Low-dose X-ray Imaging Research Articles

Lead-Free Perovskite With Efficient Tellurium Ion Activation for Multifunctional Applications.

Lead-free perovskite materials have received extensive attention due to their non-toxicity, super environmental stability and adjustable photoelectric properties. However, the inherent problems of low luminous efficiency and low photoluminescence quantum yields (PLQYs) limit its development in multifunctional applications. Here, Te4+ doped Cs2ZrCl6 with high luminous efficiency and stability for multifunctional applications are developed. Te4+ ions are used as emission centers to improve the optical properties of Cs2ZrCl6 to make efficient and stable single-component white light-emitting diodes (WLEDs), and can be used as scintillator materials to improve scintillation performance to achieve high-resolution and low-dose X-ray imaging detection. In addition, it is found for the first time that Te4+ ions can be introduced into the trap center, so that the Cs2ZrCl6:Te4+ perovskite material exhibits excellent persistent luminescence (PersL) and mechanoluminescence (ML) after X-ray radiation, which has potential applications in the fields of delayed imaging and stress sensing. This work provides a method for designing lead-free perovskites with high optical performance and scintillating properties, as well as developing multifunctional applications.

DXA-derived lumbar bone strain index corrected for kyphosis is associated with vertebral fractures and trabecular bone score in acromegaly.

The bone strain index (BSI) is a marker of bone deformation based on a finite element analysis inferred from dual X-ray absorptiometry (DXA) scans, that has been proposed as a predictor of fractures in osteoporosis (i.e., higher BSI indicates a lower bone's resistance to loads with consequent higher risk of fractures). We aimed to investigate the association between lumbar BSI and vertebral fractures (VFs) in acromegaly. Twenty-three patients with acromegaly (13 males, mean age 58 years; three with active disease) were evaluated for morphometric VFs, trabecular bone score (TBS), bone mineral density (BMD) and BSI at lumbar spine, the latter being corrected for the kyphosis as measured by low-dose X-ray imaging system (EOS®-2D/3D). Lumbar BSI was significantly higher in patients with VFs as compared to those without fractures (2.90 ± 1.46 vs. 1.78 ± 0.33, p = 0.041). BSI was inversely associated with TBS (rho -0.44; p = 0.034), without significant associations with BMD (p = 0.151), age (p = 0.500), BMI (p = 0.957), serum IGF-I (p = 0.889), duration of active disease (p = 0.434) and sex (p = 0.563). Lumbar BSI corrected for kyphosis could be proposed as integrated parameter of spine arthropathy and osteopathy in acromegaly helping the clinicians in identifying patients with skeletal fragility possibly predisposed to VFs.

Sensitive and Low-Noise Perovskite Nanocrystal-Organic Bulk Heterostructure X-ray Detectors Enabled by Sodium Bromide-Assisted In Situ Reparation.

Perovskite nanocrystals (PNCs) offer unique advantages in large-area and thick-film deposition for X-ray detection applications due to the decoupling of the crystallization of perovskite from film formation, as well as their low-temperature and scalable deposition methods. However, the partial detachment of long-chain ligands in PNCs during the purification process would lead to the exposure of surface defects, making it challenging to ensure efficient charge carrier extraction and stable X-ray detection. In this study, we propose a beneficial strategy that involves the in situ reparation of these exposed defects with sodium bromide (NaBr) during the purification process to construct CsPbBr3 PNC-organic bulk heterostructure X-ray detectors. The NaBr-passivated PNCs exhibit stronger photoluminescence intensity and lower trap density in films compared to those of the control samples, confirming the effective passivation of halide vacancy defects. Furthermore, the NiOx hole transport layer with remarkable electron blocking capability is introduced to further suppress the dark current of the devices. Consequently, the optimal devices exhibit a large sensitivity of 4237 μC Gyair-1 cm-2 and a low dark current density of 10 nA cm-2, as well as improved operational stability, which allows for high-contrast and low-dose X-ray imaging applications.

HCOO- Doping-Induced Multiexciton Emissions in Cs3Cu2I5 Crystals for Efficient X-Ray Scintillation.

Self-trapped exciton (STE) luminescence, typically associated with structural deformation of excited states, has attracted significant attention in metal halide materials recently. However, the mechanism of multiexciton STE emissions in certain metal halide crystals remains largely unexplored. This study investigates dual luminescence emissions in HCOO- doped Cs3Cu2I5 single crystals using transient and steady-state spectroscopy. The dual emissions are attributed to intrinsic STE luminescence originating from the host lattice and extrinsic STE luminescence induced by external dopants, respectively, each of which can be triggered independently at distinct energy levels. Theoretical calculations reveal that multiexciton emission originates from structural distortion of the host and dopant STEs within the 0D lattice in their respective excited states. By meticulously tuning the excitation wavelength and selectively exciting different STEs, the dynamic alteration of color change in Cs3Cu2I5:HCOO- crystals is demonstrated. Ultimately, owing to an extraordinarily high photoluminescence quantum yield (99.01%) and a diminished degree of self-absorption in Cs3Cu2I5:HCOO- crystals, they exhibit remarkable X-ray scintillation characteristics with light yield being improved by 5.4 times as compared to that of pristine Cs3Cu2I5 crystals, opening up exciting avenues for achieving low-dose X-ray detection and imaging.

Achieving Low-Dose Rate X-Ray Imaging Based on 2D/3D-Mixed Perovskite Films.

X-ray detection and imaging are widely used in medical diagnosis, product inspection, security monitoring, etc. Large-scale polycrystalline perovskite thick films possess high potential for direct X-ray imaging. However, the notorious problems of baseline drift and high detection limit caused by ions migration are still remained. Here, ion migration is reduced by incorporating 2D perovskite into 3D perovskite, thereby increasing the ion activation energy. This approach hinders ion migration within the perovskite film, consequently suppressing baseline drift and reducing the lowest detection limit(LOD) of the device. As a result, the baseline drifting declines by 20 times and the LOD reduces to 21.1nGys-1, while the device maintains a satisfactory sensitivity of 5.6×103µCGy-1cm-2. This work provides a new strategy to achieve low ion migration in large-scale X-ray detectors and may provide new thoughts for the application of mixed-dimension perovskite.

All-Inorganic Ruddlesden–Popper Perovskite Cs2CdCl4:Mn for Low-Dose and Flexible X-ray Imaging

All-Inorganic Ruddlesden–Popper Perovskite Cs₂CdCl₄:Mn for Low-Dose and Flexible X-ray Imaging

Dynamic X-ray imaging with screen-printed perovskite CMOS array.

High performance X-ray detector with ultra-high spatial and temporal resolution are crucial for biomedical imaging. This study reports a dynamic direct-conversion CMOS X-ray detector assembled with screen-printed CsPbBr3, whose mobility-lifetime product is 5.2 × 10-4 cm2 V-1 and X-ray sensitivity is 1.6 × 104 µC Gyair-1 cm-2. Samples larger than 5 cm[Formula: see text]10 cm can be rapidly imaged by scanning this detector at a speed of 300 frames per second along the vertical and horizontal directions. In comparison to traditional indirect-conversion CMOS X-ray detector, this perovskite CMOS detector offers high spatial resolution (5.0 lp mm-1) X-ray radiographic imaging capability at low radiation dose (260 nGy). Moreover, 3D tomographic images of a biological specimen are also successfully reconstructed. These results highlight the perovskite CMOS detector's potential in high-resolution, large-area, low-dose dynamic biomedical X-ray and CT imaging, as well as in non-destructive X-ray testing and security scanning.

General Algorithm Applicability in Determining DBS Lead Orientation: Adapting 2D and 3D X-Ray Techniques for SenSightTM Leads

Introduction: With recent advancements in deep brain stimulation (DBS), directional leads featuring segmented contacts have been introduced, allowing for targeted stimulation of specific brain regions. Given that manufacturers employ diverse markers for lead orientation, our investigation focuses on the adaptability of the 2017 techniques proposed by the Cologne research group for lead orientation determination. Methods: We tailored the two separate 2D and 3D X-ray-based techniques published in 2017 and originally developed for C-shaped markers, to the dual-marker of the Medtronic SenSight™ lead. In a retrospective patient study, we evaluated their feasibility and consistency by comparing the degree of agreement between the two methods. Results: The Bland-Altman plot showed favorable concordance without any noticeable systematic errors. The mean difference was 0.79°, with limits of agreement spanning from 21.4° to −19.8°. The algorithms demonstrated high reliability, evidenced by an intraclass correlation coefficient of 0.99 (p < 0.001). Conclusion: The 2D and 3D algorithms, initially formulated for discerning the circular orientation of a C-shaped marker, were adapted to the marker of the Medtronic SenSight™ lead. Statistical analyses revealed a significant level of agreement between the two methods. Our findings highlight the adaptability of these algorithms to different markers, achievable through both low-dose intraoperative 2D X-ray imaging and standard CT imaging.

Novel reconstruction method of angle-limited backprojection (ALBP) for low-dose dental panoramic X-ray imaging

Panoramic radiography is a popular two-dimensional X-ray imaging modality in dentistry. It produces a single image of the overall facial view, including the maxillary and mandibular arches and supporting structures. Panoramic images are typically reconstructed using the shift-and-add (SAA) algorithm, in which only structures within a certain image layer are in focus, and others are out of focus on the panoramic image. As the clinical use of panoramic radiography has grown rapidly, radiologists are continuously seeking ways to reduce the radiation dose to patients. This study proposes a novel panoramic reconstruction method called the angle-limited backprojection (ALBP) algorithm for low-dose panoramic X-ray imaging. In ALBP, X-rays that meet the angular criterion established in this study are selected from the measured panoramic projection data and then backprojected onto the spherical voxels placed along the dental arch, as in a typical computed tomography reconstruction. The angular criterion selects X-rays that pass through a given spherical voxel and simultaneously have directional vectors within a prespecified angular range concerning the directional vector at the corresponding source position. To validate the efficacy of the proposed reconstruction method, we conducted a numerical simulation and experiment and investigated the image characteristics. Panoramic images were reconstructed using the SAA and ALBP algorithms with full and half (i.e., half radiation dose) panoramic projections, and their image quality was quantitatively evaluated using the intensity profile and universal quality index (UQI). The image quality of the ALBP with half projections was similar to that of the SAA with full projections, indicating the efficacy of the proposed method. Accordingly, our results demonstrated the potential for radiation dose reduction in panoramic X-ray imaging.

Bright Green-Emitting All-Inorganic Terbium Halide Double Perovskite Nanocrystals for Low-Dose X-ray Imaging.

Inorganic halide double perovskite (DP) nanocrystals (NCs) have attracted great attention because of their nontoxicity, mild reaction conditions, good stability, and excellent optical and optoelectronic properties. Herein, we prepare the inorganic terbium halide DP Cs2BTbCl6 (B = Na or Ag) NCs with bright green photoluminescence (PL) emission. The Na-Tb-based DP NCs exhibit better PL properties compared with the Ag-Tb-based DP NCs, which is due to Cs2NaTbCl6 NCs having a more localized charge carrier distribution on the [TbCl6]3- octahedron. The incorporation of Sb3+ dopant in Cs2NaTbCl6 NCs can construct a more efficient energy transfer process, resulting in a doubling of PL efficiency. Furthermore, Cs2NaTbCl6: Sb3+ NCs possess excellent X-ray scintillating performance with a low-dose detection limit of 140 nGyair/s, which is nearly 5 times more sensitive than the undoped NCs. The optimized NCs show great application prospects in X-ray imaging. This work helps deepen the understanding of the luminescence mechanism, excited state dynamics, and scintillation property in Tb-based DP NCs.

Low-Dose CT Image Synthesis for Domain Adaptation Imaging Using a Generative Adversarial Network With Noise Encoding Transfer Learning.

Deep learning (DL) based image processing methods have been successfully applied to low-dose x-ray images based on the assumption that the feature distribution of the training data is consistent with that of the test data. However, low-dose computed tomography (LDCT) images from different commercial scanners may contain different amounts and types of image noise, violating this assumption. Moreover, in the application of DL based image processing methods to LDCT, the feature distributions of LDCT images from simulation and clinical CT examination can be quite different. Therefore, the network models trained with simulated image data or LDCT images from one specific scanner may not work well for another CT scanner and image processing task. To solve such domain adaptation problem, in this study, a novel generative adversarial network (GAN) with noise encoding transfer learning (NETL), or GAN-NETL, is proposed to generate a paired dataset with a different noise style. Specifically, we proposed a method to perform noise encoding operator and incorporate it into the generator to extract a noise style. Meanwhile, with a transfer learning (TL) approach, the image noise encoding operator transformed the noise type of the source domain to that of the target domain for realistic noise generation. One public and two private datasets are used to evaluate the proposed method. Experiment results demonstrated the feasibility and effectiveness of our proposed GAN-NETL model in LDCT image synthesis. In addition, we conduct additional image denoising study using the synthesized clinical LDCT data, which verified the merit of the proposed synthesis in improving the performance of the DL based LDCT processing method.

2D Perovskite Mn2+ -Doped Cs2 CdBr2 Cl2 Scintillator for Low-Dose High-Resolution X-ray Imaging.

High-performance X-ray scintillators with low detection limits and high light yield are of great importance and are a challenge for low-dose X-ray imaging in medical diagnosis and industrial detection. In this work, the synthesis of a new 2D perovskite, Cs2 CdBr2 Cl2 , via hydrothermal reaction is reported. By doping Mn2+ into the perovskite, a yellow emission located at 593nm is obtained, and the photoluminescence quantum yield (PLQY) of Cs2 CdBr2 Cl2 :5%Mn2+ perovskite reaches the highest value of 98.52%. The near-unity PLQY and negligible self-absorption of Cs2 CdBr2 Cl2 :5%Mn2+ enable excellent X-ray scintillation performance with a high light yield of 64 950 photons MeV-1 and low detection limit of 17.82 nGyair s-1 . Moreover, combining Cs2 CdBr2 Cl2 :5%Mn2+ with poly(dimethylsiloxane) to fabricate a flexible scintillator screen achieves low-dose X-ray imaging with a high resolution of 12.3 line pairs (lp) mm-1 . The results suggest that Cs2 CdBr2 Cl2 :5%Mn2+ is a promising candidate for low-dose and high-resolution X-ray imaging. The study presents a new approach to designing high-performance scintillators through metal-ion doping.

Stable perovskite single-crystal X-ray imaging detectors with single-photon sensitivity

A major thrust of medical X-ray imaging is to minimize the X-ray dose acquired by the patient, down to single-photon sensitivity. Such characteristics have been demonstrated with only a few direct-detection semiconductor materials such as CdTe and Si; nonetheless, their industrial deployment in medical diagnostics is still impeded by elaborate and costly fabrication processes. Hybrid lead halide perovskites can be a viable alternative owing to their facile solution growth. However, hybrid perovskites are unstable under high-field biasing in X-ray detectors, owing to structural lability and mixed electronic–ionic conductivity. Here we show that both single-photon-counting and long-term stable performance of perovskite X-ray detectors are attained in the photovoltaic mode of operation at zero-voltage bias, employing thick and uniform methylammonium lead iodide single-crystal films (up to 300 µm) and solution directly grown on hole-transporting electrodes. The operational device stability exceeded one year. Detection efficiency of 88% and noise-equivalent dose of 90 pGyair are obtained with 18 keV X-rays, allowing single-photon-sensitive, low-dose and energy-resolved X-ray imaging. Array detectors demonstrate high spatial resolution up to 11 lp mm−1. These findings pave the path for the implementation of hybrid perovskites in low-cost, low-dose commercial detector arrays for X-ray imaging.

High-Performance and Self-Powered X-Ray Detectors Made of Smooth Perovskite Microcrystalline Films with 100-μm Grains.

Perovskite single crystals and polycrystalline films have complementary merits and deficiencies in X-ray detection and imaging. Herein, we report preparation of dense and smooth perovskite microcrystalline films with both merits of single crystals and polycrystalline films through polycrystal-induced growth and hot-pressing treatment (HPT). Utilizing polycrystalline films as seeds, multi-inch-sized microcrystalline films can be in-situ grown on diverse substrates with maximum grain size reaching 100 μm, which endows the microcrystalline films with comparable carrier mobility-lifetime (μτ) product as single crystals. As a result, self-powered X-ray detectors with impressive sensitivity of 6.1 × 104 μC Gyair-1 cm-2 and low detection limit of 1.5 nGyair s-1 are achieved, leading to high-contrast X-ray imaging at an ultra-low dose rate of 67 nGyair s-1. Combining with the fast response speed (186 μs), this work may contribute to the development of perovskite-based low-dose X-ray imaging.

Enhancing light yield of Tb3+-doped fluoride nanoscintillator with restricted positive hysteresis for low-dose high-resolution X-ray imaging

Enhancing light yield of Tb3+-doped fluoride nanoscintillator with restricted positive hysteresis for low-dose high-resolution X-ray imaging

Number of Convolution Layers and Convolution Kernel Determination and Validation for Multilayer Convolutional Neural Network: Case Study in Breast Lesion Screening of Mammographic Images

Mammography is a low-dose X-ray imaging technique that can detect breast tumors, cysts, and calcifications, which can aid in detecting potential breast cancer in the early stage and reduce the mortality rate. This study employed a multilayer convolutional neural network (MCNN) to screen breast lesions with mammographic images. Within the region of interest, a specific bounding box is used to extract feature maps before automatic image segmentation and feature classification are conducted. These include three classes, namely, normal, benign tumor, and malignant tumor. Multiconvolution processes with kernel convolution operations have noise removal and sharpening effects that are better than other image processing methods, which can strengthen the features of the desired object and contour and increase the classifier’s classification accuracy. However, excessive convolution layers and kernel convolution operations will increase the computational complexity, computational time, and training time for training the classifier. Thus, this study aimed to determine a suitable number of convolution layers and kernels to achieve a classifier with high learning performance and classification accuracy, with a case study in the breast lesion screening of mammographic images. The Mammographic Image Analysis Society Digital Mammogram Database (United Kingdom National Breast Screening Program) was used for experimental tests to determine the number of convolution layers and kernels. The optimal classifier’s performance is evaluated using accuracy (%), precision (%), recall (%), and F1 score to test and validate the most suitable MCNN model architecture.

Fabrication of nanocrystalline Ga2O3-NiO heterojunctions for large-area low-dose X-ray imaging

The Ga2O3 photoconductor possesses a wide bandgap, a relatively large density and a high absorption coefficient for low-energy X-ray. Therefore, it is expected to realize a highly sensitive low-energy X-ray detector. Realizing p-n heterojunctions using Ga2O3 thin film is essential for large-area low-dose X-ray imaging. Here, a p-n diode consisting of nanocrystalline Ga2O3 thin film and NiO thin film is successfully prepared by electron beam evaporation, exhibiting a large current rectification ratio of 6.0 × 104. The p-n heterojunction shows a large valence band offset of 1.7 eV, a large conduction band offset of 0.84 eV and a built-in potential of 0.2 eV near the interfacial region, benefiting for separation and migration of photogenerated carriers. In addition, the photoconductive gain mechanism of Ga2O3/NiO heterojunction based X-ray detectors with optimized NiO thickness is investigated, achieving a high internal gain (3.3 × 103), a high sensitivity (3.4 × 104 μCGyair−1 cm−2), a low detection limit (42 μGyair s−1) and a short response time (2.2 ms). The optimized detectors with 10 × 10 pixels show a uniform X-ray response, demonstrating their promising use in large-area X-ray imaging applications.

Statistical changes of lung morphology in patients with adolescent idiopathic scoliosis after spinal fusion surgery-a prospective nonrandomized study based on low-dose biplanar X-ray imaging.

Adolescent idiopathic scoliosis (AIS) patients suffer from restrictive impairment of pulmonary function (PF) as a consequence of spinal and ribcage deformity. Statistic modelling of scoliotic geometry has been well-established based on low-dose biplanar X-ray device (EOS) imaging. However, the postoperative lung morphology change derived from EOS has not yet been studied adequately till now. Twenty-five female AIS patients with severe right-sided major thoracic curve (aged 13-31 years; Cobb angle 45°-92°) underwent posterior spinal fusion (PSF) were prospectively recruited for standing EOS imaging at preoperative, postoperative, and 1-year follow-up (1Y-FU) stages. EOS-based lung morphology at frontal and lateral view was measured respectively to assess serial statistical changes in area and height. At frontal view, left lung area significantly increased postoperatively (104.7 vs. 125.1 cm2; P<0.001) but without continuous increase at 1Y-FU (125.1 vs. 124.5 cm2; P=0.084), whereas right lung area showed a slight but insignificant interval increase (median: 143.8, 146.5, 148.4 cm2 at preoperative, postoperative, 1Y-FU stage, respectively; all P>0.05). At lateral view, the increase in left lung area was slight without statistically difference (median: 175.8, 178.4, 182.5 cm2 at preoperative, postoperative, 1Y-FU stage, respectively; all P>0.05), while right lung area did not significantly change postoperatively (median: 209.9, 206.7, 212.4 cm2 at preoperative, postoperative, 1Y-FU stage, respectively; all P>0.05). At both frontal and lateral view, left lung height significantly improved at both postoperative and 1Y-FU stage (all P<0.05), while preoperative right lung height was not significantly different from postoperative and 1Y-FU value (all P>0.05). EOS imaging demonstrates that left lung area in severe AIS may improve after PSF surgery. EOS may provide useful information about lung morphology change after PSF in severe AIS.

Robust learning-based x-ray image denoising—potential pitfalls, their analysis and solutions

Purpose: Since guidance based on x-ray imaging is an integral part of interventional procedures, continuous efforts are taken towards reducing the exposure of patients and clinical staff to ionizing radiation. Even though a reduction in the x-ray dose may lower associated radiation risks, it is likely to impair the quality of the acquired images, potentially making it more difficult for physicians to carry out their procedures. Method: We present a robust learning-based denoising strategy involving model-based simulations of low-dose x-ray images during the training phase. The method also utilizes a data-driven normalization step—based on an x-ray imaging model—to stabilize the mixed signal-dependent noise associated with x-ray images. We thoroughly analyze the method’s sensitivity to a mismatch in dose levels used for training and application. We also study the impact of differing noise models used when training for low and very low-dose x-ray images on the denoising results. Results: A quantitative and qualitative analysis based on acquired phantom and clinical data has shown that the proposed learning-based strategy is stable across different dose levels and yields excellent denoising results, if an accurate noise model is applied. We also found that there can be severe artifacts when the noise characteristics of the training images are significantly different from those in the actual images to be processed. This problem can be especially acute at very low dose levels. During a thorough analysis of our experimental results, we further discovered that viewing the results from the perspective of denoising via thresholding of sub-band coefficients can be very beneficial to get a better understanding of the proposed learning-based denoising strategy. Conclusion: The proposed learning-based denoising strategy provides scope for significant x-ray dose reduction without the loss of important image information if the characteristics of noise is accurately accounted for during the training phase.

Analysis of Performance of Two Wavelet Families Using GLCM Feature Extraction for Mammogram Classification of Breast Cancer

Background: Mammogram images are low dose x-ray images which detect the breast cancer before the women can actually experience it. Objective: To determine the accurate methodology for feature extraction using different wavelet families and different classification algorithms. Methods: Two wavelet families are used namely Daubechies (db8) and Biorthogonal (bior3.7). The Gray-Level Co-occurrence Matrix is used for extracting 9 features at each sub-band. 27 features are extracted at three sub-bands of Discrete Wavelet Transform. The features are extracted at three levels of decomposition and after that the classification algorithm named as Naive Bayes, Multilayer Perceptron, Fuzzy-NN and Genetic Programming are applied to extracted features. The feature selection algorithms are applied named as Wavelet and Principle Component Analysis for selecting the features and then classification accuracy is determined and compared between these. Results: Mammographic Image Analysis Society, database including 322 mammogram images from 161 patients is used. The classification algorithm without feature selection named as Fuzzy-NN gives better results at the third level of decomposition having classification accuracy for db8 wavelet family up to 99.68% and for bior3.7 wavelet family up to 99.98%. Wavelet with Multilayer Perceptron using feature selection algorithm gives the classification accuracy for db8 wavelet family up to 96.27% and for bior3.7 up to 93.47%. Conclusion: Fuzzy-NN algorithm gives highest accuracy of 99.98% for bior3.7 wavelet family. It indicates that with feature selection and without feature selection, the wavelet families differ as db8 is better consideration for with feature selection and bior3.7 wavelet family for without feature selection.