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Objectives: To compare the visibility of anatomical structures and overall quality of the attenuation images obtained with a dark-field X-ray radiography prototype with those from a commercial radiography system. Methods: Each of the 65 patients recruited for this study obtained a thorax radiograph at the prototype and a reference radiograph at the commercial system. Five radiologists independently assessed the visibility of anatomical structures, the level of motion artifacts, and the overall image quality of all attenuation images on a five-point scale, with 5 points being the highest rating. The average scores were compared between the two image types. The differences were evaluated using an area under the curve (AUC) based z-test with a significance level of p ≤ 0.05. To assess the variability among the images, the distributions of the average scores per image were compared between the systems. Results: The overall image quality was rated high for both devices, 4.2 for the prototype and 4.6 for the commercial system. The rating scores varied only slightly between both image types, especially for structures relevant to lung assessment, where the images from the commercial system were graded slightly higher. The differences were statistically significant for all criteria except for the bronchial structures, the cardiophrenic recess, and the carina. Conclusions: The attenuation images acquired with the prototype were assigned a high diagnostic quality despite a lower resolution and the presence of motion artifacts. Thus, the attenuation-based radiographs from the prototype can be used for diagnosis, eliminating the need for an additional conventional radiograph. Key Points: • Despite a low tube voltage (70 kVp) and comparably long acquisition time, the attenuation images from the dark-field chest radiography system achieved diagnostic quality for lung assessment. • Commercial chest radiographs obtained a mean rating score regarding their diagnostic quality of 4.6 out of 5, and the grating-based images had a slightly lower mean rating score of 4.2 out of 5. • The difference in rating scores for anatomical structures relevant to lung assessment is below 5%. [ABSTRACT FROM AUTHOR]

This work presents an approach for image reconstruction in clinical low-dose tomography that combines principles from sparse signal processing with ideas from deep learning. First, we describe sparse signal representation in terms of dictionaries from a statistical perspective and interpret dictionary learning as a process of aligning the distribution that arises from a generative model with the empirical distribution of true signals. As a result, we can see that sparse coding with learned dictionaries resembles a specific variational autoencoder, where the encoder is a sparse coding algorithm and the decoder is a linear function. Next, we show that dictionary learning can also benefit from computational advancements introduced in the context of deep learning, such as parallelism and stochastic optimization. Finally, we show that regularization by dictionaries achieves competitive performance in computed tomography reconstruction compared to state-of-the-art model-based and data-driven approaches, while being unsupervised with respect to tomographic data. [ABSTRACT FROM AUTHOR]

Introduction: The fourth industrial revolution or industry 4.0 has brought a variety of technologies to different societies. One of these technologies is the Internet of Things (IoT), primarily conceptualized in engineering fields and then found its way to the field of education. Internet of Everything (IoE) has been discussed in the evolution of the IoT concept. IoE mainly focuses on things, people, processes, and data. This paper aims to investigate different studies from the emergence of IoT concept and its development to IoE based teaching-learning process. Methods: The integrative review was applied as the research method, Web of Science and Scopus databases were directly investigated and 139 articles were finalized as the result of this integrative review. Results: F indings o f this study d emonstrated t hat t he t eachinglearning process with the focus on IoE could be categorized into logic models, including inputs, activities, outputs, outcomes, and external factors. Based on extracted components, the final model showed that the teaching learning approach with the focus on IoE is a process that mainly occurs through integration and connection of IoT-based infrastructures, stakeholder's interactions, teaching and learning activities. Eventually, this has brought personal and general outputs to achieve sustainability, Green IoT, and meeting the needs of industry. Simultaneously with the implementation or application of this system, several challenges can arise in the process, namely Security, Privacy, Financing, Reliable connectivity, and Cloud infrastructure. Conclusion: Therefore, this model can help policymakers or educators to be aware of the different parts of an IoE-based education system. [ABSTRACT FROM AUTHOR]

There are many studies about nurses' intention to leave their jobs and contributing factors. However, there is a lack of research about generational differences in nurses' intention to leave. This evidence may help with workforce planning and targeting specific generations of nurses with retention interventions. Using the National Database of Nursing Quality Indicators 2018 Annual Registered Nurse Survey, we used descriptive statistics and multivariate logistic regression to examine the prevalence of and reasons for nurses' intention to leave in the next year by generational age group. Our sample included 207,636 hospital nurses from across the United States. We found that 21% of nurses (n = 44,082) reported intention to leave. When comparing generations, there were differences in intention to leave, as well as differences in potentially preventable, career advancement, and personal intention to leave reasons. Workload/staffing was a common reason across generations, indicating that certain interventions may be applicable regardless of generation. [ABSTRACT FROM AUTHOR]

Dark-field radiography of the human chest is a promising novel imaging technique with the potential of becoming a valuable tool for the early diagnosis of chronic obstructive pulmonary disease and other diseases of the lung. The large field-of-view needed for clinical purposes could recently be achieved by a scanning system. While this approach overcomes the limited availability of large area grating structures, it also results in a prolonged image acquisition time, leading to concomitant motion artifacts caused by intrathoracic movements (e.g. the heartbeat). Here we report on a motion artifact reduction algorithm for a dark-field X-ray scanning system, and its successful evaluation in a simulated chest phantom and human in vivo chest X-ray dark-field data. By partitioning the acquired data into virtual scans with shortened acquisition time, such motion artifacts may be reduced or even fully avoided. Our results demonstrate that motion artifacts (e.g. induced by cardiac motion or diaphragmatic movements) can effectively be reduced, thus significantly improving the image quality of dark-field chest radiographs. [ABSTRACT FROM AUTHOR]

The purpose of the study reported in this article was to investigate the contribution of engaging in an online Teacher Professional Development (oTPD) course to improving different facets of English as Foreign Language (EFL) teachers' Professional Development (PD). To this end, ten EFL teachers of a language institute participated in the study to be taught via Telegram mobile app (as a common Mobile Social Network Site (MSNS) in Iran) during a six-month teacher training project. A 35-item technology-enhanced TPD checklist consisting of several main sections incorporating demographic items, background information, and different issues regarding TPD was designed to measure EFL teachers' self-report TPD scores at the outset and end of the training course. Results pointed to the positive effects of oTPD course on participants' PD across different facets. The obtained findings have some implications for teacher educators, syllabus designers and practitioners in EFL contexts to have a fresh look at the complicated construct of PD including several facets, consider using MSNSs in teacher education and TPD courses, prepare online teacher education courses based on teachers' needs and opinions and provide teachers with follow-up support by devoting an elapsed time between teachers' participation in oTPD and application of their learning in the course. [ABSTRACT FROM AUTHOR]

X-ray computed tomography (CT) is one of the most commonly used three-dimensional medical imaging modalities today. It has been refined over several decades, with the most recent innovations including dual-energy and spectral photon-counting technologies. Nevertheless, it has been discovered that waveoptical contrast mechanisms—beyond the presently used X-ray attenuation—offer the potential of complementary information, particularly on otherwise unresolved tissue microstructure. One such approach is dark-field imaging, which has recently been introduced and already demonstrated significantly improved radiological benefit in small-animal models, especially for lung diseases. Until now, however, dark-field CT could not yet be translated to the human scale and has been restricted to benchtop and small-animal systems, with scan durations of several minutes or more. This is mainly because the adaption and upscaling to the mechanical complexity, speed, and size of a human CT scanner so far remained an unsolved challenge. Here, we now report the successful integration of a Talbot–Lau interferometer into a clinical CT gantry and present dark-field CT results of a humansized anthropomorphic body phantom, reconstructed from a single rotation scan performed in 1 s. Moreover, we present our key hardware and software solutions to the previously unsolved roadblocks, which so far have kept dark-field CT from being translated from the optical bench into a rapidly rotating CT gantry, with all its associated challenges like vibrations, continuous rotation, and large field of view. This development enables clinical dark-field CT studies with human patients in the near future. [ABSTRACT FROM AUTHOR]

A mapping population (Reg. no. MP‐15, NSL 540708 MAP) composed of a cross between the soft white common winter wheat (Triticum aestivum L. subsp. aestivum) 'Brundage' (PI 599193) and the soft white club winter wheat (T. aestivum L. subsp. compactum) 'Coda' (PI 594372) was developed to maximize diversity within the soft white market class. The population comprises 268 F6:7 lines developed through single seed descent. The genetic linkage map consists of 2,144 DNA markers and is assigned to 32 linkage groups covering all chromosomes except 1D. This population was initially developed to determine additional markers linked to the Pch1 gene in wheat. It has further been used to identify quantitative trait loci (QTL) associated with resistance to other diseases such as Cephalosporium stripe (caused by Cephalosporium gramineum) and stripe rust (caused by Puccinia striiformis Westend. f. sp. tritici Erikss). The mapping population has also been used for identification of DNA markers associated with freezing tolerance, end‐use quality, and the compactum locus. From the differences in traits between the parental lines, the Coda/Brundage population provides the opportunity for further inquiry into the genes behind the identified QTL. The parents have only been phenotypically screened for a limited number of traits, and further screening may identify more polymorphic traits which the population can be used to map. It can also serve as a validation population for marker‐trait associations identified in other populations or other genetic studies such as recombination frequency. Core Ideas: RIL population from parents with differing traits can maximize the number of traits for study.Linkage maps and QTL for various traits have been determined from genetic analyses thus far.With known genetic information for this population, additional mapping studies are feasible. [ABSTRACT FROM AUTHOR]

X-ray dark-field imaging is a widely researched imaging technique, with many studies on samples of very different dimensions and at very different resolutions. However, retrieval of three-dimensional (3D) information for human thorax sized objects has not yet been demonstrated. We present a method, similar to classic tomography and tomosynthesis, to obtain 3D information in X-ray dark-field imaging. Here, the sample is moved through the divergent beam of a Talbot–Lau interferometer. Projections of features at different distances from the source seemingly move with different velocities over the detector, due to the cone beam geometry. The reconstruction of different focal planes exploits this effect. We imaged a chest phantom and were able to locate different features in the sample (e.g. the ribs, and two sample vials filled with water and air and placed in the phantom) to corresponding focal planes. Furthermore, we found that image quality and detectability of features is sufficient for image reconstruction with a dose of 68 μSv at an effective pixel size of 0.357 × 0.357 mm 2 . Therefore, we successfully demonstrated that the presented method is able to retrieve 3D information in X-ray dark-field imaging. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study was to evaluate the dose characteristic for patient examinations at the first clinical X‐ray dark‐field chest radiography system and to determine whether the effective patient dose is within a clinically acceptable dose range. Methods: A clinical setup for grating‐based dark‐field chest radiography was constructed and commissioned, operating at a tube voltage of 70 kVp. Thermoluminescent dosimeter (TLD) measurements were conducted using an anthropomorphic phantom modeling the reference person to obtain a conversion coefficient relating dose area product (DAP) to effective patient dose at the dark‐field system. For 92 patients, the DAP values for posterior–anterior measurements were collected at the dark‐field system. Using the previously determined conversion coefficient, the effective dose was calculated. Results: A reference person, modeled by an anthropomorphic phantom, receives an effective dose of 35 µSv. For the examined patients, a mean effective dose of 39 µSv was found. Conclusions: The effective dose at the clinical dark‐field radiography system, generating both attenuation and dark‐field images, is within the range of reported standard dose values for chest radiography. [ABSTRACT FROM AUTHOR]

Background: Grating-based x-ray dark-field and phase-contrast imaging allow extracting information about refraction and small-angle scatter, beyond conventional attenuation. A step towards clinical translation has recently been achieved, allowing further investigation on humans. Methods: After the ethics committee approval, we scanned the full body of a human cadaver in anterior-posterior orientation. Six measurements were stitched together to form the whole-body image. All radiographs were taken at a three-grating large-object x-ray dark-field scanner, each lasting about 40 s. Signal intensities of different anatomical regions were assessed. The magnitude of visibility reduction caused by beam hardening instead of small-angle scatter was analysed using different phantom materials. Maximal effective dose was 0.3 mSv for the abdomen. Results: Combined attenuation and dark-field radiography are technically possible throughout a whole human body. High signal levels were found in several bony structures, foreign materials, and the lung. Signal levels were 0.25 ± 0.13 (mean ± standard deviation) for the lungs, 0.08 ± 0.06 for the bones, 0.023 ± 0.019 for soft tissue, and 0.30 ± 0.02 for an antibiotic bead chain. We found that phantom materials, which do not produce small-angle scatter, can generate a strong visibility reduction signal. Conclusion: We acquired a whole-body x-ray dark-field radiograph of a human body in few minutes with an effective dose in a clinical acceptable range. Our findings suggest that the observed visibility reduction in the bone and metal is dominated by beam hardening and that the true dark-field signal in the lung is therefore much higher than that of the bone. [ABSTRACT FROM AUTHOR]

The purpose of this study was three-fold: first, it aimed to develop a scale to shed light on English as Foreign Language (EFL) teachers' perceptions of using Mobile Social Network Sites (MSNSs) in language teaching and learning. To this end, a 36-item MSNSs Utility Perceptions Inventory (MUPI) was developed. Second, the current study made an attempt to investigate the construct validity and reliability of the MUPI through collecting data from 184 Iranian EFL teachers. The factorability of the data has been substantiated by running Kaiser-Meyer-Olkin test of Sampling Adequacy (KMO) and Bartlett's Test of Sphericity. The results of Exploratory Factor Analysis (EFA) revealed a three-factor solution for the inventory items. Furthermore, it was deemed that the scale had a high level of internal consistency. Third, this study strove to explore EFL teachers' perceptions of MSNSs use by analyzing the results of the administered scale. The findings showed that teachers put more emphasis on factor one (Advantages of MSNSs for Teaching and Learning) and factor three (Barriers to Using MSNSs for Teaching and Learning). The findings also indicated that approximately half of the teachers believed MSNSs allow them to have a more detailed, in depth conversation with their peers and colleagues in the course. Moreover, student distraction, insufficient Internet bandwidth/speed, and insufficient technical support for teachers were some barriers to using MSNSs in classrooms. It was also confirmed that developing communication skills, increasing communication, motivating students, and sharing feedback are some advantages of using MSNSs for teaching and learning. This study has some implications for EFL teachers, teacher educators, and syllabus designers to pay particular attention to the positive features of MSNSs and harness their pedagogical benefits in English language teaching and learning on the one hand, and teacher education courses on the other hand. [ABSTRACT FROM AUTHOR]

Objectives: Grating-interferometry-based mammography (GIM) might facilitate breast cancer detection, as several research works have demonstrated in a pre-clinical setting, since it is able to provide attenuation, differential phase contrast, and scattering images simultaneously. In order to translate this technique to the clinics, it has to be adapted to cover a large field-of-view within a clinically acceptable exposure time and radiation dose.Methods: We set up a grating interferometer that fits into a standard mammography system and fulfilled the aforementioned conditions. Here, we present the first mastectomy images acquired with this experimental device.Results and Conclusion: Our system performs at a mean glandular dose of 1.6 mGy for a 5-cm-thick, 18%-dense breast, and a field-of-view of 26 × 21 cm2. It seems to be well-suited as basis for a clinical-environment device. Further, dark-field signals seem to support an improved lesion visualization. Evidently, the effective impact of such indications must be evaluated and quantified within the context of a proper reader study.Key Points: • Grating-interferometry-based mammography (GIM) might facilitate breast cancer detection, since it is sensitive to refraction and scattering and thus provides additional tissue information. • The most straightforward way to do grating-interferometry in the clinics is to modify a standard mammography device. • In a first approximation, the doses given with this technique seem to be similar to those of conventional mammography. [ABSTRACT FROM AUTHOR]

This study employs cloud-to-ground (CG) lightning flash data from the U.S. National Lightning Detection Network (NLDN) to examine temporal and spatial distributions of lightning flash and thunderstorm day (TD) occurrences over the contiguous United States from 1993 to 2018.TDdistributions are estimated fromNLDN CG flashes using 4 thunder audibility approximations: 5 and 10 nautical mile (n mi; 1 n mi 5 1.852 km) audibility ranges, and minima of 1 and 2 flashes within the audibility range. The 26-yr period examined is longer than previous studies using NLDN data, and the TD results can be compared directly to climatologies derived from surface weather observations dating back to the late 1890s. Results based on the abundant NLDN data avoid limitations introduced by the coarse horizontal resolution of surface observations inherent in pre-NLDN TD climatologies. Annual mean flash density and annual and monthly mean TD distributions are derived from almost 568 million NLDN CG flashes. A mean annual maximum of more than 16 flashes km-2 is found near Tampa, Florida. The mean annual TD maximum of 113 days (from at least 2 flashes within 10 n mi) occurs in southern Florida. Regions exceeding 70 TDs are found from eastern Texas eastward into Florida, and over the southern Rocky Mountains. Large positive deviations from the mean number of TDs extend from Texas northwestward into Colorado during 2003-07, followed by large negative deviations over the same region during 2008-12. Both deviation patterns are similar to expected summertime precipitation anomaly patterns over the United States during El Niño and La Niña years, respectively. [ABSTRACT FROM AUTHOR]

Lung tissue causes significant small-angle X-ray scattering, which can be visualized with grating-based X-ray dark-field imaging. Structural lung diseases alter alveolar microstructure, which often causes a dark-field signal decrease. The imaging method provides benefits for diagnosis of such diseases in small-animal models, and was successfully used on porcine and human lungs in a fringe-scanning setup. Micro- and macroscopic changes occur in the lung during breathing, but their individual effects on the dark-field signal are unknown. However, this information is important for quantitative medical evaluation of dark-field thorax radiographs. To estimate the effect of these changes on the dark-field signal during a clinical examination, we acquired in vivo dark-field chest radiographs of two pigs at three ventilation pressures. Pigs were used due to the high degree of similarity between porcine and human lungs. To analyze lung expansion separately, we acquired CT scans of both pigs at comparable posture and ventilation pressures. Segmentation, masking, and forward-projection of the CT datasets yielded maps of lung thickness and logarithmic lung attenuation signal in registration with the dark-field radiographs. Upon correlating this data, we discovered approximately linear relationships between the logarithmic dark-field signal and both projected quantities for all scans. Increasing ventilation pressure strongly decreased dark-field extinction coefficients, whereas the ratio of lung dark-field and attenuation signal changed only slightly. Furthermore, we investigated ratios of dark-field and attenuation noise levels at realistic signal levels via calculations and phantom measurements. Dark-field contrast-to-noise ratio (CNR) per lung height was 5 to 10% of the same quantity in attenuation. We conclude that better CNR performance in the dark-field modality is typically due to greater anatomical noise in the conventional radiograph. Given the high physiological similarity of human and porcine lungs, the presented thickness-normalized, ventilation-dependent values allow estimation of dark-field activity of human lungs of variable size and inspiration, which facilitates the design of suitable clinical imaging setups. [ABSTRACT FROM AUTHOR]

Background: Computed tomography pulmonary angiography (CTPA) is the standard imaging modality for detection or rule out of pulmonary embolism (PE); however, radiation exposure is a serious concern. With iterative reconstruction algorithms a distinct dose reduction could be achievable.Purpose: To evaluate a next generation iterative reconstruction algorithm for detection or rule-out of PE in simulated low-dose CTPA.Material and Methods: Low-dose CT datasets with 50%, 25%, and 12.5% of the original tube current were simulated based on CTPA examinations of 92 patients with suspected PE. All datasets were reconstructed with two reconstruction algorithms: standard filtered back-projection (FBP) and iterative model reconstruction (IMR). In total, 736 CTPA datasets were evaluated by three blinded radiologists regarding image quality, diagnostic confidence, and detectability of PE. Furthermore, contrast-to-noise ratio (CNR) was calculated.Results: Images reconstructed with IMR showed better detectability of PE than images reconstructed with FBP, especially at lower dose levels. With IMR, sensitivity was over 95% for central and segmental PE down to a dose level of 25%. Significantly higher subjective image quality was shown at lower dose levels (25% and 12.5%) for IMR images whereas it was higher for FBP images at higher dose levels. FBP was rated as showing less artificial image appearance. CNR was significantly higher with IMR at all dose levels.Conclusion: By using IMR, a dose reduction of up to 50% while maintaining satisfactory image quality seems feasible in standard clinical situations, resulting in a mean effective dose of 1.38 mSv for CTPA. [ABSTRACT FROM AUTHOR]

In the published Figure 4, instead of data points of 92 patients, data points of additional patients are included. Even by including more patients, the recorded mean value is below the reference value, therefore we fulfill the legal requirements regarding the local diagnostic reference level (DRL). In our work, we evaluated the effective dose values for first clinical dark-field chest radiography, both for examinations of the reference person and a certain patient collective consisting of 92 patients. [Extracted from the article]

Objective: Evaluation of a new iterative reconstruction algorithm (IMR) for detection/rule-out of pulmonary embolism (PE) in ultra-low dose computed tomography pulmonary angiography (CTPA). Methods: Lower dose CT data sets were simulated based on CTPA examinations of 16 patients with pulmonary embolism (PE) with dose levels (DL) of 50%, 25%, 12.5%, 6.3% or 3.1% of the original tube current setting. Original CT data sets and simulated low-dose data sets were reconstructed with three reconstruction algorithms: the standard reconstruction algorithm “filtered back projection” (FBP), the first generation iterative reconstruction algorithm iDose and the next generation iterative reconstruction algorithm “Iterative Model Reconstruction” (IMR). In total, 288 CTPA data sets (16 patients, 6 tube current levels, 3 different algorithms) were evaluated by two blinded radiologists regarding image quality, diagnostic confidence, detectability of PE and contrast-to-noise ratio (CNR). Results: iDose and IMR showed better detectability of PE than FBP. With IMR, sensitivity for detection of PE was 100% down to a dose level of 12.5%. iDose and IMR showed superiority to FBP regarding all characteristics of subjective (diagnostic confidence in detection of PE, image quality, image noise, artefacts) and objective image quality. The minimum DL providing acceptable diagnostic performance was 12.5% (= 0.45 mSv) for IMR, 25% (= 0.89 mSv) for iDose and 100% (= 3.57 mSv) for FBP. CNR was significantly (p < 0.001) improved by IMR compared to FBP and iDose at all dose levels. Conclusion: By using IMR for detection of PE, dose reduction for CTPA of up to 75% is possible while maintaining full diagnostic confidence. This would result in a mean effective dose of approximately 0.9 mSv for CTPA. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this work is to propose a cost function with regularization to iteratively reconstruct attenuation, phase, and scatter images simultaneously from differential phase contrast (DPC) acquisitions, without the need of phase retrieval, and examine its properties. Furthermore this reconstruction method is applied to an acquisition pattern that is suitable for a DPC tomographic system with continuously rotating gantry (sliding window acquisition), overcoming the severe smearing in noniterative reconstruction. Methods:We derive a penalized maximum likelihood reconstruction algorithm to directly reconstruct attenuation, phase, and scatter image from the measured detector values of a DPC acquisition. The proposed penalty comprises, for each of the three images, an independent smoothing prior. Image quality of the proposed reconstruction is compared to images generated with FBP and iterative reconstruction after phase retrieval. Furthermore, the influence between the priors is analyzed. Finally, the proposed reconstruction algorithm is applied to experimental sliding window data acquired at a synchrotron and results are compared to reconstructions based on phase retrieval. Results: The results show that the proposed algorithm significantly increases image quality in comparison to reconstructions based on phase retrieval. No significant mutual influence between the proposed independent priors could be observed. Further it could be illustrated that the iterative reconstruction of a sliding window acquisition results in images with substantially reduced smearing artifacts. Conclusions: Although the proposed cost function is inherently nonconvex, it can be used to reconstruct images with less aliasing artifacts and less streak artifacts than reconstruction methods based on phase retrieval. Furthermore, the proposed method can be used to reconstruct images of sliding window acquisitions with negligible smearing artifacts. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this work is to investigate the feasibility of grating-based, differential phase-contrast, full-field digital mammography (FFDM) in terms of the requirements for field-of-view (FOV), mechanical stability, and scan time. Methods: A rigid, actuator-free Talbot interferometric unit was designed and integrated into a state-of-the-art x-ray slit-scanning mammography system, namely, the Philips MicroDose L30 FFDM system. A dedicated phase-acquisition and phase retrieval method was developed and implemented that exploits the redundancy of the data acquisition inherent to the slit-scanning approach to image generation of the system. No modifications to the scan arm motion control were implemented. Results: The authors achieve a FOV of 160 × 196 mm consisting of two disjoint areas measuring 77 × 196 mm with a gap of 6 mm between them. Typical scanning times vary between 10 and 15 s and dose levels are lower than typical FFDM doses for conventional scans with identical acquisition parameters due to the presence of the source-grating G0. Only minor to moderate artifacts are observed in the three reconstructed images, indicating that mechanical vibrations induced by other system components do not prevent the use of the platform for phase contrast imaging. Conclusions: To the best of our knowledge, this is the first attempt to integrate x-ray gratings hardware into a clinical mammography unit. The results demonstrate that a scanning differential phase contrast FFDM system that meets the requirements of FOV, stability, scan time, and dose can be build. [ABSTRACT FROM AUTHOR]

Grating-based differential phase-contrast imaging has proven to be feasible with conventional X-ray sources. The polychromatic spectrum generally limits the performance of the interferometer but benefit can be gained with an energy-sensitive detector. In the presented work, we employ the energy-discrimination capability to correct for phase-wrapping artefacts. We propose to use the phase shifts, which are measured in distinct energy bins, to estimate the optimal phase shift in the sense of maximum likelihood. We demonstrate that our method is able to correct for phase-wrapping artefacts, to improve the contrast-to-noise ratio and to reduce beam hardening due to the modelled energy dependency. The method is evaluated on experimental data which are measured with a laboratory Talbot–Lau interferometer equipped with a conventional polychromatic X-ray source and an energy-sensitive photon-counting pixel detector. Our work shows, that spectral imaging is an important step to move differential phase-contrast imaging closer to pre-clinical and clinical applications, where phase wrapping is particularly problematic. [ABSTRACT FROM PUBLISHER]

Education research has shown that there is often a disconnect between what instructors teach and what students actually comprehend. Much of this disconnect stems from students' previous conceptions of the subject that often remain steadfast despite instruction. The field of meteorology is particularly susceptible to misconceptions as a result of the years of personal experience students have with weather before instruction. Consequently, it is often challenging for students to accurately integrate course material with their observations and personal explanations. A longitudinal assessment exam of the meteorology program at the U.S. Air Force Academy revealed that misconceptions of fundamental, introductory content can propagate through years of instruction, potentially impeding deeper understanding of advanced topics and hindering attainment of professional certifications. Thus, it is clear that such misconceptions must be identified and corrected early. This manuscript describes the development of the Fundamentals in Meteorology Inventory (FMI), a multiple-choice assessment exam designed to identify the common misconceptions of fundamental topics covered in introductory meteorology courses. In developing the FMI, care was taken to avoid complex vocabulary and to include plausible distractors identified by meteorology faculty members. Question topics include clouds and precipitation, wind, fronts and air masses, temperature, stability, severe weather, and climate. Applications of the exam for the meteorology community are discussed, including identifying common meteorology misconceptions, assessing student understanding, measuring teaching effectiveness, and diagnosing areas for improvement in introductory meteorology courses. Future work to be completed to ensure the efficacy of the FMI will also be acknowledged. [ABSTRACT FROM AUTHOR]

Purpose: Evaluation of a new software tool for generation of simulated low-dose computed tomography (CT) images from an original higher dose scan. Materials and Methods: Original CT scan data (100 mAs, 80 mAs, 60 mAs, 40 mAs, 20 mAs, 10 mAs; 100 kV) of a swine were acquired (approved by the regional governmental commission for animal protection). Simulations of CT acquisition with a lower dose (simulated 10–80 mAs) were calculated using a low-dose simulation algorithm. The simulations were compared to the originals of the same dose level with regard to density values and image noise. Four radiologists assessed the realistic visual appearance of the simulated images. Results: Image characteristics of simulated low dose scans were similar to the originals. Mean overall discrepancy of image noise and CT values was −1.2% (range −9% to 3.2%) and −0.2% (range −8.2% to 3.2%), respectively, p>0.05. Confidence intervals of discrepancies ranged between 0.9–10.2 HU (noise) and 1.9–13.4 HU (CT values), without significant differences (p>0.05). Subjective observer evaluation of image appearance showed no visually detectable difference. Conclusion: Simulated low dose images showed excellent agreement with the originals concerning image noise, CT density values, and subjective assessment of the visual appearance of the simulated images. An authentic low-dose simulation opens up opportunity with regard to staff education, protocol optimization and introduction of new techniques. [ABSTRACT FROM AUTHOR]

Photon-counting detector technology has enabled the first experimental investigations of energy-resolved computed tomography (CT) imaging and the potential use for K-edge imaging. However, limitations in regards to detecter technology have been imposing a limit to effective count rates. As a consequence, this has resulted in high noise levels in the obtained images given scan time limitations in CT imaging applications. It has been well recognized in the area of low-dose imaging with conventional CT that iterative image reconstruction provides a superior signal to noise ratio compared to traditional filtered backprojection techniques. Furthermore, iterative reconstruction methods also allow for incorporation of a roughness penalty function in order to make a trade-off between noise and spatial resolution in the reconstructed images. In this work, we investigate statistically-principled iterative image reconstruction from material-decomposed sinograms in spectral CT. The proposed reconstruction algorithm seeks to minimize a penalized likelihood-based cost functional, where the parameters of the likelihood function are estimated by computing the Fisher information matrix associated with the material decomposition step. The performance of the proposed reconstruction method is quantitatively investigated by use of computer-simulated and experimental phantom data. The potential for improved K-edge imaging is also demonstrated in an animal experiment. [ABSTRACT FROM PUBLISHER]

Purpose: A CT scanner measures the energy that is deposited in each channel of a detector array by x rays that have been partially absorbed on their way through the object. The measurement process is complex and quantitative measurements are always and inevitably associated with errors, so CT data must be preprocessed prior to reconstruction. In recent years, the authors have formulated CT sinogram preprocessing as a statistical restoration problem in which the goal is to obtain the best estimate of the line integrals needed for reconstruction from the set of noisy, degraded measurements. The authors have explored both penalized Poisson likelihood (PL) and penalized weighted least-squares (PWLS) objective functions. At low doses, the authors found that the PL approach outperforms PWLS in terms of resolution-noise tradeoffs, but at standard doses they perform similarly. The PWLS objective function, being quadratic, is more amenable to computational acceleration than the PL objective. In this work, the authors develop and compare two different methods for implementing PWLS sinogram restoration with the hope of improving computational performance relative to PL in the standard-dose regime. Sinogram restoration is still significant in the standard-dose regime since it can still outperform standard approaches and it allows for correction of effects that are not usually modeled in standard CT preprocessing. Methods: The authors have explored and compared two implementation strategies for PWLS sinogram restoration: (1) A direct matrix-inversion strategy based on the closed-form solution to the PWLS optimization problem and (2) an iterative approach based on the conjugate-gradient algorithm. Obtaining optimal performance from each strategy required modifying the naive off-the-shelf implementations of the algorithms to exploit the particular symmetry and sparseness of the sinogram-restoration problem. For the closed-form approach, the authors subdivided the large matrix inversion into smaller coupled problems and exploited sparseness to minimize matrix operations. For the conjugate-gradient approach, the authors exploited sparseness and preconditioned the problem to speed up convergence. Results: All methods produced qualitatively and quantitatively similar images as measured by resolution-variance tradeoffs and difference images. Despite the acceleration strategies, the direct matrix-inversion approach was found to be uncompetitive with iterative approaches, with a computational burden higher by an order of magnitude or more. The iterative conjugate-gradient approach, however, does appear promising, with computation times half that of the authors' previous penalized-likelihood implementation. Conclusions: Iterative conjugate-gradient based PWLS sinogram restoration with careful matrix optimizations has computational advantages over direct matrix PWLS inversion and over penalized-likelihood sinogram restoration and can be considered a good alternative in standard-dose regimes. [ABSTRACT FROM AUTHOR]

The ITRS roadmap and Moore’s law are driving us to print ever smaller features and ever tighter pitches. For these ultrasmall features and pitches, resist effects are expected to play a dominant role in limiting the overall lithographic process capability. To study the impact of resist parameters such as acid diffusion and quencher level on the lithographic performance, we have designed and formulated a matrix of 14 extreme ultraviolet (EUV) resists. In this article, we discuss results that we have obtained from EUV exposures of those resists on the 0.3 numerical aperture EUV Micro Exposure Tool at the Advanced Light Source at Lawrence Berkeley National Laboratories. In addition to exposure latitude and line edge roughness, acid diffusion lengths were characterized using a modification of the extended Nijboer–Zernike theory for each photoresist. A simple theory for the drop in resist contrast as function of the diffusion length is tested and leads to a verified correlation between exposure latitude and diffusion length. This theory gives guidelines to predict what acid diffusion lengths should be used for a certain lithography node. Line edge roughness analysis showed that shot noise statistics are present, and also points out that acid diffusion effects come into play. From the experimentally observed tendencies in this unique matrix of EUV photoresists, fundamental understanding was gained about prominent resist effects that will determine the lithographic performance of resist processes in future lithography nodes. [ABSTRACT FROM AUTHOR]