluorescein, which emits enhanced fluorescence at 515 nm (λ ex = 480 nm). The fluorescence intensity of BSA@AgNCs at 685 nm (λ ex = 480 nm) remains stable when exposed to X-rays. This HPF-BSA@AgNCs ratiometric fluorescence sensor can rapidly detect 0.1–20 Gy (the energy deposited per unit mass, J/kg) of X-rays. In addition, HPF-BSA@AgNCs exhibit good durability and temperature stability. Finally, HPF-BSA@AgNCs were used to measure the absorbed doses of A549 cells and evaluate the cell irradiation damage. [Display omitted] • We synthesize silver nanoclusters using bovine serum albumin (BSA) as a template, then anchored hydroxyphenyl fluorescein (HPF) to yield HPF-BSA@AgNCs. • HPF-BSA@AgNCs ratiometric fluorescence sensor can rapidly detect 0.1–20 Gy of X-rays. • HPF-BSA@AgNCs exhibit good durability and temperature stability. • HPF-BSA@AgNCs can rapidly measure the absorbed doses of A549 cells and evaluate the cell irradiation damage. [ABSTRACT FROM AUTHOR]

• Novel method enabling tracking of obscured lung tumor in X-ray. • Validation on real-world patient data (CyberKnife 1 View patients). • Zero-shot deep learning framework leveraging deep learning infrastructure yet independent of specific data or patient cohort. Motion management is essential to reduce normal tissue exposure and maintain adequate tumor dose in lung stereotactic body radiation therapy (SBRT). Lung SBRT using an articulated robotic arm allows dynamic tracking during radiation dose delivery. Two stereoscopic X-ray tracking modes are available – fiducial-based and fiducial-free tracking. Although X-ray detection of implanted fiducials is robust, the implantation procedure is invasive and inapplicable to some patients and tumor locations. Fiducial-free tracking relies on tumor contrast, which challenges the existing tracking algorithms for small (e.g., <15 mm) and/or tumors obscured by overlapping anatomies. To markedly improve the performance of fiducial-free tracking, we proposed a deep learning-based template matching algorithm – Deep Match. Deep Match consists of four self-definable stages – training-free feature extractor, similarity measurements for location proposal, local refinements, and uncertainty level prediction for constructing a more trustworthy and versatile pipeline. Deep Match was validated on a 10 (38 fractions; 2661 images) patient cohort whose lung tumor was trackable on one X-ray view, while the second view did not offer sufficient conspicuity for tumor tracking using existing methods. The patient cohort was stratified into subgroups based on tumor sizes (<10 mm, 10–15 mm, and >15 mm) and tumor locations (with/without thoracic anatomy overlapping). On X-ray views that conventional methods failed to track the lung tumor, Deep Match achieved robust performance as evidenced by >80 % 3 mm-Hit (detection within 3 mm superior/inferior margin from ground truth) for 70 % of patients and <3 mm superior/inferior distance (SID) ∼1 mm standard deviation for all the patients. Deep Match is a zero-shot learning network that explores the intrinsic neural network benefits without training on patient data. With Deep Match, fiducial-free tracking can be extended to more patients with small tumors and with tumors obscured by overlapping anatomy. [ABSTRACT FROM AUTHOR]

CsI(Tl) scintillator has been widely used in X-ray flat-panel detectors due to excellent performance characteristics including a suitable Si-photodiode emission wavelength, excellent optical output, and fast decay time. Here, a solution-based space-confined growth method was presented to achieve CsI(Tl) scintillator single-crystal flakes with controllable thickness. The grown CsI(Tl) single-crystal flake exhibits a comparable light yield (∼72,000 photons/MeV) and a lower afterglow level (0.1% @ 21 ms, 0.01% @ 118 ms) in comparison to that by the traditional melting method. This space-confined method allows for the achievement of a single crystal thickness of only 0.27 mm, making it suitable for direct application in X-ray detection and other related fields. It may open up new possibilities for the development of halide scintillator single crystals. A solution-based space-confined growth method enables the growth of high-quality CsI(Tl) single crystal flakes with controlled thickness for X-ray flat-panel detectors. [Display omitted] • A space-confined solution method is used to grown CsI(Tl) single-crystal flakes. • The thickness of the CsI(Tl) flake grown using this method can be controlled to be as thin as approximately 0.27 mm. • The CsI(Tl) flake exhibits a lower afterglow and a comparable light yield in comparison to that by the melting method. [ABSTRACT FROM AUTHOR]

Perovskite X-ray detectors are actively investigated because of their exceptional properties, including their significant attenuation coefficient, low defect density, excellent transport characteristics, easy growth, and high sensitivity to X-ray photons. However, perovskite-based high-energy X-ray detectors on the MeV scale are rarely explored. In this study, we investigate the optoelectronic characteristics and radiation detection capabilities of triple-cation Cs 0.05 FA 0.9 MA 0.05 PbI 3 single crystals (CSC) grown using the inverse temperature crystallization method. The CSCs with a reduced Goldschmidt tolerance factor owing to the presence of Cs and MA ions exhibit exceptional properties, including a bandgap of 1.447 eV, low dark current, and self-powered response to X-ray irradiation. The X-ray absorption rate of 36 keV exceeded 99% with a CSC thickness of 2 mm, demonstrating its strong stopping power. Moreover, the CSC detectors exhibit precise linear responses to varying X-ray doses and dose rates with R2 values close to 1 and relative standard deviation (RSD) values below 3% under all the tested conditions. In addition, the detector effectively detected high-energy X-rays of up to 15 MV with minimal variations in the RSD values. These findings highlight the potential of CSC as promising materials for high-performance X-ray detectors. • Triple-cation lead–halide perovskites for high-energy X-ray detection were studied. • CSC detector has uniform linear response to varying X-ray doses and rates. • CSC detector can detect high-energy X-rays of up to 15 MeV. • CSC demonstrated remarkable promise as excellent self-powered X-ray detectors. [ABSTRACT FROM AUTHOR]

• Liquid epitaxy boosts δ-CsPbI 3 's one-dimensional growth, enhancing carrier transition. • Sensitivity reaches 1768.46 μC Gy air -1 cm−2 at 432 V mm−1, outperforming α-Se and single crystalline δ-CsPbI 3 detectors. • Retains 91.34 % sensitivity after 7 days in air, showcasing impressive long-term stability. • Successful integration with a thin-film transistor array for 8-bit imaging in a 64 × 64 matrix. • Opens the door for commercial high-performance direct X-ray detectors, solving the "absorption vs. transportation" issue. An ideal direct X-ray detector should convert a low dose of X-ray photons into large quantity of electrical signals, coupled with sustained long-term stability. Nevertheless, a notable conflict arises between X-ray absorption efficiency and carrier transport in thick polycrystalline perovskite films. Moreover, conventional perovskite materials exhibit inherent challenges regarding the stability of their crystal phase and the consistency of the photocurrent. To circumvent these limitations, a polycrystalline perovskite thick film is proposed using orthorhombic CsPbI 3 (δ-CsPbI 3) as a highly stable active material. Combined with the liquid epitaxy process, δ-CsPbI 3 prefers one-dimensional growth along the carrier transportation direction, which suppresses the formation of grain boundaries, enabling high carrier mobility while maintaining X-ray absorption for a thick polycrystalline film. Consequently, the polycrystalline δ-CsPbI 3 based detector exhibits a highest sensitivity of 1768.46 μC Gy air -1 cm−2 at an electric field of 432 V mm−1 which is 88.42-fold higher than α-Se based detectors and 190-fold higher than the single crystalline δ-CsPbI 3 based detector, respectively. The sensitivity maintains 91.34 % of its initial state after 7 days exposure in the air. Combing with a thin-film transistor array, the detector achieves 8-bit imaging within a 64 × 64 matrix. This work provides a feasible method for commercialized production of high-performance direct X-ray detectors. [ABSTRACT FROM AUTHOR]

X-ray-prohibited item inspection is an important measure to maintain public safety and has been widely applied in industries such as transportation and logistics. Without bells and whistles, it is a classic few-shot object detection task due to the long-tailed distribution of data in the real world, i.e., rare items occur at low frequencies. Taking into account that most previous few-shot methods are designed to detect known categories and are unable to perceive unknown objects, this is not conducive to the screening of novel types of prohibited items because the predefined categories in specific datasets cannot cover all possible classes in the natural world. In this work, we propose a Few-shot Open-set X-ray Object Detection method (FOXOD) composed of four novel components, namely the Overlapping Object Separator (OOS), Unknown Interest Advisor (UIA), Knowledge Augmentation (KA), and Discriminant Classifier (DC). Our method aims to achieve perceptual alertness for all known prohibited items and potential unknown objects based on a few data. To alleviate the problem of high overlap between objects, OOS utilizes a hierarchical attention mechanism to sample local knowledge and decouple the features of overlapping individual targets. In addition, UIA is carefully designed to assist RPN in perceiving potential unknown proposals without supervision, while KA mitigates catastrophic forgetting of known classes by the model. Moreover, DC prevents overfitting and further identifies unknown positive objects from a large number of background proposals. Extensive experiments on SIXray and VOC datasets demonstrate that FOXOD outperforms other baselines in both X-ray and common scenarios. Code is available at: https://github.com/liumaozhen-lmz/-FOXOD. [ABSTRACT FROM AUTHOR]

A new optical beam splitting method is proposed, based on which the optical frame camera capable of capturing multiple frames in a single exposure is designed and experimentally verified. The operation of the frame camera is based on an ultra-fast response semiconductor detector. It is equipped with an optical beam splitter and an optical imaging module. The ultrafast semiconductor detector receives an optical pulse that produces a transient refractive index change, and ultrafast physical processes are recorded by diffracting the probe laser through the transient phase grating. The interaction of an X-ray pulse with a semiconductor detector to produce a phase grating is simulated, based on the Monte Carlo method. The optical beam splitting mode separates a laser into two optical pulses with a certain time difference in the direction of polarization perpendicular to each other. The imaging module filters the diffracted probe laser in the spectral plane and then images multiple frames. The frame camera was used to record the temporal and spatial distribution characteristics of femtosecond laser pulses with a temporal resolution of 4.1 ps. This frame camera has great potential and value for applying to experimental studies of inertial confinement fusion. [ABSTRACT FROM AUTHOR]

We present an analysis of publicly available X-ray and optical observations of TYC 7275-1968-1, a contact binary, red nova progenitor candidate. The long optical time series of ASAS-3 , SuperWASP , CRTS , Gaia , ASAS-SN , and TESS enabled us to improve its orbital period to 0.3828071 ± 0.0000026 d. We show the presence of an X-ray and UV source associated with TYC 7275-1968-1 from Neil Gehrels Swift Observatory, that was previously assumed to be the counterpart of CD -36 8436 (V1044 Cen), a symbiotic star located 22 arcsec from the red nova candidate. The X-ray data indicate the presence of a region with a temperature of k T = 0.8 − 0. 1 + 0. 9 keV and a luminosity of 1.4 − 0. 2 + 0. 1 × 1031 erg s −1 in the range 0.3 – 10 keV. The detection of X-rays and modulated UV emission suggests that both components of the binary are chromospherically active. • TYC 7275-1968-1 is a binary eclipsing system suggested as red novae progenitor. • Swift and TESS data are related to red nova progenitor and not for CD-36 8436. • We improved the orbital period of TYC 7275-1968-1 using the TESS data. • The period found is considered as limits to orbital instability. • The X-ray emission originates in a corona around the contact binary. [ABSTRACT FROM AUTHOR]