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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]

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]

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]

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]

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]

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]

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]

X-ray detection and imaging have arose lots of attentions in modern society, due to its stronger penetrating ability. This review highlights the potential of different kinds of halide perovskites for direct X-ray detector and imager, and systematically summaries current progress on them, as well as a brief outlook presents for further boosting their performances. [Display omitted] X-ray detection has significantly applied in medical diagnostics, railway flaw detection, security screening, non-destructive testing in industrial products and quality inspection in food industry et al. Recently, as one of the alternative materials, halide perovskites show great potential in high-performance X-ray detector for their relatively high atomic number, superior carrier life-time produce, tunable band gap, and low temperature fabrication process. Accordingly, based on halide perovskite, some advanced and meaningful work was conducted, and corresponding performances of X-ray detector have reached a comparative height. Herein, we aim at systematically summarizing current progress on halide perovskite based X-ray detectors: (1) First, an introduction of background and key parameters is provided to understand the X-ray detectors clearly; (2) After that, we put an emphasis on the advanced work for various halide perovskites based X-ray detectors. Meanwhile, their optimized strategies and applications in imaging are presented; (3) Finally, the challenges remained and promising opportunities are also presented, for further boosting the performance of halide perovskites based X-ray detectors. [ABSTRACT FROM AUTHOR]

Two-dimensional (2D) hybrid perovskite single crystals are promising photovoltaic materials. However, the single crystals grown from solution usually respond poorly to light and other charged particles. The 2D (BDA)CsPb 2 Br 7 single crystals (BDA = 1,4-butanediamine) are grown from a supersaturated solution. The macroscopical growth steps are present on the surface, leading to a large leakage current during device operation. The surface defects are removed to expose a clean and flat surface. This well-defined crystallographic surface enables an Ohmic contact with the electrode, which minimized the dark current and baseline drift. Consequently, the assembled devices exhibit an enhanced response to LED light and X-rays, revealing the surface defect to be one of the culprits underneath the poor performance of solution-grown perovskite single crystals. • The (BDA)CsPb 2 Br 7 perovskite single crystal was grown by solution cooling method. • Surface defects worsen the detection performance of crystals for photons and X-rays. • A surface treatment method was used to remove defects and improve device performance. [ABSTRACT FROM AUTHOR]

Deep learning-based X-ray detection of hazardous materials is crucial for public safety, as it can automatically detect them in baggage. However, most existing algorithms for X-ray detection rely on supervised learning, necessitating large amounts of labeled data for training. Obtaining such data is challenging due to the unique nature of X-ray safety images, requiring significant time and money investment from trained staff for accurate labeling. In this paper, we propose a new X-ray dangerous goods detection framework called EslaXDET, whose backbone is trained by a hybrid Self-Supervised Learning (SSL) strategy and whose detection head is designed for a non-multistage backbone. First, the hybrid strategy named ESLA is an abbreviation for E nhanced S elf-supervised L earning with masked A utoencoders, which does not require the involvement of labels as it is derived from a hybrid architecture of Contrastive Learning (CL) and Masked Image Model (MIM). Then, the detection head, called Head-Tail Feature Pyramid (HTFP), creates multi-level feature maps comparable to that produced by a multi-level backbone structure by downsampling the output feature of the last stage of the plain Vision Transformers (ViT) multiple times. Finally, the experimental results show that with the backbone of ViT-B, the top-1 accuracy of ESLA on the ImageNet-1K dataset is 77.2%, which is 3% higher than BYOL. Moreover, the average precision (AP, the same evaluation metrics as COCO) of EslaXDET on the PIDray dataset is 69.2%, nearly 8% higher than the original method SDANet, providing a new idea for the subsequent SSL-based X-ray baggage security detection method. [Display omitted] • A new hybrid SSL framework named ESLA. • A new SSL detection framework for X-ray baggage screening named EslaXDET. • A new detector head called HTFP is adapted to a plain ViT. [ABSTRACT FROM AUTHOR]

[Display omitted] CsPbBr 3 -CsPb 2 Br 5 wafer is obtained by water-assisted coprecipitation method, and a spray-coating method is further utilized to convert it into CsPbBr 3 -CsPb 2 Br 5 -CsPbI x Br 3-x composite wafer, which exhibits superior performance and reliability of X-ray detection. • Water-assisted coprecipitation is proposed to prepare high-quality CsPbBr 3 -CsPb 2 Br 5 powder. • CsPbBr 3 -CsPb 2 Br 5 wafer is obtained by pressure-induced aggregation of the powder. • Spray-coating of CsI/H 2 O onto CsPbBr 3 -CsPb 2 Br 5 wafer can convert it into CsPbBr 3 -CsPb 2 Br 5 -CsPbI x Br 3-x composite wafer. • X-ray detector with the composite wafer exhibits much improved performance and reliability. Lead halide perovskite wafers with large lateral size, controllable thickness, and desirable optoelectronic characteristics are promising for X-ray detectors. Herein, CsPbBr 3 -CsPb 2 Br 5 -CsPbI x Br 3-x composite wafers are prepared via water-assisted coprecipitation and spray coating. The preparation involved pressure-induced aggregation of the CsPbBr 3 -CsPb 2 Br 5 powder produced through coprecipitation using of H 2 O/MeOH mixed solvent into CsPbBr 3 -CsPb 2 Br 5 wafers, followed by spraying a CsI/H 2 O solution onto the wafer surface to transform it into a CsPbBr 3 -CsPb 2 Br 5 -CsPbI x Br 3-x composite wafer. Multiple favorable properties, including compact surface, high crystallinity, excellent carrier transportation, large/adjustable size, low cost, and mass producibility, can be identified for the CsPbBr 3 -CsPb 2 Br 5 -CsPbI x Br 3-x composite wafer. An X-ray detector with high performance and excellent stability is realized with this wafer. It yields high resistivity (ρ; 1.3 × 109 Ω cm−2, exceptional carrier mobility (μ)/lifetime (τ) (μτ) product (1.01 × 10−3 cm2 V−1), high sensitivity (20555.1 μC Gy air −1 cm−2), and low detection limit (127.7 nGy s−1). Hence, our research provides a reliable strategy for optimizing the structure and performance of perovskite wafer-based X-ray detectors and enabling mass preparation. [ABSTRACT FROM AUTHOR]

• This work proposes a Modified VGG19 deep-learning architecture to diagnose the Chest X-Rays. • This work computes the essential handcrafted features from the Chest X-Rays. • This work introduces an Ensemble of Features Scheme (EFS) by integrating the deep-features and the handcrafted features. • Serial fusion and PCA based selection is implemented in EFS to choose primary feature set. • Experimental results demonstrate superior performance of Modified VGG19 in comparison with AlexNet, VGG16, VGG19 and ResNet50. Pneumonia is one of the major illnesses in children and aged humans due to the Infection in the lungs. Early analysis of pneumonia is necessary to prepare for a possible treatment procedure to regulate and cure the disease. This research aspires to develop a Deep-Learning System (DLS) to diagnose the lung abnormality using chest X-ray (radiograph) images. The proposed work is implemented using; (i) Conventional chest radiographs and (ii) Chest radiograph treated with a threshold filter. The initial experimental evaluation is carried out using the traditional DLS, such as AlexNet, VGG16, VGG19 and ResNet50 with a SoftMax classifier. The results confirmed that, VGG19 provides better classification accuracy (86.97%) compared to other methods. Later, a customized VGG19 network is proposed using the Ensemble Feature Scheme (EFS), which combines the handcrafted features attained with CWT, DWT and GLCM with the Deep-Features (DF) achieved using Transfer-Learning (TL) practice. The performance of customized VGG19 is tested using different classifiers, such as SVM-linear, SVM-RBF, KNN classifier, Random-Forest (RF) and Decision-Tree (DT). The result confirms that VGG19 with RF classifier offers better accuracy (95.70%). When the similar experiment is repeated using threshold filter treated chest radiographs, the VGG19 with RF classifier offered superior classification accuracy (97.94%). This result confirms that, proposed DLS will work well on the benchmark images and in the future, it can be considered to diagnose clinical grade chest radiographs. To create your abstract, type over the instructions in the template box below. Fonts or abstract dimensions should not be changed or altered. Image, graphical abstract [ABSTRACT FROM AUTHOR]

Silicon carbide fibre/silicon carbide (SiC f /SiC) composites are important for manufacturing the hot-section components of aero engines and supersonic vehicles. Hence, quality control, as well as qualitative and quantitative non-destructive testing and evaluation (NDT&E) are critical. A grey (G) value method for the characterisation and NDT&E of manufacturing defects in SiC f /SiC composites based on the attenuation behaviour of low-energy X-rays was proposed, and a digital X-ray imaging detection system was developed. Specimens with artificial and manufacturing defects were evaluated, thereby revealing that imperfections were induced when the SiC f /SiC composites were formed at the high-temperatures; microcracks (100-μm-wide) and rectangular defects (0.1-mm-deep) were detected with a sensitivity exceeding 100 μm. Our results demonstrated that 'voids', 'microcracks', 'porosity', 'polymer impregnation inhomogeneity', 'fibre-lack', and 'gap-delamination' were the typical manufacturing defects caused during formation of SiC f /SiC composites at high temperatures; the minimum deviation between the detected and designed length of a 10-mm-long microcrack in the 3.0-mm-thick SiC f /SiC composite specimen was ~3%; the manufacturing defects were effectively characterised and evaluated using the distribution behaviours of G values and digital radiographic imaging features. Image 1 [ABSTRACT FROM AUTHOR]

State-of-the art X-ray imaging cameras using silicon sensors for X-ray detection have demonstrated a frame-rate of 10 MHz and excellent performance for X-ray energies below 20 keV. We proposed a pixelated ultrafast inorganic scintillator-based front imager for GHz hard X-ray imaging. The proposed imager is featured with a total absorption for hard X-ray photons, and provides sub-ns scintillation pulse width crucial for X-ray bunches of a few ns spacing foreseen at the proposed MaRIE facility. We measured temporal response of a dozen ultrafast and fast inorganic scintillators at the 10-ID-B site of the Advanced Photon Source (APS) of ANL. Crystal's response to hybrid X-ray beam of 30 keV, consisting of singlet bunches of 50 ps width and septuplet bunches of 27 ps width with 2.83 ns bunch spacing, was measured. Ultrafast inorganic scintillators, such as BaF 2 :Y and ZnO:Ga, show clearly resolved X-ray bunches for septuplets, as well as no degradation of amplitude for continuous eight septuplets, providing a proof of principle for the ultrafast inorganic scintillator-based total absorption front imager for the proposed MaRIE project. [ABSTRACT FROM AUTHOR]

[Display omitted] • WO 3 shows X-Ray induced photochromic properties by W6+ to W5+. The transformation of tungsten oxide from yellow (without X-ray) to blue green (60 min) under X-ray radiation of varying duration, and it is a continuous process. Under X-ray irradiation treatment, some of the W-O bonds break, causing the oxygen molecules to leave the surface lattice and creating oxygen vacancies. One oxygen vacancy in WO 3 generally causes two electrons, which reduces W6+ ions into W5+. The product is H x WO 3 , resulting in a reduction in the crystalline volume and band gap of the sample. Simultaneously thermally annealed pre- and post-X-ray irradiation samples, both of which are the same color after cooling. This new finding extends the photochromic energy range of tungsten oxide and has important implications for the design and fabrication of other X-ray-induced photochromic materials for charge transfer, which will certainly benefit the development of next-generation X-ray detection materials. [ABSTRACT FROM AUTHOR]

Metal halide perovskites have gained significant attention as promising materials for ionizing radiation detection due to their facile fabrication process, exceptional optoelectronic properties and high attenuation coefficients. To effectively absorb the incident X-ray photons, thick active layers have been reported and fabricated via spray-coating. However, the conventional spray-coating method is susceptible to various adverse effects, making it challenging to achieve high-quality thick perovskite films. In this work, we propose the use of antisolvent-assisted spray-coating to deposit perovskite films, which results in small surface roughness, thick films on various substrates. The slow growth of the thick film and the ability to regulate its crystallization through the modulation of processing atmosphere were also carefully studied. The optimized X-ray detector demonstrated a sensitivity of up to 3370.8 μC Gy air −1 cm−2, demonstrating its great potential for X-ray detection applications. • Anti-solvent spray-coating technique was established to deposit perovskite thick films. • The spray-coating process was systematically investigated and optimized. • Optimized devices based on antisolvent-assisted X-ray detectors are promising for real applications. [ABSTRACT FROM AUTHOR]

Synergistic nanostructures possess enriched electrical and optical properties compared to conventional nanostructures. 1D - 3D synergized nanostructure was implied to elucidate the performance of the X-ray sensor for the first time. Current research in X-ray detection only focuses on implementing high attenuating material based on oxides/ perovskites in developing X-ray sensors. Herein we approached tailoring the performance of an X-ray sensor with a synergistic nanostructure composed of sodium vanadium oxide (NaV 3 O 8) with substantial grain boundary (GB) segregation of silver bismuth sulfide (AgBiS 2) , enabling the structured arrangement of nanostructured grains at the surface of NaV 3 O 8 nanorods. Then, it was coated as a thick film on top of the interdigitated electrodes by glass rod sliding technique to readout the dose-dependent X-ray sensing capability. From the X-ray impinged photocurrent characteristics, the sensor with 75 wt% AgBiS 2 segregated NaV 3 O 8 exhibits superior sensitivity 82.6 nC mGy−1 cm−2 and low-noise equivalent dose rate 1.04 mGy Hz−0.5 for 2.49 mGy s−1 than other compositions. These experimental findings explore the implication of synergistic nanostructures as active layers in direct conversion X-rays sensors for improved charge extraction and enhancement in X-ray impinged photocurrent at low dose rates. [Display omitted] • AgBiS 2 :NaV 3 O 8 segregated synergistic nanostructures with (100:0 wt%); (75:25 wt%); (50:50 wt%); (25:75 wt%) compositions was used to fabricate low-dose X-ray sensors. • X-ray impinged photocurrent characteristics reveal that X-ray sensors based on (25:75 wt%) NaV 3 O 8 : AgBiS 2 exhibit low dark current of 10-8A at 2 V bias condition. • Our device exhibit sensitivity of (82.6 nC mGy-1 cm-2) and NED (1.04 mGy Hz-0.5) at 2.49 mGy s-1 dose rate. [ABSTRACT FROM AUTHOR]

• In this research, we introduced a novel TB-UNet based on dilated fusion block (DF) and Attention gate (AG) mechanism for accurate segmentation of lung regions. • We also proposed TB-DenseNet, which is based on five dual convolution blocks, DenseNet-169 layer, and a feature fusion block for the precise classification of tuberculosis images. • The experiments have been performed on three chest X-ray (CXR) datasets, segmented images, and original images are fed to TB-DenseNet for better classification. Tuberculosis still significantly impacts the world's population, with more than 10 million people getting sick each year. Researchers have focused on developing computer-aided diagnosis (CAD) technology based on X-ray imaging to support the identification of tuberculosis, and deep learning is a popular and efficient method. However, deep learning-based CAD approaches usually ignore the relationship between the two vision tasks of specific region segmentation and classification. In this research, we introduced a novel TB-UNet, which is based on dilated fusion block (DF) and Attention block (AB) block for accurate segmentation of lungs regions and achieved the highest results in terms of Precision (0.9574), Recall (0.9512), and F1score (0.8988), IoU (0.8168) and Accuracy (0.9770). We also proposed TB-DenseNet which is based on five dual convolution blocks, DenseNet-169 layer, and a feature fusion block for the precise classification of tuberculosis images. The experiments have been performed on three chest X-ray (CXR) datasets, segmented images, and original images are fed to TB-DenseNet for better classification. Furthermore, the proposed method is tested against simultaneously three different diseases, such as Pneumonia, COVID-19, and Tuberculous. The highest results are achieved in terms of Precision (0.9567), Recall (0.9510), F1score (0.9538), and Accuracy (0.9510). The achieved results reflect that our proposed method produces the highest accuracy compared to the state-of-the-art methods. The source code is available at: https://github.com/ahmedeqbal/TB-DenseNet. [ABSTRACT FROM AUTHOR]

• X-ray-responsive PNIPAm-based microgels are obtained. • Diselenide/ditelluride crosslinkers are synthesized. • PNIPAm microgel-based interferometers are generated. • Interferometers can respond to 0–50 Gy X-rays with tunable colors. • Interferometers show ultrahigh sensitivity of 101.63 nm/Gy. We report the successful development of novel microgel-based interferometers for X-ray dose sensing, which can meet fast-developing and widespread applications of ionizing radiation. Poly(N-isopropylacrylamide) (pNIPAm)-based microgels are crosslinked by different molecules (i.e., N, N'-methylenebisacrylamide (BIS), N, N'-bis(acryloyl)cystamine (BAC), bis(2-acrylamidoethyl) diselenide (BASe), and bis(2-acrylamidoethyl) ditelluride) (BATe). These color-tunable photonic materials are generated by sandwiching X-ray-responsive microgels between two Au layers. The radiolysis of an aqueous solution by X-ray irradiation yields •OH radicals, leading to the cleavage of crosslinkers of pNIPAm-based microgels. The chemical reaction induces the swelling of microgels, increasing the distance between the two Au layers of the interferometers. Eventually, the optical signal of the device (i.e., reflectance spectra and color) varies with the X-ray dose, showing an ultrahigh sensitivity of 101.63 nm/Gy. For the first time, our work provides novel microgel-based interferometers for spectral and visual X-ray dose detection via the chemical–mechanical-optical signal transduction strategy. [ABSTRACT FROM AUTHOR]

Nanocrystalline materials have garnered significant recognition in the scientific and research community for developing X-ray sensors. The applicability of bismuth-based binary and ternary compounds has been extensively studied in X-ray imaging and cancer therapy applications owing to their high attenuation. Among the binary and ternary compounds of bismuth, the n-type semiconductor silver bismuth sulfide (AgBiS 2) was studied for the detection of X-rays at lower doses, based on its total attenuation (μ = 3.07 cm2 g−1 at 70 keV), density (ρ = 7.02 g cm−3), and bandgap (E g = 1.21 eV). The effect of grain size on X-ray sensing performance was examined to validate the effective size required for maximum attenuation of X-rays and successful extraction of induced mobility carriers. X-ray sensors with four different AgBiS 2 grain sizes were cast on interdigitated electrodes (IDEs) and subjected to different doses of X-rays at 2 V bias to study its dose-dependent X-ray sensing nature using an intra-oral (70 kVp-AC) X-ray machine. AgBiS 2 -based X-ray sensor exhibited the highest sensitivity of 20.13 μC mGy−1 cm−3 with the lowest Noise-equivalent dose ratio (NED) of 0.08 μGy Hz−0.5, 0.20 mGy detection limit and a response time of 0.12 s. This outcome validates that AgBiS 2 can be applied as a potential replacement for perovskites in direct X-ray detection. [Display omitted] • Grain size effect on nano AgBiS 2 was studied for direct conversion X-ray detection at 70 keV X-ray photon energy. • As-prepared AgBiS 2 was heat treated at 150 °C for 15, 60, 90, and 180 min to study the grain size effect. • AgBiS 2 with 54 nm size exhibits superior sensitivity (20.13 μC mGy−1 cm−3), NED (5 μGy Hz−0.5) and swift response (0.12 s) for 7.97 mGy dose. [ABSTRACT FROM AUTHOR]

X-ray detectors have drawn great attention due to their wide applications in medical imaging and industrial inspection. Lead halide perovskite exhibits excellent X-ray detection merits because of its high-Z element and outstanding photoelectric properties. However, the perovskite-based X-ray detectors exhibit poor stability, low resistivity and large dark leakage current due to the soft lattice and ion migration of perovskite materials. Herein, we used Ga 2 O 3 compact layer to form a heterojunction structure with formamidinum lead iodide (FAPbI 3) to largely ease these issues. Compared with the bare FAPbI 3 detector, the dark current of the FAPbI 3 /Ga 2 O 3 heterojunction detector is reduced by 3 orders of magnitude and the photo-to-dark current ratio (PDCR) increased by 31-fold. The detection limit of 0.23 mGys−1 is obtained which is 20 times lower than the FAPbI 3 detector and short response time of 20 ms is obtained. More importantly, the FAPbI 3 /Ga 2 O 3 device exhibits better repeatability due to the suppression of ion migration by Ga 2 O 3. This work provides an effective strategy to obtain low dark current and stable perovskite-based photodetector. • A coplanar interdigital MSM-structured X-ray detector was fabricated based on FAPbI 3 /Ga 2 O 3 heterojunction. • Low dark current density (4.1 pAmm−2), high PDCR (433) and low detection limit (0.23 mGys−1) were obtained. • The performance improvement of the device is due to the suppression of iodine ions migration by compact Ga 2 O 3. [ABSTRACT FROM AUTHOR]

Semiconductor sensors based on the rad-optic effect enable ultra-fast detection of X-rays and play an important role in fusion diagnostics. Obtaining the responsivity of the semiconductor ultrafast response material is an important part of characterization. In this work, the refractive index change mechanism of the semiconductor under X-ray irradiation was analyzed, and the quantitative relationship between the diffraction efficiency and the X-ray photon energy was established through the LT-AlGaAs diffraction imaging experiments. The impulse responses of LT-AlGaAs under 1 keV–10 keV X-ray radiation were calculated, revealing the variation of responsivity with radiated photon energy. Imaging experiments of LT-AlGaAs were performed by bombarding an Al target to generate 1.5 keV X-rays. The diffraction images were obtained in agreement with the simulations. The responsivity of the semiconductor chip increases with the square of the incident X-ray power density. This study provides meaningful analyses for the development of ultra-fast X-ray imaging systems based on the rad-optic effect. [ABSTRACT FROM AUTHOR]

The first results on betatron radiation obtained in laser-plasma acceleration experiments at the FLAME laser facility are presented. The diagnostic apparatus for the X-ray detection available at the facility is described together with the experimental setup for the generation of betatron radiation. [ABSTRACT FROM AUTHOR]

In this paper, we present a multi-voltage threshold (MVT) digitizer using a time-varied threshold and investigate the feasibility of using this digitizer to develop the data acquisition system for photon-counting X-ray security inspection imaging. This digitizer compares the scintillation pulse with a preset time-varied voltage signal and records the time information of the intersections. As the amplitude of the threshold varies as a function of time, the voltage values of the intersections could be calculated using the recorded time, and the energy information could be extracted via the acquired time–voltage samples. Unlike the constant voltage thresholds MVT digitizer requiring multiple voltage comparators, this method needs only one voltage comparator, which notably reduces the complexity in configuration. We demonstrate the development of such an MVT digitizer using a sine signal threshold and evaluate its energy performance with a yttrium orthosilicate (YSO) scintillator and Silicon Photomultiplier (SiPM) detector (designed for X-ray detection). The digitizer obtains energy resolutions of 41.4%, 26.6%, and 25.5% at 30, 59.5, and 80.9 keV, respectively. For comparison, the YSO/SiPM detector is also evaluated with a high-speed oscilloscope, and measured energy resolutions are 40.6%, 26.5%, and 25.1% at 30, 59.5, and 80.9 keV, respectively. These results indicate that the proposed MVT digitizer using a time-varied threshold is a promising method for developing a YSO/SiPM-based photon-counting X-ray detector. [ABSTRACT FROM AUTHOR]

Lung nodule detection in chest X-ray (CXR) images is common to early screening of lung cancers. Deep-learning-based Computer-Assisted Diagnosis (CAD) systems can support radiologists for nodule screening in CXR images. However, it requires large-scale and diverse medical data with high-quality annotations to train such robust and accurate CADs. To alleviate the limited availability of such datasets, lung nodule synthesis methods are proposed for the sake of data augmentation. Nevertheless, previous methods lack the ability to generate nodules that are realistic with the shape/size attributes desired by the detector. To address this issue, we introduce a novel lung nodule synthesis framework in this paper, which decomposes nodule attributes into three main aspects including the shape, the size, and the texture, respectively. A GAN-based Shape Generator firstly models nodule shapes by generating diverse shape masks. The following Size Modulation then enables quantitative control on the diameters of the generated nodule shapes in pixel-level granularity. A coarse-to-fine gated convolutional Texture Generator finally synthesizes visually plausible nodule textures conditioned on the modulated shape masks. Moreover, we propose to synthesize nodule CXR images by controlling the disentangled nodule attributes for data augmentation, in order to better compensate for the nodules that are easily missed in the detection task. Our experiments demonstrate the enhanced image quality, diversity, and controllability of the proposed lung nodule synthesis framework. We also validate the effectiveness of our data augmentation strategy on greatly improving nodule detection performance. • Lung nodule synthesis framework disentangles nodule attributes to the shape, the size, and the texture, respectively. • Applying modulated shape mask provides diverse variation of nodule shape and quantitative control of nodule size. • Data augmentation based on the controllability of lung nodule synthesis effectively improves lung nodule detection. [ABSTRACT FROM AUTHOR]

Pneumothorax can be life-threatening if not diagnosed on time. Most of the research studies for pneumothorax detection in chest X-rays (CXR) images have applied the transfer learning approach. In this study, we have explored the parameter-efficient attention based lightweight convolutional neural network (ALCNN) for pneumothorax detection in CXR images. It has stacked convolutional layers with the attention mechanism to re-calibrate channel-wise feature maps. Furthermore, we have also evaluated three different transfer learning approaches to compare the performance with ALCNN. The ALCNN has obtained the comparable results with 10x fewer parameters in comparison to VGG-19 and ResNet-50 architectures. The ALCNN achieved a 0.73 sensitivity and an area under curve (AUC) of 0.79 on the held-out test set. While pre-trained and fine-tuned, VGG, 19, achieved a sensitivity value of 0.52 and 0.71 and an AUC value of 0.72 and 0.81, respectively. Similarly, pre-trained and fine-tuned ResNet-50 achieved a sensitivity value of 0.69 and 0.74 and an AUC value of 0.77 and 0.80, respectively. In the third transfer learning approach, VGG, 19, and ResNet-50 obtained sensitivity values of 0.65 and 0.69, respectively, while the AUC value of 0.79 for both VGG-19 and ResNet-50. The results obtained in our study show that transfer learning did not have a significant impact on performance for pneumothorax detection in CXR. [Display omitted] • Parameter-efficient ALCNN model is proposed for pneumothorax detection in chest X-rays. • The ALCNN obtained comparable results with ten times less parameters when compared with three transfer learning approaches on two deep architectures. • Obtained results show that the transfer learning approaches did not have a significant effect on the performance for pneumothorax detection. [ABSTRACT FROM AUTHOR]

Recently, semiconductive polymeric materials have attracted attention as an active layer for detecting ionizing radiation because of their excellent properties such as flexibility, easy production, solution processability and low-cost production. This paper presents X-ray detection properties of Poly(3-hexylthiophene) (P3HT):Phenyl C61 butyric acid methyl ester (PCBM) blend structure with different PCBM loading ratios. P3HT:PCBM mixing ratio was changed from 1:0 to 1:2. Top contact of the pure and blend structured device were produced by using a solution based graphite ink. Devices were constructed with vertical bulk resistive architecture within an ohmic electrode structure as ITO/PEDOT:PSS/P3HT:PCBM/Graphite configuration. Graphite electrode was coated on the active layer with the spray coating method. All devices exhibited ohmic current-voltage (I–V) characteristics. The blend structured devices exhibited stable saw-tooth type behaviour in photocurrent responses against the on and off states of X-rays. Saw-tooth type responses could be evaluated as major evidence for a potential usage of organic electronic device technology direct radiation detectors. Although the best sensitivity value to X-ray was obtained with the blend structure with equal ratio, it was observed that the rise and decay times were shortened with the increase in the amount of PCBM in the blend structure from. [Display omitted] • P3HT:PCBM active layer based X Ray detectors. • Spray coated graphite electrode was used as the top ohmic contact for all devices. • P3HT:PCBM ratio was changed as (1:0), (1:0.5), (1:1), (1:2). • Best sensitivity value to X-ray was obtained with the blend structure with equal ratio of PCBM and P3HT (1:1). [ABSTRACT FROM AUTHOR]

The aims of this study is to improve the sensitivity of indirect X-ray detectors by investigating the properties and application of ternary-blended organic active layers. The ternary-blended active layers studied were composed of conjugated polymer PBDB-T-2F as the donor (D1), non-fullerene Y6 as the first acceptor (A1) and ITIC-4F as the second acceptor (A2). The structural similarity between the two acceptors allows the advantage formation of a homogeneous acceptor phase and results in good film morphology. Another advantage of our approach is the electrical and optical characteristics of the active layer can be modulated based on the mixing ratio of the two acceptors. To find the optimal ternary blending, the content of D1 was fixed while the A1:A2 content ratio was adjusted. The CsI (Tl) scintillator-coupled detector with an active layer of PBDB-T-2F:Y6:ITIC-4F = 1.0:0.6:0.4 achieved the highest sensitivity of 4.27 × 103 μC∙Gy air −1∙cm−2 giving respective improvements of 27.10% and 43.92% compared to binary-blend PBDB-T-2F:Y6 = 1:1 and PBDB-T-2F:ITIC-4F = 1:1. Next, the active layer's spin-coating conditions and the bias conditions were examined to further improve the sensitivity of the detector. Finally, the detector with a PBDB-T-2F:Y6:ITIC-4F = 1.0:0.6:0.4 active layer was shown to have the highest sensitivity of 5.42 × 103 μC∙Gy air −1 cm−2 at a bias of – 1.6 V with a 97 ± 2 nm thick active layer. The aims of this study are to improve the sensitivity of indirect X-ray detectors by investigating the properties of ternary-blended organic active layers. The structural similarity between the two acceptors allows the advantage formation of a homogeneous acceptor phase and results in good film morphology. Another advantage of our approach is the electrical and optical characteristics of the active layer can be modulated based on the mixing ratio of the two acceptors. The CsI (Tl) scintillator-coupled detector with ternary-blended active layer giving respective improvements of 27.10% and 43.92% compared to binary-blended active layer. [Display omitted] • To improve the sensitivity of the X-ray detector, a ternary-blend strategy was applied to the organic active layer. • The X-ray detector using ternary-blended active layer shown 27.10% and 43.92% higher sensitivity compared to their respective binary combinations (PBDB-T-2F:Y6 and PBDB-T-2F:ITIC-4F). • The indirect-type X-ray detector using PBDB-T-2F:Y6:ITIC-4F = 1.0:0.6:0.4 ternary-blended active layer was achieved a high sensitivity of 5.42 × 103 μC∙Gy air −1∙cm−2. [ABSTRACT FROM AUTHOR]

Semiconductor-based direct conversion X-ray sensors have widespread applications spanning from medical diagnosis to industrial inspection. However, current findings on X-ray detection based on perovskites shows high sensitivity but exhibit large leakage current and poor stability, thus, inhibiting them from commercialization. Highly stable AgBiS 2 with large attenuation coefficient (μ = 3.07 g cm−2 at 70 keV), shows excellent charge conversion due to its higher atomic number (Bi, Z = 83), and density (ρ = 7.02 g cm−3) was used for X-ray detection. Here, we approach to enhance the net sensitivity of AgBiS 2 by tailoring all three parameters by segregating micro/ nanocrystals of cerium oxide (CeO 2) at the AgBiS 2 grain boundary (GB) region. From the X-ray impinged photocurrent response, substantial GB segregation of n-CeO 2 at the AgBiS 2 interface leads to improved attenuation and promotes the conversion of multiple scattered X-ray photons into electrons by interacting with the adjacent grains, thus resulting in enhanced photocurrent generation. The sensitivity (S) and noise equivalent dose (NED) ratio were calculated to determine the lowest detectivity of the sensor with less generated noise signals. From these experimental findings, 10 % of n-CeO 2 segregation leads to an improvement in the sensitivity of AgBiS 2 to 29 μC mGy−1 cm−3. [Display omitted] • X-ray sensors were fabricated with micro/ nano CeO 2 segregated AgBiS 2 thick films. • Multiple scattered X-ray photons at the AgBiS 2 grain boundary region were effectively utilized by nano CeO 2 grains, resulting in higher charge carrier generation. • X-ray impinged photocurrent measurement revealed nano CeO 2 :AgBiS 2 presents record sensitivity 29.3 μC mGy−1 cm−3 for 7.97 mGy dose. [ABSTRACT FROM AUTHOR]

Organometal halide perovskites have proven to be potential materials for X-ray detection due to their great photoelectric properties, high radiation attenuation and low-cost preparation. However, ion migration is one of the obstacles for its applications, especially, ion migration via surface is much easier in single crystal materials than bulk diffusion which could significantly degrade the device performances. In this paper, the KCl passivation layer is prepared by the thermal evaporation method and inserted between crystal and electrode The trap density and μ τ product of pristine and KCl passivated MAPbI 3 devices are compared, and the results demonstrate KCl as a passivation layer can effectively passivate the surface traps and improve electrical performance. The KCl passivated MAPbI 3 detector exhibits a high X-ray sensitivity of 3700 μ C Gy air − 1 cm −2 under −20 V bias. [ABSTRACT FROM AUTHOR]

To obtain both a high count rate of >10 7 s −1 and a detection efficiency sufficient for high-energy X-rays of >30 keV, we propose a scintillation timing detector using a proportional-mode silicon avalanche photodiode (Si-APD) for synchrotron radiation nuclear resonant scattering. We here present results obtained with a prototype detector using a lead-loaded plastic scintillator (EJ-256) mounted on a proportional-mode Si-APD (active area size: 3 mm in diameter). The detector was operated at ‒35 °C for a better signal-to-noise ratio. Using synchrotron X-rays of 67.41 keV, which is the same energy as the first excited level of 61 Ni, we successfully measured pulse-height and time spectra of the scintillation light. A good time resolution of 0.50±0.06 ns (full width at half-maximum) was obtained for 67.41 keV X-rays with a scintillator 3 mm in diameter and 2 mm thick. [ABSTRACT FROM AUTHOR]

A new 1D coordination polymer [Pb(adba)(DMF)] n exhibits the competitive sensitivity, detection limit and radiation stability responsive to X-ray and could serve as a promising scintillating material candidate for X-ray detection in highly irradiating conditions. [Display omitted] • A new X-ray responsive 1D coordination polymer [Pb(adba)(DMF)] n (named as Pb-adba , H 2 adba = 4,4′-(9,10-anthracenediyl)dibenzoic acid, DMF = N , N -dimethylformamide) was constructed with Pb(II) salt and H 2 adba by a mild solvothermal process. • Pb-adba exhibits the competitive sensitivity and detection limit toward X-ray than classical scintillators PbWO 4 (PWO), anthracene and some reported SMOFs. • Pb-adba possess favorable radiation stability at the dose rate of 42.29 mGy/s for 3 h (equivalent to the cumulative dose of 456 Gy). The strong X-ray attenuation and beneficial optoelectronic properties of lead(II)-based coordination polymers (CPs) materials have aroused great interest in the field of radiation detection. In this work, a X-ray responsive scintillating 1D Pb(II)-CP [Pb(adba)(DMF)] n (named as Pb-adba , H 2 adba = 4,4′-(9,10-anthracenediyl)dibenzoic acid, DMF = N , N -dimethylformamide) with favourable irradiation stability was synthesized by the self-assembly approach, which exhibits competitive sensitivity and detection limit toward X-ray than classical scintillators PbWO 4 (PWO), anthracene and some reported SMOFs. [ABSTRACT FROM AUTHOR]

During storage and long-distance refrigerated transport, low temperatures may lead to invisible freezing injury, which lowers the overall fruit quality and shortens storage time. As a result, nondestructive evaluation of freezing injury is necessary to evaluate the quality of fruit. The freezing injury of pear Xinli No.7 was experimentally investigated using X-ray technology and scanning electron microscope (SEM). It was found that the gray value of the freezing region in the X-ray image of pear was higher than that of the healthy region, based on which the freezing injury could be distinguished nondestructively. Besides, the area of the freezing region increased linearly with the decrease of the freezing temperature and the gray value increased monotonically when the freezing time increases. Based on the observation of the micro-structure of the freezing pear using an electron microscope, the variation of the gray value is due to the changes of the cavities formed by ice crystals, increasing with the degree of freezing injury. This study explored the X-ray images to determine the severity of pear freezing injury and revealed the mechanism of X-ray variation caused by freezing injury, which is conducive to determining the freezing time and temperature for the purpose of preservation, reducing storage cost and optimizing long-distance refrigerated transportation. • Freeze injury causes X-ray change. • X-ray detects freeze degree. • Cavity affects X-ray. [ABSTRACT FROM AUTHOR]

• A cascade framework is proposed for automatic lung segmentation in CXRs. • An adaptive closed polyline searching method is used to obtain data sequence. • An improved machine learning model is proposed to express a mathematical model. • The explainability-guided mathematical model is used to denote lung contour. • Performance of the proposed method is evaluated on public multi-site datasets. Large variations in anatomical shape and size, too much overlap between anatomical structures, and inconsistent anatomical shapes make accurate lung segmentation in chest x-rays (CXR) a challenging problem. In this paper, we propose an automatic method called A-LugSeg that consists of two subnetworks for lung segmentation in CXRs. The first is a segmentation subnetwork based on a deep learning model (i.e., Mask-RCNN), which completes a coarse segmentation for each input CXR image. The second is a refinement subnetwork designed to optimize the coarse segmentation result by combining an improved closed principal curve method and an enhanced machine learning, where the lung contour's explainability-guided mathematical model is expressed by the machine learning's parameters. The performance of the proposed method is evaluated on three public datasets, namely the ShenZhen hospital Chest X-ray dataset (SZCX), Japanese Society of Radiological Technology dataset (JSRT), and Montgomery County chest x-ray dataset (MC), which contain the 662 CXRs, 247 CXRs, and 138 CXRs, respectively. We used different datasets for training/validation (SZCX) and testing (SZCX/JSRT/MC). Furthermore, we used six evaluation metrics to evaluate the performance of our proposed method, including Dice Similarity Coefficient (DSC), Jaccard Similarity Coefficient (Ω), Accuracy (ACC), Precision, Sensitivity, and Specificity. The obtained results (DSC = 0.973, Ω = 0.958, ACC = 0.972, and p -value for DSC < 0.001) for JSRT, (DSC = 0.971, Ω = 0.955, ACC = 0.97, and p -value for DSC < 0.001) for MC, (DSC = 0.972, Ω = 0.956, and ACC = 0.97) for hybrid datasets (JSRT + MC), and (Precision, Sensitivity, and Specificity are higher than 0.98) show the superior performance of the proposed dual subnetwork segmentation algorithm compared to the existing state of the art approaches. [ABSTRACT FROM AUTHOR]

• PL, XEL and sensing properties of Er3+ and Er3+/Yb3+ doped Gd 2 Zr 2 O 7 are studied. • A good radiation resistance is realized for these samples with pyrochlore structure. • Er3+ emissions keep stable under continuous X-ray excitation. • FIR of 2H 11/2 to 4S 3/2 is insensitive to excitation powers with S r-max of 1.1% K−1. • Er3+/Yb3+: Gd 2 Zr 2 O 7 can be used for optical thermometry and X-ray detection. A series of Er3+-doped and Er3+-Yb3+ co-doped Gd 2 Zr 2 O 7 phosphors were synthesized via hydrothermal method, and their multifunctional properties were studied in detail. The Raman spectra indicated that the products were the ordered pyrochlore phase of Gd 2 Zr 2 O 7 , which exhibited a good radiation resistance. The up-conversion (UC), down-conversion (DC) photoluminescence (PL) and X-ray excited luminescence (XEL) spectra of the Er3+: Gd 2 Zr 2 O 7 samples showed the similar spectra profiles, which were composed of the prominent green (2H 11/2 /4S 3/2 →4I 15/2) and weak red (4F 9/2 →4I 15/2) emissions. The co-doping of Yb3+ ions was beneficial for the improvement in UC PL but led to the reductions in DC PL and XEL. Besides, the X-ray induced green emissions demonstrated a high-sensitivity to the dose rate and a long-term stability against the continuous X-ray irradiation. Moreover, using the fluorescence intensity ratio (FIR) technique, the temperature sensing behaviors were analyzed based on the thermally coupled levels (TCLs) 2H 11/2 and 4S 3/2 of Er3+. The FIRs were found to be insensitive to the excitation power variation, and the optimal relative sensing sensitivity reached ~1.1%K−1 at 298 K. These characteristics may enable the studied system applicable for optical thermometry, X-ray detection and X-ray imaging. [ABSTRACT FROM AUTHOR]

For the research on alpha emitters used for targeted alpha particle therapy such as astatine-211 (211At), alpha particle as well as X-ray imaging are required for autoradiography and phantom imaging or in vivo imaging of small animals. Consequently, two imaging detectors for different types of radiations are required in such research. However, preparing two types of imaging detectors needs cost and space. If a single imaging detector could image alpha particles as well as X-rays for 211At, it would be an advance in the imaging research for targeted alpha particle therapy. Consequently, we developed a detector that can be used for both alpha particle and X-ray imaging. The developed imaging detector is a phoswich type made of a ZnS(Ag) sheet and a cerium doped YAlO 3 (YAP(Ce)) plate optically coupled to each other with a 1-mm-thick light guide between scintillators. These scintillators were optically coupled to a 1-inch-square position-sensitive photomultiplier tube (PSPMT) to form an imaging detector. The ZnS(Ag) sheet detects alpha particles while the YAP(Ce) plate detects X-rays from 211At. Due to the pulse height difference between alpha particles and X-rays, a different high voltage was supplied to the PSPMT for alpha particle and low-energy X-ray detection. Discrimination between alpha particles and X-rays were conducted by pulse height as well as pulse shapes of ZnS(Ag) and YAP(Ce). The intrinsic spatial resolution for 5.5-MeV alpha particles was better than 0.6 mm the full width at half maximum (FWHM), while that for 60-keV gamma photons was ∼1.2 mm FWHM. Energy resolution for 5.5-MeV alpha particles was 60% FWHM, while that for 60-keV gamma photons was 25% FWHM. With a 4-mm-thick, 0.6-mm-diameter parallel hole collimator mounted on the detector, the system spatial resolution for 60-keV gamma photons was ∼2 mm FWHM within 5 mm from the collimator surface, and its sensitivity was 0.5%. An image of the 211At alpha particle distribution of a sliced kidney as well as an X-ray image of a paper soaked with 211At solution could be obtained. We conclude that the developed detector is promising for single-detector imaging of alpha particles as well as X-rays from 211At. • A phoswich detector composed of ZnS(Ag) and YAP(Ce) for astatine-211 imaging was developed for both alpha particles and X-rays. • An image of the At-211 alpha particle distribution as well as an X-ray image could be obtained. • The developed detector is promising for imaging of alpha particles as well as X-rays from At-211. [ABSTRACT FROM AUTHOR]

• Intracranial vessel perforation is a serious complication in EVT, procedural success may benefit from fast automated detection. • Automatic intracranial vessel perforation detection in DSA is studied for the first time. • Perforations are pooled from multiple (inter-)national clinical trials/registries. • Learning perforation progression characteristics as well as ensemble modeling improves performance. • The methods reach human expert level performance in perforation detection. [Display omitted] Intracranial vessel perforation is a peri-procedural complication during endovascular therapy (EVT). Prompt recognition is important as its occurrence is strongly associated with unfavorable treatment outcomes. However, perforations can be hard to detect because they are rare, can be subtle, and the interventionalist is working under time pressure and focused on treatment of vessel occlusions. Automatic detection holds potential to improve rapid identification of intracranial vessel perforation. In this work, we present the first study on automated perforation detection and localization on X-ray digital subtraction angiography (DSA) image series. We adapt several state-of-the-art single-frame detectors and further propose temporal modules to learn the progressive dynamics of contrast extravasation. Application-tailored loss function and post-processing techniques are designed. We train and validate various automated methods using two national multi-center datasets (i.e., MR CLEAN Registry and MR CLEAN-NoIV Trial), and one international multi-trial dataset (i.e., the HERMES collaboration). With ten-fold cross-validation, the proposed methods achieve an area under the curve (AUC) of the receiver operating characteristic of 0.93 in terms of series level perforation classification. Perforation localization precision and recall reach 0.83 and 0.70 respectively. Furthermore, we demonstrate that the proposed automatic solutions perform at similar level as an expert radiologist. [ABSTRACT FROM AUTHOR]

Abstract: The properties of a novel X-ray diffraction (XRD) technique having very low sensitivity to the sample morphology were previously elucidated through theoretical considerations and model simulations (Hansford, 2011 [1]). This technique opens up the possibility of mineralogical analysis by XRD without sample preparation. Here, the results of proof-of-principle experimental tests are presented. Two sets of experiments were performed using a vacuum chamber equipped with an X-ray tube source, sample holder and charge-coupled detector. Firstly, a pressed-powder pellet of α-quartz was placed in three different positions relative to the X-ray source and detector. The changes in position represent gross sample movements which would be inconceivable in conventional XRD analysis. The resulting back-reflection energy-dispersive spectra show a very high degree of correspondence other than an overall intensity factor dependent on the distance between the sample and detector. Secondly, the back-reflection spectrum of an unprepared limestone hand specimen, having mm-scale surface morphology, was compared to the spectrum of a calcite pressed-powder pellet. The correspondence of the diffraction peaks in the spectra demonstrate that the limestone is comprised dominantly of calcite. In both cases, the claims of the earlier paper are fully supported by the results of these experimental tests. [Copyright &y& Elsevier]

A novel Eu3+ ions-based metal–organic coordination polymer with a peculiar "snake-shaped" chain structure has been synthesized, which exhibits efficient light emission, excellent line response to X-rays and high structure and luminescence stability against continuous irradiation. [Display omitted] • A new type of luminescent Eu-MOCP was synthesized by simple solvothermal method. • Synthesized Eu-based MOCP shows an efficient and stable light emission under X-ray excitation, and delivers an excellent linear response to X-ray dose. • Compound 1 demonstrates high structure and luminescence stability against continuous X-ray irradiation. In this paper, a novel Eu ions-based metal–organic coordination polymer (MOCP) named Eu(1,3,6,8-PTS)(H 2 O) 7 ·4H 2 OHbipy (1) (PTS = pyrenetetrasulfonic acid) has been prepared, and its structure, stability, photoluminescence and scintillation properties were systematically investigated. Compound 1 gives a peculiar "snake-shaped" chain structure with the aid of π-π stacking effect of 4,4′-bipyridine auxiliary template. An efficient and stable light emission was detected under X-ray irradiation, which presents an excellent linear response to X-ray dose. Moreover, this compound demonstrates high radiation stability, illustrating its potential as a scintillator for X-ray detection. This work not only provides guidance for the design and fabrication of sulfonic ligand derived MOCPs with Eu (III) ions coordiantion, but also demonstrates the potential of MOCPs scintillators for X-ray detection technology. [ABSTRACT FROM AUTHOR]

• The 25 µm-thick ZnO film using sputtering method was characterized for X-ray detection applications. • p+-Si/ZnO X-ray detector based on the 25 µm-thick ZnO film shows a high sensitivity of 128 μC∙Gy−1∙cm−2 at − 20 V. • The on-off response is related to the V O defect, which was verified by the transmittance spectrum and the TSC spectrum. [Display omitted] In the field of direct-conversion flat panel X-ray detector, semiconductor with thickness of tens to hundreds microns is needed. In this paper, we demonstrate that thick ZnO semiconductor deposited by RF magnetron sputtering can be candidate for the X-ray detector. The 25 µm ZnO film was prepared by sputtering method under 200 °C and a p+-Si/ZnO X-ray detector based on the thick ZnO film was investigated to explore its X-ray detection properties. The detector shows nonzero short circuit current and open circuit voltage indicating the heterojunction nature of the ZnO film in contact with the p+-Si substrate. The detector shows linear response to the X-ray dose rate and has a high sensitivity of 128 μC∙Gy−1∙cm−2 at −20 V under 30 kV p X-rays indicating its great potential in the flat panel X-ray detector applications. The on-off response of the detector is related to the V O defect in the ZnO film, which can be verified from the transmission spectrum, the thermal stimulated current spectrum, and the photoluminescence spectrum. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents the results of the characterisation of a back-illuminated pixel sensor manufactured in Silicon-on-Insulator technology on a high-resistivity substrate with soft X-rays. The sensor is thinned and a low energy phosphorus implantation is performed on the back-plane. The response to X-rays from 2.12 to 8.6keV is evaluated with fluorescence radiation at the LBNL Advanced Light Source. [Copyright &y& Elsevier]

Abstract: The system at threshold is a sensitive testing ground for low energy QCD, especially for the explicit chiral symmetry breaking. Therefore, we have measured the K-series X-rays of kaonic hydrogen atoms at the electron–positron collider of Laboratori Nazionali di Frascati, and have determined the most precise values of the strong-interaction energy-level shift and width of the 1s atomic state. As X-ray detectors, we used large-area silicon drift detectors having excellent energy and timing resolution, which were developed especially for the SIDDHARTA experiment. The shift and width were determined to be and , respectively. The new values will provide vital constraints on the theoretical description of the low-energy interaction. [Copyright &y& Elsevier]

Abstract: The Pauli exclusion principle (PEP), as a consequence or the spin-statistics connection, is one of the basic principles of the modern physics. Being at the very basis of our understanding of matter, it spurs a lively debate on its possible limits, deeply rooted as it is in the very foundations of Quantum Field Theory. The VIP (VIolation of the Pauli exclusion principle) experiment established the world''s best limit on the probability that PEP is violated by electrons, using the method of searching for PEP forbidden atomic transitions in copper. We describe the experimental method and the obtained results; we briefly present future plans to go beyond the actual limit by upgrading the experiment using vetoed new spectroscopic fast Silicon Drift Detectors. We also shortly mention the possibility of using a similar experimental technique to search for possible X-rays generated in the spontaneous collapse models of quantum mechanics. [Copyright &y& Elsevier]

Abstract: This paper presents a new power efficient asynchronous multiplexer (MUX) for application in analog front-end electronics (AFE) used in X-ray medical imaging systems. Contrary to typical synchronous MUXes that have to be controlled by a clock, this circuit features a simple structure, as the clock is not required. The circuit dissipates power only while detecting the active signals and then automatically turns back to the power down mode. Medical imaging systems usually consist of several dozen to even several hundreds of channels that operate asynchronously. The proposed MUX enables an unambiguous choice of the active channel. In case of two or more channels that become active at the same time the MUX serializes the reading out data from particular channels. This characteristic leads to 100% effectiveness in data processing and no impulses’ loss. The proposed MUX together with an experimental readout ASIC has been implemented in the CMOS 0.18μm process and occupies 1100μm2/channel area. It works properly in a wide range of the voltage supply in between 0.8 and 1.8V. Energy consumed during the detection of one active channel is below 1pJ, while the detection time is about 1ns. [ABSTRACT FROM AUTHOR]

• A novel multi-kernel-size spatial-channel attention model for COVID-19 detection • The proposed method enables early diagnosis from chest X-ray images. • Evaluation with real-world data demonstrates improved accuracy at 98.2 Novel coronavirus 2019 (COVID-19) has spread rapidly around the world and is threatening the health and lives of people worldwide. Early detection of COVID-19 positive patients and timely isolation of the patients are essential to prevent its spread. Chest X-ray images of COVID-19 patients often show the characteristics of multifocality, bilateral hairy glass turbidity, patchy network turbidity, etc. It is crucial to design a method to automatically identify COVID-19 from chest X-ray images to help diagnosis and prognosis. Existing studies for the classification of COVID-19 rarely consider the role of attention mechanisms on the classification of chest X-ray images and fail to capture the cross-channel and cross-spatial interrelationships in multiple scopes. This paper proposes a multi-kernel-size spatial-channel attention method to detect COVID-19 from chest X-ray images. Our proposed method consists of three stages. The first stage is feature extraction. The second stage contains two parallel multi-kernel-size attention modules: multi-kernel-size spatial attention and multi-kernel-size channel attention. The two modules capture the cross-channel and cross-spatial interrelationships in multiple scopes using multiple 1D and 2D convolutional kernels of different sizes to obtain channel and spatial attention feature maps. The third stage is the classification module. We integrate the chest X-ray images from three public datasets: COVID-19 Chest X-ray Dataset Initiative, ActualMed COVID-19 Chest X-ray Dataset Initiative, and COVID-19 radiography database for evaluation. Experimental results demonstrate that the proposed method improves the performance of COVID-19 detection and achieves an accuracy of 98.2%. [ABSTRACT FROM AUTHOR]

Background: The accuracy of the chest x-ray (CXR) in the identification of lung cancer amongst symptomatic individuals is uncertain.Purpose: To determine the diagnostic accuracy of the CXR for the detection of non-small cell carcinomas (NSCLC) and all primary intrathoracic malignancies.Methods: A prospective cohort study of consecutive CXR reports obtained within a primary care open access initiative. Eligibility criteria were symptoms specified by National Institute for Clinical Excellence as indicative of possible lung cancer and age over 50-yrs. A positive test was a CXR which led directly or indirectly to investigation with CT. The reference standards were malignancies observed within a one- or two-year post-test period.Results: 8,948 CXR outcomes were evaluated. 496 positive studies led to a diagnosis of 101 patients with primary intrathoracic malignancy including 80 with NSCLC. Within two-years, a cumulative total of 168 patients with primary intrathoracic malignancies including 133 NSCLC were observed. The sensitivity and specificity for NSCLC were 76% (95 %CI 68-84) and 95% (95 %CI 95-96) within 1-year and 60% (95 %CI 52-69) and 95% (95 %CI 95-96) within 2-years. The 2-yr positive and negative likelihood ratios were 12.8 and 0.4. The results did not differ for NSCLC compared to all primary malignancies. Within this symptomatic population a negative test reduced the 2-year risk of lung cancer to 0.8%.Conclusions: A positive test strongly increases the probability of malignancy whereas a negative test does not conclusively exclude the disease. The findings allow the risk of malignancy following a negative test to be estimated. [ABSTRACT FROM AUTHOR]

X-ray detection is an important technology for medical diagnosis as well as industrial and security inspections. While today's commercial X-ray detectors are bulky, photodetectors based on organic semiconductors have attracted increasing attention owing to their low temperature processing capabilities, flexibility and low cost. Nonetheless, the low X-ray attenuation coefficient of organic semiconductors still hinders their practical application. Herein, a new organic-inorganic hybrid strategy is proposed to improve the X-ray sensitivity of organic photodetectors (OPDs). A solution-processed X-ray sensitive hybrid OPD is fabricated by embedding CsPbBr 3 quantum dots (QDs) into a P3HT:PC 61 BM bulk heterojunction photodiode. The QDs, acting as embedded scintillators in the organic active layer, maintain a high radioluminescence. The proposed hybrid structure enables indirect X-ray detection in a comprehensive manner. These hybrid photodetectors exhibit suppressed dark current densities in the range of tens of picoamperes per square centimeters for different weight ratios of blended QDs. The best OPD achieves a sensitivity of 229.6 e nGy−1 mm−2 (3.67 μC Gy−1 cm−2) and a dark current of 23.3 pA cm−2 at a low operating voltage (−3 V) for 20–80 kV "soft" X-rays, thus representing great potential for the development of next generation low cost, portable, and highly sensitive X-ray detectors. [Display omitted] • An all-in-one X-ray photodetector is realized by embedding CsPbBr 3 QDs into the P3HT:PC 61 BM photodiode. • The hybrid photodetectors exhibit suppressed dark current densities and high photosensitivity. • Great enhancement in X-ray sensitivity is achieved with CsPbBr 3 QDs. [ABSTRACT FROM AUTHOR]