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The characteristic X-ray detector (CXRD), a CsI(Tl) scintillator with a 50-mm diameter, is a directional X-ray sensor that measures characteristic X-rays from radioactive material, such as 137 Cs, and identifies the direction of radioactive contamination. We evaluated a CXRD and visualized the distribution of radioactivity in the contaminated area near the Fukushima Dai-ichi nuclear power station, where the ambient dose equivalent rate was 2.1 μSv/h at 1 m above ground level. We found a good correlation between the characteristic X-ray fluxes and the distribution of radioactive contaminants with a 0.823 Pearson product–moment correlation coefficient. [ABSTRACT FROM AUTHOR]

Eu 3+ doped heavy germanate scintillating glasses were prepared by melt quenching method. Their physical and luminescent properties were investigated. The glasses exhibit the densities of more than 6.5 g/cm 3 . The transmittance spectra show the glasses have good transmittance in the visible region. The glasses show intense red emissions under 393 nm light excitation and X-ray excitation. The lifetimes of 614 nm emission of Eu 3+ -doped germanate glasses are in the range from 1.424 ms to 1.484 ms. The results indicate that Eu 3+ -doped high density germanate scintillating glasses could be of good anti-radiation properties and could be an X-ray scintillating material suitable to X-ray detection for slow event. [ABSTRACT FROM AUTHOR]

• COVID-19 images were analyzed with a new preprocessing model. • In this study, feature extraction was performed from COVID-19 images according to RGB values. • The proposed model was tested by statistical methods. • The results of both normal data and feature-reduced data were compared. The COVID-19 pandemic spread all over the world, starting in China in late 2019, and significantly affected life in all aspects. As seen in SARS, MERS, COVID-19 outbreaks, coronaviruses pose a great threat to world health. The COVID-19 epidemic, which caused pandemics all over the world, continues to seriously threaten people's lives. Due to the rapid spread of COVID-19, many countries' healthcare sectors were caught off guard. This situation put a burden on doctors and healthcare professionals that they could not handle. All of the studies on COVID-19 in the literature have been done to help experts to recognize COVID-19 more accurately, to use more accurate diagnosis and appropriate treatment methods. The alleviation of this workload will be possible by developing computer aided early and accurate diagnosis systems with machine learning. Diagnosis and evaluation of pneumonia on computed tomography images provide significant benefits in investigating possible complications and in case follow-up. Pneumonia and lesions occurring in the lungs should be carefully examined as it helps in the diagnostic process during the pandemic period. For this reason, the first diagnosis and medications are very important to prevent the disease from progressing. In this study, a dataset consisting of Pneumonia and Normal images was used by proposing a new image preprocessing process. These preprocessed images were reduced to 15x15 unit size and their features were extracted according to their RGB values. Experimental studies were carried out by performing both normal values and feature reduction among these features. RGB values of the images were used in train and test processes for MLAs. In experimental studies, 5 different Machine Learning Algorithms (MLAs) (Multi Class Support Vector Machine (MC-SVM), k Nearest Neighbor (k-NN), Decision Tree (DT), Multinominal Logistic Regression (MLR), Naive Bayes (NB)). The following accuracy rates were obtained in train operations for MLAs, respectively; 1, 1, 1, 0.746377, 0.963768. Accuracy results in test operations were obtained as follows; 0.87755, 0.857143, 0.857143, 0.877551, 0.938776. [ABSTRACT FROM AUTHOR]

The novel COVID-19 pandemic, has effectively turned out to be one of the deadliest events in modern history, with unprecedented loss of human life, major economic and financial setbacks and has set the entire world back quite a few decades. However, detection of the COVID-19 virus has become increasingly difficult due to the mutating nature of the virus, and the rise in asymptomatic cases. To counteract this and contribute to the research efforts for a more accurate screening of COVID-19, we have planned this work. Here, we have proposed an ensemble methodology for deep learning models to solve the task of COVID-19 detection from chest X-rays (CXRs) to assist Computer-Aided Detection (CADe) for medical practitioners. We leverage the strategy of transfer learning for Convolutional Neural Networks (CNNs), widely adopted in recent literature, and further propose an efficient ensemble network for their combination. The DenseNet-201 architecture has been trained only once to generate multiple snapshots, offering diverse information about the extracted features from CXRs. We follow the strategy of decision-level fusion to combine the decision scores using the blending algorithm through a Random Forest (RF) meta-learner. Experimental results confirm the efficacy of the proposed ensemble method, as shown through impressive results upon two open access COVID-19 CXR datasets — the largest COVID-X dataset, as well as a smaller scale dataset. On the large COVID-X dataset, the proposed model has achieved an accuracy score of 94.55% and on the smaller dataset by Chowdhury et al., the proposed model has achieved a 98.13% accuracy score. • Proposed a CNN ensemble framework for medical practitioners. • A COVID-19 Detection system for Chest X-ray images is established. • Generated base model snapshots for ensembling by training the CNN model. • Followed decision-level fusion to combine decision scores using blending algorithm. • Appreciable results on largest COVID-X public dataset verifies the efficacy of the method. [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]

Chip resistors are the most common and most frequent components in all electronics. Voids are formed by outgassing during solder reflow. Excessive voids influence the electrical and thermal conductivity of the solder joint and hence reduce its reliability. Therefore, in this study, we propose a scheme combining Residual Multiscale Skip Connected Net (RMSC-Net) and Recurrent Convolutional Network (RU-Net) to accurately detect the voids and solder joints of the X-ray images of the chip resistor. We first develop an RMSC-Net for void segmentation of X-ray images. RMSC-Net combines residual with multiscale skip connections. Residual learning solves the problem of gradient dispersion by learning the difference between the target and input values. The proposed multiscale skip connection combines multiple high- and low-resolution feature maps to realize multilayer feature perception of voids. Then, we deploy RU-Net with recurrent convolution modules to apply the chip resistors' solder joint segmentation. Experimental results demonstrate that the overall performance of RMSC-Net and RU-Net is better than other methods in detecting voids and solder joints of three different types of chip resistors. RMSC-Net achieves average SE gains of 2.70 and 2.25 points over UNet++ and FedDG, respectively. The average PR of RU-Net is 0.34 and 0.61 points higher than that of UNet++ and FedDG, respectively. • A detection scheme that combines RMSC-Net and R-UNet to detect voids and solder joints in chip resistors is proposed. • A RMSC-Net is developed for micro-voids segmentation of CT images. • We present multi-scale skip connections to fuse different levels of features. • The residual is introduced to solve the problem of gradient dispersion or gradient explosion. • R-UNet with recurrent convolution modules is adopted to detect the edges of solder joints accurately. [ABSTRACT FROM AUTHOR]

• An image preprocessing method is applied to CXR data, and the segmented images are selected and fed into the model. • Introduction of fine-tuned Global Attention Blocks (GAB) and Category Attention Blocks (CAB) to obtain more detailed information on micro lesions. • The DenseNet and VGG models were fused to detect different pneumonia diseases. Since December 2019, the novel coronavirus disease (COVID-19) caused by the syndrome coronavirus 2 (SARS-CoV-2) strain has spread widely around the world and has become a serious global public health problem. For this high-speed infectious disease, the application of X-ray to chest diagnosis plays a key role. In this study, we propose a chest X-ray image classification method based on feature fusion of a dense convolutional network (DenseNet) and a visual geometry group network (VGG16). This paper adds an attention mechanism (global attention machine block and category attention block) to the model to extract deep features. A residual network (ResNet) is used to segment effective image information to quickly achieve accurate classification. The average accuracy of our model in detecting binary classification can reach 98.0%. The average accuracy for three category classification can reach 97.3%. The experimental results show that the proposed model has good results in this work. Therefore, the use of deep learning and feature fusion technology in the classification of chest X-ray images can become an auxiliary tool for clinicians and radiologists. [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]

The scintillator film, as a key element affecting X-ray detection imaging resolution, has attracted more and more attention. At present, it is mainly obtained by grinding and polishing of crystal or ceramic scintillators and film evaporation technology, with high cost, limited size and long preparation period. In this work, we propose a simple method to prepare scintillator films by blending (Lu 0.995 Ce 0.005) 3 Al 5 O 12 nano-powders and polydimethylsiloxane (PDMS), and characterize the uniformity, light absorption, photoluminescence, and X-ray excited luminescence (XEL) of these. The XEL results show that the prepared LuAG:Ce-PDMS composite scintillator films have a clear broadband emission in the region of 480 and 680 nm, which can be well coupled with silicon photodiodes. Its XEL integral intensity is 286% that of commercial BGO scintillators, and the spatial resolution is 25 lp/mm when the film thickness is 100 μm. All of those show the LuAG:Ce-PDMS composite scintillator films have a potential application in scintillator-based indirect-type X-ray imaging. • A simple method to prepare scintillation films. • The XEL intensity of the film is 286% of that of commercial BGO scintillator. • The image resolution is 25 lp/mm when the film thickness is 100 μm. [ABSTRACT FROM AUTHOR]

A digital x-ray detector scheme based on a pixelated scintillator coupled with a fiber optic (FOT) array is suitable for many high-resolution x-ray imaging applications. However, certain challenges need to be addressed for fabrication of wafer-scale uniform pixelated x-ray scintillators. In addition, difficulties associated with implementation of the data acquisition system for acquiring output image data from the multiple image sensors used in the detector also need to be addressed. In this paper, a 2×2 FOT array-coupled digital x-ray detector scheme using a 5-in. pixelated scintillator is proposed. A novel fabrication setup along with the corresponding processes for fabricating the wafer-scale pixelated scintillator and implementation of a specially designed embedded data acquisition system based on a single embedded micro-processer (ARM) and four field-programmable gate array (FPGA) chips are discussed in detail. Preliminary experiments demonstrate that this pixelated scintillator-based digital x-ray detector scheme with an active imaging area of about 100 mm×100 mm shows considerable potential for use in high-resolution x-ray imaging. [ABSTRACT FROM AUTHOR]

The influence of the gas-static processing on the optical, structural and electrophysical properties of Au–CdZnTe–Au structures, used in X- and gamma-ray detectors, was investigated. The processing, which is described in detail in the experimental part, was done in a laboratory-scale setup “GAUS-4/2000-35” with the following process parameters: pressure=0.32±0.02 GPa, temperature ~170 °C, time=2 h. The influence of the mentioned processing on the photoluminescence, the Raman scattering, the electric resistance, the I–V characteristics and the spectrometric parameters of the Au–CdZnTe–Au structures was determined. The physical mechanisms, through which the gas-static processing induces changes in the structural and functional properties, were analyzed. It was observed that the gas-static processing (with the above-mentioned process parameters) of the Au–CdZnTe–Au structures leads to a significant increase of the electric resistance of the structures; it also leads to the increase of the intensity of the photoelectric absorption peak when the respective detector is registering X- and gamma-radiation with energy near 32.19 keV. The Raman and photoluminescence data indicates the formation of the surface oxides TeO x and the compensation of Cd vacancies by Au atoms. The assumption that, under the discussed processing, two different rival processes modify the Au–CdZnTe junction due to the influence of the increased temperature ~170 °C and pressure ~0.3 GPa, was suggested. The first process is the formation of TeO 2 oxide (which increases the electric resistance) on the contact; the second process is the destruction of the surface films of the oxides and the absorbed gases. Most likely, the first process is dominant, which was evidenced by the Raman and photoluminescence measurements. [ABSTRACT FROM AUTHOR]

X- and γ -ray detection is currently a hot topic for a wide scientific community, spanning from astrophysics to nuclear medicine. However, lack of optics capable of focusing photons of energies in the energy range 0.1–1 MeV leaves the photon detection to a direct-view approach, resulting in a limited efficiency and resolution. The main scope of the INFN-LOGOS project is the development of technologies that enable manufacturing highly performing optical elements to be employed in the realization of hard X-ray lenses. Such lenses, typically named Laue lenses, consist of an ensemble of crystals disposed in concentric rings in order to diffract the incident radiation towards the focus of the lens, where a detector is placed. In particular, the INFN-LOGOS project aims at the realization of intrinsically bent silicon and germanium crystals exploiting the quasi-mosaic effect for focusing hard X-rays. Crystal manufacturing relies on a proper revisitation of techniques typically employed in silicon micromachining, such as thin film deposition and patterning or ion implantation. [ABSTRACT FROM AUTHOR]

The Astrophysics Division of CEA Saclay has a long history in the development of CdTe based pixelated detection planes for X and gamma-ray astronomy, with time-resolved imaging and spectrometric capabilities. The last generation, named Caliste HD, is an all-in-one modular instrument that fulfills requirements for space applications. Its full-custom front-end electronics is designed to work over a large energy range from 2 keV to 1 MeV with excellent spectroscopic performances, in particular between 10 and 100 keV (0.56 keV FWHM and 0.67 keV FWHM at 13.9 and 59.5 keV). In the frame of the ORIGAMIX project, a consortium based on research laboratories and industrials has been settled in order to develop a new generation of gamma camera. The aim is to develop a system based on the Caliste architecture for post-accidental interventions or homeland security, but integrating new properties (advanced spectrometry, hybrid working mode) and suitable for industry. A first prototype was designed and tested to acquire feedback for further developments. The main difference between astronomy and nuclear applications is the radiation flux and energy-ranges involved. In this study, we particularly focused on spectrometric performances with high energies and high fluxes. Therefore, our device was exposed to energies up to 700 keV ( 133 Ba, 137 Cs) and we measured the evolution of energy resolution (0.96 keV at 80 keV, 2.18 keV at 356 keV, 3.33 keV at 662 keV). Detection efficiency decreases after 150 keV, as Compton effect becomes dominant. However, CALISTE is also designed to handle multiple events, enabling Compton scattering reconstruction, which can drastically improve detection efficiencies and dynamic range for higher energies up to 1408 keV ( 22 Na, 60 Co, 152 Eu) within a 1-mm thick detector. In particular, such spectrometric performances obtained with 152 Eu and 60 Co were never measured before with this kind of detector. [ABSTRACT FROM AUTHOR]

The principle of the X-ray detector which can simultaneously perform the measurement of the exposure rate and 2D (two-dimensional) distribution is described. A commercially available CMOS image sensor has been adopted as the key part to receive X-ray without any scintillators. The correlation between the pixel value (PV) and the absorbed exposure rate of X-ray is studied using the improved Elman neural network. Comparing the optimal adjustment process of the BP (Back Propagation) neural network and the improved Elman neural network, the neural network parameters are selected based on the fitting curve and the error curve. The experiments using the practical production data show that the proposed method achieves high accurate predictions to 10 −15 , which is consistent with the anticipated value. It is proven that it is possible to detect the exposure rate using the X-ray detector with the improved Elman algorithm for its advantages of fast converges and smooth error curve. [ABSTRACT FROM AUTHOR]

Recently, a novel plasma display panel (PDP)-based X-ray detector (PXD) was developed. The goal of this study is to develop a data acquisition system for use with the PXD as an imaging detector. Since the prototype detector does not have any barrier ribs or a switching device in a detector pixel, a novel pixelation scheme—the line-scan method—is developed for this new detector. To implement line scanning, a multichannel high-voltage switching circuit and a multichannel charge-acquisition circuit are developed. These two circuits are controlled by an FPGA-based digital signal processing board, from which the information about the charge and position of each pixel can be sent to a PC. FPGA-based baseline compensation and switching noise rejection algorithms are used to improve the signal-to-noise ratio (SNR). The characteristic curve of the entire PXD system is acquired, and the correlation coefficients between the X-ray dose, and the signal intensity and the SNR were determined to be approximately 0.99 and 52.9, respectively. [ABSTRACT FROM AUTHOR]

We demonstrated the material- and radiation-detection properties of cadmium manganese telluride (Cd 1− x Mn x Te; x =0.06), a wide-band-gap semiconductor crystal grown by the modified floating-zone method. We investigated the presence of various bulk defects, such as Te inclusions, twins, and dislocations of several as-grown indium-doped Cd 1− x Mn x Te crystals using different techniques, viz., IR transmission microscopy, and chemical etching. We then fabricated four planar detectors from selected CdMnTe crystals, characterized their electrical properties, and tested their performance as room-temperature X- and gamma-ray detectors. Our experimental results show that CMT crystals grown by the modified floating zone method apparently are free from Te inclusions. However, we still need to optimize our growth parameters to attain high-resistivity, large-volume single-crystal CdMnTe. [ABSTRACT FROM AUTHOR]

In this article, a two-dimensional detector based on plasma display technology was investigated as a candidate for a flat-panel radiation detector. By using the three-dimensional Garfield code, the dependence of the electric field and multiplication on various electrode structures was examined. Based on the calculation of multiplication, three different electrode designs, including CAC, ridged CAC, and double-ridged CAC structures were selected and prototype detectors adopting these designs were fabricated and tested. The performance of these detectors was evaluated by measuring the charge density and sensitivity. The charge density of the double-ridged CAC detector during the X-ray for the on condition varied from 0.482 up to 2.59 μ C / cm 2 at the address bias scope of −500–−1500 V , while the cathode voltage was locked at - 400 V . The sensitivity of the same detector was 0.596 nC / mR ⋅ cm 2 in an electric field of 0.54 V/μm, which was the highest value. This was about one-third lower than the sensitivity of the amorphous selenium (a-Se) based detector at 10 V/μm. [ABSTRACT FROM AUTHOR]

This paper presents an upgraded in-trap decay spectroscopy apparatus which has been developed and constructed for use with TRIUMF׳s Ion Trap for Atomic and Nuclear science (TITAN). This device consists of an open-access electron-beam ion-trap (EBIT), which is surrounded radially by seven low-energy planar Si(Li) detectors. The environment of the EBIT allows for the detection of low-energy photons by providing backing-free storage of the radioactive ions, while guiding charged decay particles away from the trap centre via the strong (up to 6 T) magnetic field. In addition to excellent ion confinement and storage, the EBIT also provides a venue for performing decay spectroscopy on highly charged radioactive ions. Recent technical advancements have been able to provide a significant increase in sensitivity for low-energy photon detection, towards the goal of measuring weak electron-capture branching ratios of the intermediate nuclei in the two-neutrino double beta ( 2 ν β β ) decay process. The design, development, and commissioning of this apparatus are presented together with the main physics objectives. The future of the device and experimental technique are discussed. [ABSTRACT FROM AUTHOR]

Medical X-ray digital imaging systems such as mammography, radiography and computed tomography (CT), are composed from efficient radiation detectors, which can transform the X-rays to electron signal. Scintillators are materials that emit light when excited by X-rays and incorporated in X-ray medical imaging detectors. Columnar scintillator, like CsI:T1 is very often used for X-ray detection due to its higher performance. The columnar form limits the lateral spread of the optical photons to the scintillator output, thus it demonstrates superior spatial resolution compared to granular scintillators. The aim of this work is to provide an analytical model for calculating the MTF, the DQE and the emission efficiency of a columnar scintillator. The model parameters were validated against published Monte Carlo data. The model was able to predict the overall performance of CsI:Tl scintillators and suggested an optimum thickness of 300 μm for radiography applications. [ABSTRACT FROM AUTHOR]

Spontaneous regression (SR) is defined as the complete or partial disappearance of disease without anticancer treatments. We report a case of SR of small cell lung cancer (SCLC) combined with cancer associated retinopathy (CAR). A 65-year-old woman was admitted to our hospital to examine abnormal shadows of the lung with visual loss. She was diagnosed with SCLC associated with CAR. Subsequent chest X-ray and CT scan showed partial regression of both primary tumor and lymph node metastasis without anticancer treatment. Recoverin antigen was present on the tumor cells and anti-recoverin antibody was observed in the patient's serum. Activation of recoverin-specific antitumor cytotoxic T lymphocyte (CTL) was observed in this patient. SCLC was considered to reduce spontaneously by the activation of recoverin-specific antitumor CTL. To the best of our knowledge, this is the first report of SR in SCLC combined with CAR. [ABSTRACT FROM AUTHOR]

To detect low-dose-rate X-rays, we have developed an X-ray-detecting module for semiconductor diodes. The module consists of a current–voltage ( I – V ) amplifier, a voltage–voltage ( V – V ) amplifier, and an alternating-current adopter with a smoothing circuit. The photocurrents flowing through a diode are converted into voltages and amplified using the I – V and V – V amplifiers. To measure relative sensitivities, we used three silicon PIN diodes (Si-PIN), a cerium-doped yttrium aluminum perovskite [YAP(Ce)] crystal, and a Lu 2 (SiO 4 )O [LSO] crystal. Three detectors are as follows: an Si-PIN, a YAP(Ce)–Si-PIN, and an LSO–Si-PIN. Using the three detectors, the amplifier output voltages were in proportion to the tube current at a constant tube voltage of 70 kV. Using a multichannel analyzer, the event-pulse-height spectra were measured to analyze X-ray-electric conversion effect in the three detectors. The output voltage of the Si-PIN was approximately twice as high as those obtained using the YAP(Ce)–Si-PIN and the LSO–Si-PIN at the measurement conditions. [ABSTRACT FROM AUTHOR]

The progression of adolescent idiopathic scoliosis is typically monitored via regular radiographic follow-up. The Cobb angle (as measured on whole-spine radiographs) is considered as the gold standard in scoliosis monitoring. Objective To determine the sensitivity and specificity of back surface topography parameters, with a view to detecting changes in the Cobb angle. Patient and method One hundred patients (mean age: 13.3) with Cobb angles greater than 10 degrees were included. Topographic parameters were measured in a standard position and in a position with hunched shoulders. Gibbosities and spinal curvatures were evaluated. Results An increase of more than 2 degrees in any one gibbosity or in the sum of the gibbosities (in either of the two examination positions) enabled the detection of a five-degree increase in the Cobb angle with a sensitivity of 86% and a specificity of 50%. Conclusion If the present results are confirmed by other studies, analysis with back surface topography parameters may reduce the number of X-ray examinations required to detect increases in the Cobb angle. [ABSTRACT FROM AUTHOR]

A novel on-chip, customer-design spiral biasing adaptor (SBA) has been developed. A single SBA is used for biasing a Si drift detector (SDD) and SDD array. The use of an SBA reduces the biasing current. This paper shows the calculation of the geometry of an SBA and an SDD to get the best drift field in the SDD and SDD array. Prototype SBAs have been fabricated to verify the concept. Electrical measurements on these SBAs are in agreement with the expectations. The new SDD array with an SBA can be used for X-ray detection and in nuclear physics experiments. [ABSTRACT FROM AUTHOR]

This paper introduces a new concept of silicon radiation detector with intrinsic multiplication of the charge, called Low Gain Avalanche Detector (LGAD). These new devices are based on the standard Avalanche Photo Diodes (APD) normally used for optical and X-ray detection applications. The main differences to standard APD detectors are the low gain requested to detect high energy charged particles, and the possibility to have fine segmentation pitches: this allows fabrication of microstrip or pixel devices which do not suffer from the limitations normally found [1] in avalanche detectors. In addition, a moderate multiplication value will allow the fabrication of thinner devices with the same output signal of standard thick substrates. The investigation of these detectors provides important indications on the ability of such modified electrode geometry to control and optimize the charge multiplication effect, in order to fully recover the collection efficiency of heavily irradiated silicon detectors, at reasonable bias voltage, compatible with the voltage feed limitation of the CERN High Luminosity Large Hadron Collider (HL-LHC) experiments [2] . For instance, the inner most pixel detector layers of the ATLAS tracker will be exposed to fluences up to 2×10 16 1 MeV n eq /cm 2 , while for the inner strip detector region fluences of 1×10 15 n eq /cm 2 are expected. The gain implemented in the non-irradiated devices must retain some effect also after irradiation, with a higher multiplication factor with respect to standard structures, in order to be used in harsh environments such those expected at collider experiments. [ABSTRACT FROM AUTHOR]

The projection number, acquisition time, radiation dose, and full and 2×2 binning modes of the thin film transistor (TFT) X-ray imaging detector were evaluated for image quality in a prototype cone-beam computed tomography (CBCT) built for medical applications. The detector is an amorphous silicon (a-Si) based TFT X-ray detector (PaxScan 4030CB, Varian, Inc.). The a-Si based TFT X-ray detector has a 397×298 mm 2 active area with 194 μm pixel pitch and 2048×1536 pixel, of which, 388 μm pixel pitch and 1024×768 pixel were used for the 2×2 binning mode. The Feldkamp, Davis, and Kress (FDK) reconstruction algorithm was used to generate 3D images, and the comparisons were made between different modes of acquisition. The American Association of Physicists in Medicine (AAPM) computed tomography (CT) performance phantom (model 610, CIRS) and the chest phantom (model 76-683, Nuclear Associates) were used to evaluate the image quality. [ABSTRACT FROM AUTHOR]

Dental X-ray films are still largely used due to sterilization issues, simplicity and, mainly, economic reasons. These films almost always are double coated (double emulsion) and have a lead foil in contact with the film for X-ray backscattering rejection. Herein we explore the use of the lead foil as an image intensifier. In these studies, spatial resolution was investigated when images were acquired on the dental X-ray films with and without the lead foil. Also, the lead foil was subjected to atomic analysis (fluorescent measurements) and structure analysis (X-ray diffraction). We determined that the use of the lead foil reduces the exposure time, however, does not affect the spatial resolution on the acquired images. This suggests that the fluorescent radiation spread is smaller than the grain sizes of the dental X-ray films. [ABSTRACT FROM AUTHOR]

The ROOT based Offline and Online Analysis (ROAn) framework was developed to perform data analysis on data from Depleted P-channel Field Effect Transistor (DePFET) detectors, a type of active pixel sensors developed at the MPI Halbleiterlabor (HLL). ROAn is highly flexible and extensible, thanks to ROOT׳s features like run-time type information and reflection. ROAn provides an analysis program which allows to perform configurable step-by-step analysis on arbitrary data, an associated suite of algorithms focused on DePFET data analysis, and a viewer program for displaying and processing online or offline detector data streams. The analysis program encapsulates the applied algorithms in objects called steps which produce analysis results. The dependency between results and thus the order of calculation is resolved automatically by the program. To optimize algorithms for studying detector effects, analysis parameters are often changed. Such changes of input parameters are detected in subsequent analysis runs and only the necessary recalculations are triggered. This saves time and simultaneously keeps the results consistent. The viewer program offers a configurable Graphical User Interface (GUI) and process chain, which allows the user to adapt the program to different tasks such as offline viewing of file data, online monitoring of running detector systems, or performing online data analysis (histogramming, calibration, etc.). Because of its modular design, ROAn can be extended easily, e.g. be adapted to new detector types and analysis processes. [ABSTRACT FROM AUTHOR]

This work puts forward the idea of dual-mode X-ray detection using color change and electric signal, and provides a MOF (metal–organic framework)-based host–guest strategy to synthesize rewritable radiochromic semiconductive materials, which are promising to avoid the lack of digital processing ability and reusability of commercial radiographic/radiochromic films and the non-portability of commercial electric detectors. [Display omitted] • Obtain the first rewritable radiochromic semiconductor via a host–guest strategy. • Realize X-ray detection using color change and electric signal for the first time. • Exhibit color change and electric signal upon irradiation in the REVERSIBLE mode. • Achieve a sensitivity of 3216 µCGy–1cm−2, higher than known MOF-based detectors. This work puts forward the idea of dual-mode X-ray detection using color change and electric signal, and provides a MOF (metal–organic framework)-based host–guest strategy to synthesize rewritable radiochromic semiconductive materials, which are promising to avoid the lack of digital processing ability and reusability of commercial radiographic/radiochromic films and the non-portability of commercial electric detectors. The obtained semiconductor with photochromism-active viologen exhibited rapid color change from colorless to blue and photocurrent response upon irradiation of X-ray and was easily bleached after thermal annealing for reuse. As an application example, the inner detail of a printed circuit board was successfully revealed through radiochromic imaging. Meanwhile, a single-crystal detector of the semiconductor achieved a sensitivity of 3216 µCGy–1cm−2, which is higher than those of all reported MOF-based detectors and commercial α-Se detectors. [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]

• Hierarchical Bezier-based Learning improves residual networks to detect stenosis. • A high-quality image patch generator for X-ray coronary angiography analysis. • The generative model reaches a Fréchet Inception Distance of up to 84.0886. • Self-attention mechanisms maximize neural network performance up to 7%. • Notable stenosis detection accuracy, precision, F1-score, and specificity of 0.8934, 0.9031, 0.8880, 0.9111, respectively, were reached. [Display omitted] Background and Objective: Automatic detection of stenosis on X-ray Coronary Angiography (XCA) images may help diagnose early coronary artery disease. Stenosis is manifested by a buildup of plaque in the arteries, decreasing the blood flow to the heart, increasing the risk of a heart attack. Convolutional Neural Networks (CNNs) have been successfully applied to identify pathological, regular, and featured tissues on rich and diverse medical image datasets. Nevertheless, CNNs find operative and performing limitations while working with small and poorly diversified databases. Transfer learning from large natural image datasets (such as ImageNet) has become a de-facto method to improve neural networks performance in the medical image domain. Methods: This paper proposes a novel Hierarchical Bezier-based Generative Model (HBGM) to improve the CNNs training process to detect stenosis. Herein, artificial image patches are generated to enlarge the original database, speeding up network convergence. The artificial dataset consists of 10,000 images containing 50% stenosis and 50% non-stenosis cases. Besides, a reliable Fréchet Inception Distance (FID) is used to evaluate the generated data quantitatively. Therefore, by using the proposed framework, the network is pre-trained with the artificial datasets and subsequently fine-tuned using the real XCA training dataset. The real dataset consists of 250 XCA image patches, selecting 125 images for stenosis and the remainder for non-stenosis cases. Furthermore, a Convolutional Block Attention Module (CBAM) was included in the network architecture as a self-attention mechanism to improve the efficiency of the network. Results: The results showed that the pre-trained networks using the proposed generative model outperformed the results concerning training from scratch. Particularly, an accuracy, precision, sensitivity, and F1-score of 0.8934, 0.9031, 0.8746, 0.8880, 0.9111, respectively, were achieved. The generated artificial dataset obtains a mean FID of 84.0886, with more realistic visual XCA images. Conclusions: Different ResNet architectures for stenosis detection have been evaluated, including attention modules into the network. Numerical results demonstrated that by using the HBGM is obtained a higher performance than training from scratch, even outperforming the ImageNet pre-trained models. [ABSTRACT FROM AUTHOR]

Gd 2 O 2 S:Tb (P43) powder was widely used in soft X-ray detection due to its high light yield. Compared with P43, GAGG:Ce scintillator has high light transmittance, fast decay time and strong radiation resistance. Photonic crystals (PhCs) can be used to enhance the light output of scintillator. In this paper, two-dimensional (2D) photonic crystals that consist of square arrays of air holes etched into TiO 2 layer were fabricated on the exit surface of GAGG:Ce scintillator to enhance its light output. The luminescence spectra and the light output of GAGG:Ce scintillator with/without PhCs were measured at the BL08U1A beamline of Shanghai Synchrotron Radiation Facility. The results showed that the light output of GAGG:Ce scintillator with PhCs can be enhanced by a factor of 1.43 times compared with the reference GAGG:Ce scintillator, 2.35 times compared with YAG:Ce scintillator, 1.24 times compared with Gd 2 O 2 S:Tb scintillation ceramic and 0.76 times compared with P43 powder layer with the mass thickness of about 1.3mg/cm 2 with optical grease coupling. No significant change was observed in luminescence decay time between GAGG:Ce scintillator with and without PhCs. It makes GAGG:Ce scintillator with PhCs a promising material instead of P43 powder and YAG:Ce scintillator in soft X-ray detector. [ABSTRACT FROM AUTHOR]

• A dataset of X-ray radiographs of pear fruit was simulated from CT scans. • Deep anomaly detection models were trained on data of healthy pears and tested on data of healthy and defect pears. • Synthetic anomalies in training improved performance over the unsupervised case. • High AUC scores (up to 0.96) and classification accuracy (up to 95%) were obtained. • Defect pears with a cavity percentage > 1.0% could be detected 100% accurate. To preserve the quality of fresh fruit after harvest and to meet the year-round demand for high-quality fruit, pears are stored under a controlled atmosphere. However, due to preharvest events or suboptimal storage conditions, internal disorders might develop resulting in severe quality loss. Examples include internal browning and cavities, which are invisible externally. Here, X-ray radiography is investigated as a technique for internal quality inspection. The detection of defect fruit is approached as an anomaly detection (AD) problem, in which a model is constructed using nominal data and an anomaly score is used to identify defect fruit. In this work, multiple deep AD methods are shown to be effective to detect pears with internal cavity and browning disorders using X-ray radiographs (mean area under the receiver operating characteristic curve (AUC) up to 0.962). The best performing methods were found on par with a state-of-the-art multisensor disorder detection method (mean AUC up to 0.966). By investigating AD performance in function of internal disorder severity, it was shown that defect fruit with a cavity volume percentage > 1.0% could be detected 100% accurate using inline X-ray imaging. For lower cavity area percentages, the accuracy depended on the internal browning severity. Additionally, the explainability of the deep AD methods, i.e., how well human interpretable insight can be provided from each method's predictions, were qualitatively evaluated using anomaly heatmaps, which provided useful insight in the execution of the deep learning algorithms. [ABSTRACT FROM AUTHOR]

• Introduce task amenability for quantifying task-specific image quality assessment • Propose meta-reinforcement learning algorithms for learning label-efficient, adaptable task amenability • Select task amenable data for improving performance in three tasks from two clinical applications [Display omitted] In this paper, we consider image quality assessment (IQA) as a measure of how images are amenable with respect to a given downstream task, or task amenability. When the task is performed using machine learning algorithms, such as a neural-network-based task predictor for image classification or segmentation, the performance of the task predictor provides an objective estimate of task amenability. In this work, we use an IQA controller to predict the task amenability which, itself being parameterised by neural networks, can be trained simultaneously with the task predictor. We further develop a meta-reinforcement learning framework to improve the adaptability for both IQA controllers and task predictors, such that they can be fine-tuned efficiently on new datasets or meta-tasks. We demonstrate the efficacy of the proposed task-specific, adaptable IQA approach, using two clinical applications for ultrasound-guided prostate intervention and pneumonia detection on X-ray images. [ABSTRACT FROM AUTHOR]

Spectroscopy focusing array (SFA) and polarimetry focusing array (PFA) are the two major payloads of the enhanced X-ray Timing and Polarimetry mission (eXTP). Nested Wolter-I X-ray mirror module is implemented in SFA and PFA to achieve a high effective area. When evaluating the properties of the mirror module, the alignment of the optical axis of the X-ray mirror module and a quasi-parallel X-ray beam is a prerequisite for ensuring accuracy of the results. To assist the alignment of the X-ray mirror module, an X-ray focal plane detector with one of the largest detection areas, is designed based on a back-illuminated scientific complementary metal–oxide–semiconductor transistor (sCMOS) sensor(GSENSE6060BSI; Gpixel Inc). Then the characteristics of readout noise, dark current, and split-pixel event properties of the detector are studied with the self-developed multi-target fluorescence X-ray source in a 100-m long X-ray test facility. The energy calibration is performed based on the single-pixel event, and the energy non-linearity of the detector is also observed. Finally, based on the optical model, the eXTP mirror module is simulated, and the alignment test of the Wolter-I X-ray mirror module designed for Einstein Probe/Follow-up X-ray Telescope via the "Burkert test" method is demonstrated. [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]

Results characterizing the performance of prototype thin (3µm i layer) GaAs p+–i–n+ mesa photodiodes (one 200µm diameter and one 400µm diameter device) are presented showing the spectral performance of the devices at photon energies from 4.95keV (V Kα1 X-ray fluorescence) to 59.5keV (241Am γ-ray emission). The devices were operated uncooled at +33.3°C. The energy resolution (full width half maximum) was measured to vary from 780eV at 4.95keV to 950eV at 59.5keV for the 200µm diameter diode, and from 1.08keV at 4.95keV to 1.33keV at 59.5keV for the 400µm diameter diode. The increased broadening of FWHM with increasing photon energy was found to be greater than can be explained by the expected energy dependence of the Fano noise, but the peak charge output from the devices varied linearly (R 2 200 µm=0.99998, R 2 400 µm=0.999998) with incident photon energy. [ABSTRACT FROM AUTHOR]

Highlights: [•] A diode was designed in the shape of a silicon cube with p–n junctions on all sides. [•] The purpose was to create an X-ray detector with angular independent response. [•] The cubes were manufactured with a micromachining process. [•] The angular variation in the response was reduced with a factor 7. [ABSTRACT FROM AUTHOR]

Highlights: [•] We proposed new procedure for derivatization of biogenic amines. [•] The NMR and XRD analysis confirmed the purity and uniqueness of derivatives. [•] Concentration of biogenic amines in wine samples were analyzed by RP-HPLC. [•] Sample contamination and derivatization reactions interferences were minimized. [Copyright &y& Elsevier]

Highlights: [•] We synthesized mesopore tobermorite from steel slag in a short time curing. [•] The influence of inorganic admixtures on tobermorite formation was discussed. [•] 2% ordered tobermorite is beneficial to accelerate the hydration of steel slag. [•] Alkali and SO4 2− ions are effective admixtures to the generation of tobermorite. [ABSTRACT FROM AUTHOR]

Abstract: A fast generation method for the X-ray pulsar signal, which utilizes the Gaussian distribution to generate the photon sequence instead of the generally used Poisson distribution, is presented for the simulation system of the X-ray pulsar-based autonomous navigation. Employing the basic principle of the X-ray photon detector, the mathematical model of the Poisson point process of the X-ray pulsar light curve is defined using the cyclostationary inhomogeneous Poisson process at the Solar System Barycenter (SSB). Followed by a brief introduction of the traditional methods, the idea of the signal generation method is introduced based on the pulsar signal model. Then the proposed method is discussed in detail and we give the rigrous proof for its correctness. The dead time of the detector has also been considered in the signal generation procedure. The computational complexity of the proposed method is analyzed and compared with traditional methods. Numerical experiments show that the proposed method greatly reduces the computational complexity compared with the traditional ones. The accordance of the simulated data with the real data is verified by several ways including profile verification, chi-squared test, photon statistics comparison and spectrum analysis. [Copyright &y& Elsevier]

Highlights: [•] [Co(dien)2]3+ has been recognized as a molecular receptor for benzoates. [•] The isomeric identification of [Co(dien)2]3+ was done with the help of spectroscopic studies. [•] Binding constants with benzoates were determined by UV–vis titration method in aqueous medium. [•] X-ray study reveals the formation of chains and layers through second-sphere coordination network. [ABSTRACT FROM AUTHOR]

Abstract: Paternal uniparental disomy 14 (pUPD14) is a rare condition, and only about 30 cases have been reported in Japan. It is characterized by facial abnormalities, a small chest, and ventral abdominal wall defects. An 11-year-old girl with pUPD14 had severe thoracic deformity with a projection on the right side and depression on the left side. On chest X-ray films and CT scans, her chest was narrow, the sternum showed clockwise rotation and depression, and the inferior parts of some ribs protruded anterior to the sternum. We performed a “modified Nuss procedure” to treat the patient's thoracic deformity using a pectus bar. Costal cartilages were resected to increase thoracic mobility, and an anterior incision was made in the sternum down to the marrow to correct her thoracic deformity. Marked improvement was achieved postoperatively. [Copyright &y& Elsevier]

Abstract: Microcalcifications are one of the most common abnormalities detected by mammography for the diagnosis of breast cancer. However, the detection of microcalcifications and correct diagnosis of breast cancer are limited by the sensitivity and specificity of mammography. Therefore, the objective of this study was to investigate the potential of bisphosphonate-functionalized gold nanoparticles (BP-Au NPs) for contrast-enhanced radiographic detection of breast microcalcifications using two models of breast microcalcifications, which allowed for precise control over levels of hydroxyapatite (HA) mineral within a low attenuating matrix. First, an in vitro imaging phantom was prepared with varying concentrations of HA uniformly dispersed in an agarose hydrogel. The X-ray attenuation of HA-agarose compositions labeled by BP-Au NPs was increased by up to 26 HU compared to unlabeled compositions for HA concentrations ranging from 1 to 10 mg/mL. Second, an ex vivo tissue model was developed to more closely mimic the heterogeneity of breast tissue by injecting varying concentrations of HA in a Matrigel carrier into murine mammary glands. The X-ray attenuation of HA-Matrigel compositions labeled by BP-Au NPs was increased by up to 289 HU compared to unlabeled compositions for HA concentrations ranging from 0.5 to 25 mg/mL, which included an HA concentration (0.5 mg/mL) that was otherwise undetectable by micro-computed tomography. Cumulatively, both models demonstrated the ability of BP-Au NPs to enhance contrast for radiographic detection of microcalcifications, including at a clinically-relevant imaging resolution. Therefore, BP-Au NPs may have potential to improve clinical detection of breast microcalcifications by mammography. [Copyright &y& Elsevier]

Abstract: In this paper we present the methods, results, and analysis of the BepiColombo SIXS instruments' ground calibrations. The aim of these calibrations was to characterize the performance of the three SIXS X-ray detectors to enable reliable spectral analysis of the solar X-ray data. The ground calibrations for characterizing the performance of the three separate HPSi (High-Purity Silicon) PIN (Positive Intrinsic Negative) X-ray detectors included the following tasks. Determination of the energy resolution as a function of photon energy at different operational temperatures, determination of the detector sensitivity within the FoV (Field of View) as a function of the off-axis and roll angles, pile-up tests for determining the speed of the read out electronics, measurements of the low energy threshold of the energy scale, i.e. the minimum measurable photon energy corresponding to the adjustable software parameter, a comparison calibration of the fluorescence line fluxes with the SMART-1 XSM FS (Flight Spare) detector, and determination of the shifting of the energy scale as a function of the ambient temperature. We also describe the method and results of determining the geometrical area of the detector apertures based on the image analysis of very high resolution photographs obtained with by the Scanning Electron Microscope (SEM). [Copyright &y& Elsevier]

Abstract: A 1.7MeV tandem accelerator has been recently installed at Centro Atómico Bariloche, Argentina. This communication includes a brief description of the system facility with the main associated equipment, in particular that used for PIXE measurements. The X-ray detector efficiency was experimentally determined by comparing X-ray characteristic spectra with theoretical predictions. The knowledge of this parameter allows us to perform quantification without standards with good precision. We show some recent applications of PIXE in archaeology and forensic science done at our laboratory. In the archaeological field we determined elements constituent of pastes and black, white, brown and ocher pigments from Aguada Portezuelo Culture (600–900 AD). This study allowed us to infer about the presence of psilomelante mineral (a mineral with barium) as precursor of some black pigments. In the forensic field we determined trace elements that are present in seven gunpowders commonly used in Argentina. We note that any gunpowder can be distinguished by the presence of trace elements. [Copyright &y& Elsevier]

Abstract: An X-ray photon detector based on the highly granular readout of an InGrid is described. This gaseous detector, based on a highly pixelized readout chip with an integrated Micromegas grid, allows for a topological analysis of each event and, thus, a distinction between a charged track and a photon conversion is possible in most cases. Because of the high granularity, an energy resolution of 5.2% for 5.9keV photons was observed and a background reduction of a factor of about 120 was achieved, while retaining 95% efficiency for 5.9keV photons. [Copyright &y& Elsevier]

Abstract: We report on the efficiency calibration of a HPGe x-ray detector using radioactive sources and an analytical expression taken from the literature, in two different arrangements, with and without a broad-angle collimator. The frontal surface of the Ge crystal was scanned with pencil beams of photons. The Ge dead layer was found to be nonuniform, with central and intermediate regions that have thin ( range) and thick (mm range) dead layers, respectively, surrounded by an insensitive ring. We discuss how this fact explains the observed efficiency curves and generalize the adopted model. We show that changes in the thickness of the Ge-crystal dead layer affect the efficiency of x-ray detectors, but the use of an appropriate broad-beam external collimator limiting the photon flux to the thin dead layer in the central region leads to the expected efficiency dependence with energy and renders the calibration simpler. [Copyright &y& Elsevier]