Small Number Of Projections Research Articles

On the association between noise exposure and annoyance for road and rail traffic noise

There have been a number of small projects in the Oslo area attempting to determine how annoyance relates to noise exposure. There are several possible ways to measure annoyance, some of them are quantitative and some are qualitative. Noise exposure can be measured or calculated with acceptable accuracy in a given position. But it is still uncertain how the evaluation should be performed, as both outdoor and indoor levels should be taken into account. The subjective evaluation of noise immission for an exposed person also depends on other factors beside the physical noise. We will, however, claim that noise is a reasonable proxy for the total environmental exposure for a resident. It would also seem that a subjective evaluation requires grounding in objective facts in order to be useful. There are many possible reasons for a large variation between persons in the perceived annoyance due to the same noise exposure. We suggest a simple model with a wide range of uncertainty as a possible predictor of perceived annoyance within a given neighbourhood.

Alternative education in Russian megacities: a chance for a different school

Introduction. The relevance of the study is determined by the search for innovative ways to develop school education. The study of the history and current state of alternative education in the largest Russian cities plays a significant role in this search. Systematisation of private educational projects will help families to better orientate themselves in alternative education and avoid its destructive models. Materials and Methods. An analysis of scientific literature was conducted, and information from the websites of 665 private educational projects was collected and analyzed, including 322 from Moscow, 183 from Saint Petersburg, 57 from Yekaterinburg, and 51 each from Novosibirsk and Kazan. In-depth interviews with their leaders were conducted, focus groups with experts were held, and an analysis of federal state statistics was made. Research Results. The coverage of children by humanistic alternative education practices in Russia is less than 1%. However, over 10 years, there has been a noticeable growth in the number of educational projects outside the system. An analysis of Project websites showed that only 8% of them consider themselves to be alternative education. 43% of Projects have a license for primary educational activities. Most often, projects implement primary general education programs. 23% of projects claim to implement proprietary programs. A small number of projects are based on specific didactic systems, approaches and practices. The typology of Alternative Education Projects is made taking into account the role of the child in the formation and implementation of educational requests. The study identified three spaces of alternative education: projects supporting family education, projects with established didactic systems (program schools), and A-schools. There are destructive practices in alternative education. Conclusion. Alternative education in the large cities of Russia is diverse and includes both humanistic and other pedagogical practices, as well as a degree of uncertainty. The pedagogical practices of alternative education are difficult to typologize. This living organism continuously transforms, sensitively responding to the external environment.

Artifact suppression for breast specimen imaging in micro CBCT using deep learning

BackgroundCone-beam computed tomography (CBCT) has been introduced for breast-specimen imaging to identify a free resection margin of abnormal tissues in breast conservation. As well-known, typical micro CT consumes long acquisition and computation times. One simple solution to reduce the acquisition scan time is to decrease of the number of projections, but this method generates streak artifacts on breast specimen images. Furthermore, the presence of a metallic-needle marker on a breast specimen causes metal artifacts that are prominently visible in the images. In this work, we propose a deep learning-based approach for suppressing both streak and metal artifacts in CBCT.MethodsIn this work, sinogram datasets acquired from CBCT and a small number of projections containing metal objects were used. The sinogram was first modified by removing metal objects and up sampling in the angular direction. Then, the modified sinogram was initialized by linear interpolation and synthesized by a modified neural network model based on a U-Net structure. To obtain the reconstructed images, the synthesized sinogram was reconstructed using the traditional filtered backprojection (FBP) approach. The remaining residual artifacts on the images were further handled by another neural network model, ResU-Net. The corresponding denoised image was combined with the extracted metal objects in the same data positions to produce the final results.ResultsThe image quality of the reconstructed images from the proposed method was improved better than the images from the conventional FBP, iterative reconstruction (IR), sinogram with linear interpolation, denoise with ResU-Net, sinogram with U-Net. The proposed method yielded 3.6 times higher contrast-to-noise ratio, 1.3 times higher peak signal-to-noise ratio, and 1.4 times higher structural similarity index (SSIM) than the traditional technique. Soft tissues around the marker on the images showed good improvement, and the mainly severe artifacts on the images were significantly reduced and regulated by the proposed. method.ConclusionsOur proposed method performs well reducing streak and metal artifacts in the CBCT reconstructed images, thus improving the overall breast specimen images. This would be beneficial for clinical use.

Source-detector trajectory optimization for CBCT metal artifact reduction based on PICCS reconstruction

Precise instrument placement plays a critical role in all interventional procedures, especially percutaneous procedures such as needle biopsies, to achieve successful tumor targeting and increased diagnostic accuracy. C-arm cone beam computed tomography (CBCT) has the potential to precisely visualize the anatomy in direct vicinity of the needle and evaluate the adequacy of needle placement during the intervention, allowing for instantaneous adjustment in case of misplacement. However, even with the most advanced C-arm CBCT devices, it can be difficult to identify the exact needle position on CBCT images due to the strong metal artifacts around the needle. In this study, we proposed a framework for customized trajectory design in CBCT imaging based on Prior Image Constrained Compressed Sensing (PICCS) reconstruction with the goal of reducing metal artifacts in needle-based procedures. We proposed to optimize out-of-plane rotations in three-dimensional (3D) space and minimize projection views while reducing metal artifacts at specific volume of interests (VOIs). An anthropomorphic thorax phantom with a needle inserted inside and two tumor models as the imaging targets were used to validate the proposed approach. The performance of the proposed approach was also evaluated for CBCT imaging under kinematic constraints by simulating some collision areas on the geometry of the C-arm. We compared the result of optimized 3D trajectories using the PICCS algorithm and 20 projections with the result of a circular trajectory with sparse view using PICCS and Feldkamp, Davis, and Kress (FDK), both using 20 projections, and the circular FDK method with 313 projections. For imaging targets 1 and 2, the highest values of structural similarity index measure (SSIM) and universal quality index (UQI) between the reconstructed image from the optimized trajectories and the initial CBCT image at the VOI was calculated 0.7521, 0.7308 and 0.7308, 0.7248 respectively. These results significantly outperformed the FDK method (with 20 and 313 projections) and the PICCS method (20 projections) both using the circular trajectory. Our results showed that the proposed optimized trajectories not only significantly reduce metal artifacts but also suggest a dose reduction for needle-based CBCT interventions, considering the small number of projections used. Furthermore, our results showed that the optimized trajectories are compatible with spatially constrained situations and enable CBCT imaging under kinematic constraints when the standard circular trajectory is not feasible.

Wind Farm Impacts on Birds and Bats: Planning, Baseline Studies, Mitigation and Monitoring Overview

Onshore wind energy has undergone enormous development over the last decade globally. Looking only at the European Union (EU), 11 GW were installed in 2021 alone. But the predictions are even higher for the period 2022–2026. If we focus our attention only on the group of 27 EU countries, the average annual installed onshore wind capacity is expected to be 18 GW. In Kazakhstan, wind energy has been installed so far in a small number of projects, although it has enormous capacity for expansion. The government has established a wind energy development programme until 2030, which foresees the installation of 2 GW (around 400 wind turbines). But this technology is not free of impacts on biodiversity, and especially on birds and bats. The main effects on these groups are: direct habitat loss due to vegetation removal; habitat degradation due to light and noise impacts; habitat fragmentation; loss of connectivity and the barrier effect on local and regional wildlife migrations; death by direct collision (or barotrauma in the case of bats); or increased predation rates by opportunistic predators. Therefore, only through planning, good baseline studies, use of the best-known mitigation measures, and adequate monitoring of the actual effects caused in the operation phase will it be possible to mitigate their effects. Our presentation gives an overview of the main effects on biodiversity that have been detected in Europe for wind energy, finally reviewing the main mitigation and monitoring measures employed, so that during the development of this technology in Kazakhstan, the best existing knowledge can be used as a starting point.

The Beginnings of 1980s Soviet ‘Paper Architecture’ and the Circumstances of its Existence

History of Soviet ‘Paper Architeture’ of 1980s is mostly oral: its fragments are scattered in architecture magazines, critical articles and interviews. It seems that it has come from nowhere — this phenomenon has a very weak connection with what was going on in ‘built’ architecture. Nevertheless, Paper Architecture is a prominent part of Soviet culture of 1980s that is impossible to neglect. Conceptual architecture in the 20th century has certain regularity: to totalitarian myths of 1940s and once again as the part of the ‘Space Age’ aesthetics of 1960s. Paper Architecture wasn’t supported by ‘real’ architecture except from a very small number of projects; nevertheless it has answered the postmodernist challenge — to make architecture talk. Restoration of events chronicle may be the key to understanding the development of Paper Architecture: its duality between art and architecture, weak interest of its authors in ‘real’ building and disbanded nature of working groups can be explained by outer circumstances, not some program of the group. This article tries to connect this puzzle from recollections and events to describe the beginnings of this phenomenon.

Architettura e frammentismo, o lo stile tardo di Giuliano da Sangallo

Giuliano da Sangallo was an artist originally trained as a legnaiuolo and a sculptor, but it is especially as an architect that we remember him, particularly for his service to two generations of the Medici, from Lorenzo the Magnificent to Leo X. His late style is emblematic of the methodological questions developed by historiography around the concept of Altersstil. It was both the product of highly personal, even idiosyncratic, formal preferences and a trigger for new trends that emerged in the architecture of sixteenth-century Italy. Indeed, the erudite, seductive language displayed in the last years of his life would have a fundamental impact on subsequent generations of designers, despite the small number of projects actually completed. Different design strategies, all experimented with over the previous decades, converge in Giuliano da Sangallo’s late style, making his architectural work so distinctive and pregnant with consequences: the taste for variation in the use of architectural orders and their conceptual autonomy from the wall’s mass; the sculptural treatment of figural details, producing dense atmospheric effects; the conception of the building as a boxy, elementary volume covered with precious surfaces. In 1990, Manfredo Tafuri recognized the common ground of these different aspects in their fragmentary quality. He was commenting on Giuliano's very last projects for the completion of the church of San Lorenzo through a new, monumental facade, conceived between 1515 and 1516,a few months before Giuliano’s death and as a response to an initiative undertaken by the first Medici pope. This article will focus primarily on this group of projects, or better, of drawings, but will also analyse a significant addition, presented to the public in 2017, on the occasion of an exhibition at the Uffizi. In both their graphic modes and architectural contents, these sheets represent Sangallo’s artistic testament. Characterised by sumptuous forms – i.e., showing the free and secure ductus that one would expect from an artist in the autumn of his career – and density of references, in terms of tectonics, civic identity, and antiquarian knowledge, they constitute a final word on the possibilities of representation in architecture.

Development of visible light tomographic imaging system for field-reversed configuration collisional merging experiment.

A visible light tomographic imaging system has been developed for the collisional merging experiment of field-reversed configurations (FRCs) on the FRC Amplification via Translation-Collisional Merging device at Nihon University. Two FRCs formed by field-reversed theta-pinch translate at super-Alfvénic velocity and collide with each other. The translation and collision processes are completed in 20-30 µs, and a single FRC is reformed in ∼70 µs. To study these translation and collisional merging processes, the tomographic system, including fast response tomographic cameras and a reconstruction method assuming a Rigid-Rotor (RR) model, is developed. The developed tomographic cameras simply consist of 16 channels of multi-anode photomultipliers, a band-pass filter, a slit, and a cylindrical lens, which expands the viewing angle. Because the viewing angle is limited by the size of the viewports of the metal chamber, the iterative method assuming the RR model has been applied to reconstruct tomographic images from a small number of projections. The developed tomographic imaging system can estimate the behavior of FRCs. Four cameras are installed in the two cross sections near the collision point. The radial shift of each translated FRC can be calculated by this system. Details of the developed tomographic camera system and RR reconstruction method are reported.

Neural network regularization in the problem of few-view computed tomography

The computed tomography allows to reconstruct the inner morphological structure of an object without physical destructing. The accuracy of digital image reconstruction directly depends on the measurement conditions of tomographic projections, in particular, on the number of recorded projections. In medicine, to reduce the dose of the patient load there try to reduce the number of measured projections. However, in a few-view computed tomography, when we have a small number of projections, using standard reconstruction algorithms leads to the reconstructed images degradation. The main feature of our approach for few-view tomography is that algebraic reconstruction is being finalized by a neural network with keeping measured projection data because the additive result is in zero space of the forward projection operator. The final reconstruction presents the sum of the additive calculated with the neural network and the algebraic reconstruction. First is an element of zero space of the forward projection operator. The second is an element of orthogonal addition to the zero space. Last is the result of applying the algebraic reconstruction method to a few-angle sinogram. The dependency model between elements of zero space of forward projection operator and algebraic reconstruction is built with neural networks. It demonstrated that realization of the suggested approach allows achieving better reconstruction accuracy and better computation time than state-of-the-art approaches on test data from the Low Dose CT Challenge dataset without increasing reprojection error.

The clean development mechanism in Eastern Europe: an in-depth exploration

The Clean Development Mechanism (CDM), a partnership tool founded under the Kyoto Protocol, grants potential opportunities to help developing countries achieve sustainable development. The present research examines the CDM projects in Eastern Europe (Moldova, Serbia, Bosnia and Herzegovina, Montenegro, and Albania). Although there were far fewer projects in this region than, for instance, China or India, it has some specific features that make it worth studying. Major findings are that most CDM projects in Eastern Europe involved a changing combination of two or more sources of financing, and the distribution of projects in the region was uneven. Moreover, although there was a small number of projects overall, they were all cost-effective, long-term and large-scale. The findings of the research call for improvements to be made to the governance of the CDM, by strengthening the international and national regulation of projects and by aggregating the scales of decision-making and actions so that real multi-scalar transnational governance — from the global level down to the local level — is implemented in a coherent manner. It is also recommended to carry out ex-post project evaluations, following which readjustments could be made.

Research on competitiveness of Nghi Son Economic Zone in Thanh Hoa and some raised issues

Competitiveness plays an important role in the efficiency and productivity of the Economic zone. The research analyzed the current state of competitiveness of Nghi Son economic zone, Thanh Hoa province, by means of analysis, synthesis, statistics and comparison based on the data source of Nghi Son economic zone management board. After screening and processing, the following results are obtained: (i) Competition at the enterprise level: foreign-invested enterprises act in a small number of projects but account for 73.68 of total investment capital. The number of assembly, processing and processing projects in the economic zone accounts for a large proportion, of which petrochemical and chemical industry projects take two-thirds of the registered capital, lack of the presence of other industries; (ii) Competition at the local level: Infrastructure investment projects are mobilized from central capital and socialized to build relatively synchronous and complete hard and soft infrastructure; living environment and investment support services to meet practical needs. (iii); Availability factors in the economic zone: the favorable geographical location and abundant natural resources are the factors that create the competitiveness of the economic zone. However, the problem of Nghi Son Economic Zone is that there are still some limitations that need to be overcome to improve competitiveness in the coming time.

Sparse-view Cone-beam Breast CT Reconstruction via cGAN Constrained by Image Edges

Clinical applications of cone-beam breast CT(CBBCT) are hindered by relatively higher radiation dose and longer scan time. This study proposes sparse-view CBBCT, i.e. with a small number of projections, to overcome the above bottlenecks. A deep learning method - conditional generative adversarial network constrained by image edges (ECGAN) - is proposed to suppress artifacts on sparse-view CBBCT images reconstructed by filtered backprojection (FBP). The discriminator of the ECGAN is the combination of patchGAN and LSGAN for preserving high frequency information, with a modified U-net as the generator. To further preserve subtle structures and micro calcifications which are particularly important for breast cancer screening and diagnosis, edge images of CBBCT are added to both the generator and the discriminator to guide the learning. The proposed algorithm has been evaluated on 20 clinical raw datasets of CBBCT. ECGAN substantially improves the image qualities of sparse-view CBBCT, with a performance superior to those of total variation (TV) based iterative reconstruction and FBPConvNet based post-processing. On one CBBCT case with the projection number reduced from 300 to 100, ECGAN enhances peak-signal-to-noise ratio (PSNR) and structural similarity (SSIM) on FBP reconstruction from 24.26 and 0.812 to 37.78 and 0.963, respectively. These results indicate that ECGAN successfully reduces radiation dose and scan time of CBBCT by 1/3 with only small image degradations.

Discrete Terahertz tomography: a simulation study

As Terahertz (THz) technology becomes more prominent in the imaging industry, there is a rising need for improved reconstruction techniques for THz tomographic imaging. Conventional reconstruction techniques yield artifacts for limited data problems, hindering further analysis of the reconstruction. In this paper, we explore a discrete reconstruction algorithm for Terahertz tomography, which exploits prior knowledge on the gray levels in the imaging data of the object to obtain high quality reconstructions. Simulations show that, compared to THz-SIRT reconstruction, the discrete THz algorithm (THz-DART) generates more accurate reconstructions, especially when only a small number of projections or projections acquired within a limited angular range are available.

Analysis of the results of a computational experiment to restore the discontinuous functions of two variables using projections

This article presents the main statements of the method of approximation of discontinuous functions of two variables, describing an image of the surface of a 2D body or an image of the internal structure of a 3D body in a certain plane, using projections that come from a computer tomograph. The method is based on the use of discontinuous splines of two variables and finite Fourier sums, in which the Fourier coefficients are found using projection data. The method is based on the following idea: an approximated discontinuous function is replaced by the sum of two functions – a discontinuous spline and a continuous or differentiable function. A method is proposed for constructing a spline function, which has on the indicated lines the same discontinuities of the first kind as the approximated discontinuous function, and a method for finding the Fourier coefficients of the indicated continuous or differentiable function. That is, the difference between the function being approximated and the specified discontinuous spline is a function that can be approximated by finite Fourier sums without the Gibbs phenomenon. In the numerical experiment, it was assumed that the approximated function has discontinuities of the first kind on a given system of circles and ellipses nested into each other. The analysis of the calculation results showed their correspondence to the theoretical statements of the work. The proposed method makes it possible to obtain a given approximation accuracy with a smaller number of projections, that is, with less irradiation.

Computed tomography image reconstruction using stacked U-Net

Since the development of deep learning methods, many researchers have focused on image quality improvement using convolutional neural networks. They proved its effectivity in noise reduction, single-image super-resolution, and segmentation. In this study, we apply stacked U-Net, a deep learning method, for X-ray computed tomography image reconstruction to generate high-quality images in a short time with a small number of projections. It is not easy to create highly accurate models because medical images have few training images due to patients' privacy issues. Thus, we utilize various images from the ImageNet, a widely known visual database. Results show that a cross-sectional image with a peak signal-to-noise ratio of 27.93 db and a structural similarity of 0.886 is recovered for a 512 × 512 image using 360-degree rotation, 512 detectors, and 64 projections, with a processing time of 0.11 s on the GPU. Therefore, the proposed method has a shorter reconstruction time and better image quality than the existing methods.

A Hybrid Multi-Population Approach to the Project Portfolio Selection and Scheduling Problem for Future Force Design

Future Force Design (FFD) is a strategic planning activity that decides the programming of defence capability options. This is a complex problem faced by the Australian Department of Defence (DoD) and requires the simultaneous selection and scheduling of projects. Specifically, this is a NP-hard problem known as the Project Portfolio Selection and Scheduling Problem (PPSSP). While the PPSSP is a complex problem itself, its complexity is further increased when coupled with the additional characteristics that arise in the context of defence-oriented planning, such as long planning periods and complex operational constraints. As a result, many previous studies examined only a small number of projects over a short planning period and are largely unsuitable for the scale required in the defence sector. To address this issue, two primary contributions are made in this paper. Firstly, this study describes a complex practical PPSSP, inspired by the FFD process, and develops a corresponding mathematical model. Problem instances are derived from real-world, publicly-available defence data. Secondly, to address instances of the problem, two existing meta-heuristics are considered and a hybrid, multi-population approach is proposed. Results are compared against those attained by a commercial exact solver and indicate that there is no statistically significant difference in performance between the proposed multi-population approach and the exact solver. A key benefit of the proposed meta-heuristic approach is that its run time is not significantly influenced by the complexity of the problem instance. Additionally, many interesting practical insights regarding the solution of selection and scheduling problems are uncovered.

التجارة الاجتماعية و دورها في تحقيق ابعاد الميزة التنافسية / دراسة استطلاعية لآراء مديري عدد من المشاريع الصغيرة في مدينة دهوك

يهدف هذا البحث إلى التعرف على تأثير التجارة الاجتماعية على الميزة التنافسية في عدد من المشاريع الصغيرة في مدينة دهوك . وتمثلت مشكلة البحث في السؤال الرئيسي هل تؤدي التجارة الاجتماعية الى تحقيق المزايا التنافسية بالنسبة للمشاريع المبحوثة؟.ولقد اعتمد الباحثان على اختبار التجارة الاجتماعية كمتغير مستقل والتي تمثلت ب ( التسويق الاجتماعي ، التقييم والمراجعة ، تحسين وسائل التواصل الاجتماعي ، الاعلانات والتطبيقات الاجتماعية ، المنتديات والتجمعات ، التوصيات والاجتماعية ) و الميزة التنافسية كمتغير معتمد. وتم صياغة فرضيتين اساسيتين للبحث وهما 1. توجد علاقات ارتباط معنوية طردية بين التجارة الاجتماعية كمتغير مستقل والميزة التنافسية كمتغير معتمد.2. توجد علاقة تأثير معنوية للتجارة الاجتماعية كمتغير مستقل في الميزة التنافسية كمتغير معتمد. وسيعتمد البحث على الاستبانة كأداة رئيسية لجمع بيانات الجانب الميداني، وباستخدام عدد من الاساليب الاحصائية في تحليل البيانات. تمثلت اهم نتائج البحث بتفهم العينة المبحوثة إلى كل من مفهوم التجارة الاجتماعية و الميزة التنافسية وملاحظتهما اثناء الاداء الوظيفي، ويستنتج من التحليل الاحصائي بأن هناك علاقة ارتباط و تأثير قوية بين التجارة الاجتماعية و الميزة التنافسية. وفي ضوء تلك الاستنتاجات وصفت الدراسة عدداً من المقترحات تخدم الميدان المبحوث عنها لعل أهمها تجسد بضرورة قيام الادارة العليا بالقرب من الزبائن و تهيئة المناخ الداعم لمشاركتهم وذلك عن طريق الاهتمام بأخذ آرائهم و توجهاتهم عن منتجات الشركة عن طريق منصات اجتماعية على مواقع التواصل الاجتماعي تمكن المشروع من تحقيق الميزة التنافسية لها مقارنة بالمنافسين.

Application of Project Activities in Culture

The purpose of the article is to consider an issue of application of project activities in culture.Research methodology. The study is based on the combination of methods: systemic, sociocultural approach, the fundamental tenets of the theory and history of culture management. The authors use general scientific and interdisciplinary methods of research: analysis and synthesis, induction and deduction, comparison, generalization, formalization.Results. The paper studies various levels of public institutions, foreign entities and representative offices holding competitive selections for the cultural projects in Ukraine, the strategy and goals of the state regarding the growth options, types and levels of projects, methods of funding and implementation. It is noted that significant number of projects are of cultural and recreational nature, the small number of projects are patriotic or with a focus on the needs of inclusion, singular student projects.Novelty. An attempt is made at considering the project activities in Ukraine on micro-and macro-levels based on the state programs in culturology. The dynamics of public demand for the cultural projects is found out.The practical significance. Recently there has been a shift in cultural demand from the ethnic and traditional to the post-modern and festival with a build-up of civilian considerations. Therefore, there is a need to engage culturology as a reflection mechanism of the current situation, the circulation of symbols and dynamics of tastes as well as its consideration within the framework of state strategies and decentralization in the implementation of cultural projects.

Crowdfunding – revealing preferences for environmental goods

PurposeA major problem in environmental economics is to estimate the monetary value of non-market goods. This is especially relevant for environmental goods. To assess their non-use value, different approaches have been used measuring stated and revealed preferences. However, both methodologies are associated with criticism. The purpose of this paper is to propose a new method to estimate non-use values of environmental goods, i.e., to calculate revealed preferences in crowdfunded projects.Design/methodology/approachSince millions of individuals invest in various crowdfunded projects, the willingness to pay (WTP) can be robustly derived for any kind of project. Here, data on 19 projects on three endangered species are collected from various crowdfunding platforms.FindingsWith the new method introduced to estimate the monetary value of non-market goods, the WTP could be determined for a number of projects. Across projects, the average WTP per person is $42 for dolphins, $45 for falcons and $38 for butterflies. This new approach is validated by comparing these values to a meta-analysis of contingent valuation studies reporting on average $42 for dolphins, $37 for falcons and $24 for butterflies.Research limitations/implicationsThe limitation of this study is the small number of projects which are for demonstration only.Practical implicationsValidating this method by a comparison with a meta-analysis of contingent valuation shows that estimating WTP via crowdfunding may serve as a new instrument. Given the large number of subjects and diversity of projects in crowdfunding, a robust WTP could be derived for many topics in the future.Originality/valueA new method to estimate the monetary value of non-market goods is introduced. Estimating the WTP via crowdfunded projects makes it possible to measure revealed preferences for a large variety of environmental and other projects.

Analytic Computed Tomography Reconstruction in Sparse-Angular Sampling Using a Sinogram-Normalization Interpolation Method

This study investigated analytic computed tomography (CT) reconstruction in sparse-angular sampling using a new sinogram interpolation method to reduce patient radiation dosage. In sparse-angle CT, only a small number of projections, far less than what is required by the Nyquist sampling theory, are taken from the CT system and used for image reconstruction. However, CT images reconstructed by using the standard filtered-backprojection algorithm usually suffer from severe streak artifacts due to theoretically insufficient angular sampling. In this study, a new sinogram interpolation method, the so-called sinogram-normalization interpolation, was introduced to the analytic sparse-angle CT reconstruction to alleviate such artifacts. To validate the proposed method, we performed a systematic simulation and experiment and investigated the image characteristics. CT images were reconstructed using the three sparse-angular samplings of 100, 120, and 150, and their image qualities were quantitatively evaluated in terms of the intensity profile, the peak signal-tonoise ratio, and the universal quality index. The results indicated that the proposed interpolation method effectively reduced streak artifacts in the analytic sparse-angle CT reconstruction, thus maintaining the image quality.