scholarly journals Quantitative imaging and automated fuel pin identification for passive gamma emission tomography

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ming Fang ◽  
Yoann Altmann ◽  
Daniele Della Latta ◽  
Massimiliano Salvatori ◽  
Angela Di Fulvio
Keyword(s):  
Inverse Problem ◽  
Image Reconstruction ◽  
Image Resolution ◽  
Emission Tomography ◽  
Nuclear Safeguards ◽  
Activity Levels ◽  
Spent Fuel ◽  
Gamma Emission ◽  
Cross Sectional ◽  
Fuel Rods

AbstractCompliance of member States to the Treaty on the Non-Proliferation of Nuclear Weapons is monitored through nuclear safeguards. The Passive Gamma Emission Tomography (PGET) system is a novel instrument developed within the framework of the International Atomic Energy Agency (IAEA) project JNT 1510, which included the European Commission, Finland, Hungary and Sweden. The PGET is used for the verification of spent nuclear fuel stored in water pools. Advanced image reconstruction techniques are crucial for obtaining high-quality cross-sectional images of the spent-fuel bundle to allow inspectors of the IAEA to monitor nuclear material and promptly identify its diversion. In this work, we have developed a software suite to accurately reconstruct the spent-fuel cross sectional image, automatically identify present fuel rods, and estimate their activity. Unique image reconstruction challenges are posed by the measurement of spent fuel, due to its high activity and the self-attenuation. While the former is mitigated by detector physical collimation, we implemented a linear forward model to model the detector responses to the fuel rods inside the PGET, to account for the latter. The image reconstruction is performed by solving a regularized linear inverse problem using the fast-iterative shrinkage-thresholding algorithm. We have also implemented the traditional filtered back projection (FBP) method based on the inverse Radon transform for comparison and applied both methods to reconstruct images of simulated mockup fuel assemblies. Higher image resolution and fewer reconstruction artifacts were obtained with the inverse-problem approach, with the mean-square-error reduced by 50%, and the structural-similarity improved by 200%. We then used a convolutional neural network (CNN) to automatically identify the bundle type and extract the pin locations from the images; the estimated activity levels finally being compared with the ground truth. The proposed computational methods accurately estimated the activity levels of the present pins, with an associated uncertainty of approximately 5%.

scholarly journals Idea of an experimental technique for quantitative passive gamma emission tomography on irradiated nuclear fuel assemblies

2021 ◽  
Vol 7 ◽  
Author(s):  
Peter Jansson
Keyword(s):  
Image Reconstruction ◽  
Nuclear Fuel ◽  
Experimental Technique ◽  
Quantitative Information ◽  
Emission Tomography ◽  
Gamma Emission ◽  
Fuel Rods ◽  
Activity Distribution ◽  
Fuel Assemblies ◽  
Irradiated Nuclear Fuel

An idea is presented in which passive gamma emission tomography of irradiated nuclear fuel is developed to enable quantitative information of the spatial activity distribution of selected isotopes within the fuel rods of the assembly. The idea is based on using well-known calibration sources mounted in the measurement device during measurement. The image reconstruction would include the sources, thereby enable quantification of the activity distribution. Should the idea be proven viable, the outcome would be valuable to the global community dealing with characterisation of nuclear fuel in terms of safety, security, safeguards and fuel development.

scholarly journals Synergistic motion compensation strategies for positron emission tomography when acquired simultaneously with magnetic resonance imaging

2021 ◽  
Vol 379 (2204) ◽  
pp. 20200207
Author(s):  
Irene Polycarpou ◽  
Georgios Soultanidis ◽  
Charalampos Tsoumpas
Keyword(s):  
Magnetic Resonance Imaging ◽  
Positron Emission Tomography ◽  
Magnetic Resonance ◽  
Image Reconstruction ◽  
Motion Correction ◽  
Kinetic Modelling ◽  
Image Resolution ◽  
Emission Tomography ◽  
Resonance Imaging ◽  
Positron Emission

Subject motion in positron emission tomography (PET) is a key factor that degrades image resolution and quality, limiting its potential capabilities. Correcting for it is complicated due to the lack of sufficient measured PET data from each position. This poses a significant barrier in calculating the amount of motion occurring during a scan. Motion correction can be implemented at different stages of data processing either during or after image reconstruction, and once applied accurately can substantially improve image quality and information accuracy. With the development of integrated PET-MRI (magnetic resonance imaging) scanners, internal organ motion can be measured concurrently with both PET and MRI. In this review paper, we explore the synergistic use of PET and MRI data to correct for any motion that affects the PET images. Different types of motion that can occur during PET-MRI acquisitions are presented and the associated motion detection, estimation and correction methods are reviewed. Finally, some highlights from recent literature in selected human and animal imaging applications are presented and the importance of motion correction for accurate kinetic modelling in dynamic PET-MRI is emphasized. This article is part of the theme issue ‘Synergistic tomographic image reconstruction: part 2’.

scholarly journals DEVELOPMENT OF A MODELING APPROACH TO ESTIMATE RADIATION FROM A SPENT FUEL ROD QUIVER

2021 ◽  
Vol 247 ◽  
pp. 16006
Author(s):  
Zs. Elter ◽  
V. Mishra ◽  
S. Grape ◽  
E. Branger ◽  
P. Jansson ◽  
...  
Keyword(s):  
Gamma Radiation ◽  
Spent Nuclear Fuel ◽  
Radiation Transport ◽  
Neutron Radiation ◽  
Nuclear Safeguards ◽  
Monte Carlo Code ◽  
Spent Fuel ◽  
Fuel Rods ◽  
History Of ◽  
New Type

Before encapsulation of spent nuclear fuel in a geological repository, the fuels need to be verified for safeguards purposes. This requirement applies to all spent fuel assemblies, including those with properties or designs that are especially challenging to verify. One such example are quivers, a new type of containers used to hold damaged spent fuel rods. After placing damaged rods inside the quivers, they are sealed with a thick lid and the water is removed. The lid is thick enough to significantly reduce the amount of the gamma radiation penetrating through it, which can make safeguards verification from the top using gamma techniques difficult. Considering that the number of quivers at storage facilities is foreseen to increase in near future, studying the feasibility of verification is timely. In this paper we make a feasibility study related to safeguards verification of quivers, aimed at investigating the gamma and neutron radiation field around a quiver designed by Westinghouse AB and filled with PWR fuel rods irradiated at the Swedish Ringhals site. A simplified geometry of the quiver and the detailed operational history of each rod are provided by Westinghouse and the reactor operator, respectively. The nuclide inventory of the rods placed in the quiver and the emission source terms are calculated with ORIGEN-ARP. The radiation transport is modeled with the Serpent2 Monte Carlo code. The first objective is to assess the capability of the spent fuel attribute tester (SFAT) to verify the content for nuclear safeguards purposes. The results show that the thick quiver lid attenuates the gamma radiation, thereby making gamma radiation based verification from above the quiver difficult.

scholarly journals FORK EXPERIMENTS IN THE HOT CELL USING SPENT FUEL RODS FOR INTERNATIONAL NUCLEAR SAFEGUARDS

2021 ◽  
Author(s):  
Jianwei Hu ◽  
Robert Mcelroy Jr ◽  
Andrew Nicholson ◽  
Stephen Croft
Keyword(s):  
Nuclear Safeguards ◽  
Spent Fuel ◽  
Fuel Rods

PEMBELAJARAN SIMULASI PENCITRAAN CT DENGAN MENGGUNAKAN PRINSIP REKONSTRUKSI CITRA DALAM SOFTWARE MATLAB

2015 ◽  
Vol 8 (3) ◽  
pp. 161
Author(s):  
Samuel Gideon
Keyword(s):  
Image Reconstruction ◽  
Ct Imaging ◽  
The Body ◽  
Reconstruction Technique ◽  
Imaging Features ◽  
Back Projection ◽  
Cross Sectional ◽  
Low Contrast ◽  
Image Reconstruction Technique ◽  
Imaging Algorithms

This research was conducted as a learning alternatives for study of CT (computed tomograpghy) imaging using image reconstruction technique which are inversion matrix, back projection and filtered back projection. CT imaging can produce images of objects that do not overlap. Objects more easily distinguishable although given the relatively low contrast. The image is generated on CT imaging is the result of reconstruction of the original object. Matlab allows us to create and write imaging algorithms easily, easy to undersand and gives applied and exciting other imaging features. In this study, an example cross-sectional image recon-struction performed on the body of prostate tumors using. With these methods, medical prac-titioner (such as oncology clinician, radiographer and medical physicist) allows to simulate the reconstruction of CT images which almost resembles the actual CT visualization techniques.Keywords : computed tomography (CT), image reconstruction, Matlab

Image Reconstruction with the Fourier Coefficients for Magnetic Induction Tomography

2020 ◽  
Vol 16 (2) ◽  
pp. 156-163
Author(s):  
Jingwen Wang ◽  
Xu Wang ◽  
Dan Yang ◽  
Kaiyang Wang
Keyword(s):  
Inverse Problem ◽  
Image Reconstruction ◽  
Magnetic Induction ◽  
Fourier Coefficients ◽  
Signal Reconstruction ◽  
Reconstruction Algorithm ◽  
Reconstruction Method ◽  
Measurement Equation ◽  
Image Reconstruction Method ◽  
Magnetic Induction Tomography

Background: Image reconstruction of magnetic induction tomography (MIT) is a typical ill-posed inverse problem, which means that the measurements are always far from enough. Thus, MIT image reconstruction results using conventional algorithms such as linear back projection and Landweber often suffer from limitations such as low resolution and blurred edges. Methods: In this paper, based on the recent finite rate of innovation (FRI) framework, a novel image reconstruction method with MIT system is presented. Results: This is achieved through modeling and sampling the MIT signals in FRI framework, resulting in a few new measurements, namely, fourier coefficients. Because each new measurement contains all the pixel position and conductivity information of the dense phase medium, the illposed inverse problem can be improved, by rebuilding the MIT measurement equation with the measurement voltage and the new measurements. Finally, a sparsity-based signal reconstruction algorithm is presented to reconstruct the original MIT image signal, by solving this new measurement equation. Conclusion: Experiments show that the proposed method has better indicators such as image error and correlation coefficient. Therefore, it is a kind of MIT image reconstruction method with high accuracy.

scholarly journals Exploring activity levels in physical education lessons in the UK: a cross-sectional examination of activity types and fitness levels

2021 ◽  
Vol 7 (1) ◽  
pp. e000924
Author(s):  
Nick Beale ◽  
Emma Eldridge ◽  
Anne Delextrat ◽  
Patrick Esser ◽  
Oliver Bushnell ◽  
...  
Keyword(s):  
Physical Activity ◽  
Physical Education ◽  
Multilevel Models ◽  
Activity Levels ◽  
Cross Sectional ◽  
Registration Number ◽  
Global Norms ◽  
Cross Sectional Design ◽  
The Uk ◽  
Fitness Levels

ObjectivesTo establish pupil fitness levels, and the relationship to global norms and physical education (PE) enjoyment. To measure and describe physical activity (PA) levels during secondary school PE lessons, in the context of recommended levels, and how levels vary with activity and lesson type.MethodsA cross-sectional design; 10 697 pupils aged 12.5 (SD 0.30) years; pupils who completed a multistage fitness test and wore accelerometers to measure PA during PE lessons. Multilevel models estimated fitness and PE activity levels, accounting for school and class-level clustering.ResultsCardiorespiratory fitness was higher in boys than girls (ß=−0.48; 95% CI −0.56 to −0.39, p<0.001), within absolute terms 51% of boys and 54% of girls above the 50th percentile of global norms. On average, pupils spent 23.8% of PE lessons in moderate-to-vigorous PA (MVPA), and 7.1% in vigorous PA (VPA). Fitness-focused lessons recorded most VPA in co-educational (ß=1.09; 95% CI 0.43 to 1.74) and boys-only lessons (ß=0.32; 95% CI −0.21 to 0.85). In girls-only lessons, track athletics recorded most VPA (ß=0.13; 95% CI −0.50 to 0.75) and net/wall/racket games (ß=0.97; 95% CI 0.12 to 1.82) the most MVPA. For all lesson types, field athletics was least active (ß=−0.85; 95% CI −1.33 to −0.36). There was a relationship of enjoyment of PE to fitness (ß=1.03; 95% CI 0.83 to 1.23), and this relationship did not vary with sex (ß=−0.14 to 0.23; 95% CI −0.16 to 0.60).ConclusionsPE lessons were inactive compared with current guidelines. We propose that if we are to continue to develop a range of sporting skills in schools at the same time as increasing levels of fitness and PA, there is a need to introduce additional sessions of PE activity focused on increasing physical activity.Trial registration numberNCT03286725.

Inverse Association Between Health Literacy and Obesity Among Children in Greece: A School-Based, Cross-Sectional Epidemiological Study

2021 ◽  
pp. 109019812098294
Author(s):  
Aikaterini Kanellopoulou ◽  
Venetia Notara ◽  
George Antonogeorgos ◽  
Maria Chrissini ◽  
Andrea Paola Rojas-Gil ◽  
...  
Keyword(s):  
Health Literacy ◽  
Weight Status ◽  
Dietary Habits ◽  
Population Based ◽  
Activity Levels ◽  
Inverse Association ◽  
Linear Regression Models ◽  
Cross Sectional ◽  
Body Weight Status ◽  
High Level

Children’s health literacy is a crucial pillar of health. This study is aimed to examine the association between health literacy and weight status among Greek schoolchildren aged 10 to 12 years old. A population-based, cross-sectional observational study enrolling 1,728 students (795 boys), aged 10 to 12 years old, was conducted during school years 2014–2016. A health literacy index (range 0-100) was created through an item response theory hybrid model, by combining a variety of beliefs and perceptions of children about health. The mean health literacy score was 70.4 (±18.7). The majority of children (63.8%) had a “high” level (i.e., >67/100) of health literacy, 30.5% had a “medium” level (i.e., 34–66/100) of health literacy, while a small proportion of children (5.7%) had a “low” level (i.e., <33/100). Girls exhibited a higher level of health literacy than boys (71.7 ± 18.3 vs. 68.8 ± 19.1, p < .01). Regarding body weight status, 21.7% of children was overweight and 5.0% was obese. Linear regression models showed that the health literacy score was inversely associated with children’s body mass index (regression coefficient [95% CI]: −0.010 [−0.018, −0.001]), after adjusting for dietary habits, physical activity levels, and other potential confounders. Health literacy seems to be a dominant characteristic of children’s weight status; therefore, school planning, as well as public health policy actions should emphasize on the ability of children’s capacity to obtain, process, and understand basic health information.

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