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      The usefulness of SwiftScan technology for bone scintigraphy using a novel anthropomorphic phantom

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          Abstract

          The aim of this study was to demonstrate the usefulness of SwiftScan with a low-energy high-resolution and sensitivity (LEHRS) collimator for bone scintigraphy using a novel bone phantom simulating the human body. SwiftScan planar image of lateral view was acquired in clinical condition; thereafter, each planar image of different blend ratio (0–80%) of Crality 2D processing were created. SwiftScan planar images with reduced acquisition time by 25–75% were created by Poisson’s resampling processing. SwiftScan single photon emission computed tomography (SPECT) was acquired with step-and-shoot and continuous mode, and SPECT images were reconstructed using a three-dimensional ordered subset expectation maximization incorporating attenuation, scatter and spatial resolution corrections. SwiftScan planar image showed a high contrast to noise ratio (CNR) and low percent of the coefficient of variance (%CV) compared with conventional planar image. The CNR of the tumor parts in SwiftScan SPECT was higher than that of the conventional SPECT image of step and shoot acquisition, while the %CV showed the lowest value in all systems. In conclusion, SwiftScan planar and SPECT images were able to reduce the image noise compared with planar and SPECT image with a low-energy high-resolution collimator, so that SwiftScan planar and SPECT images could be obtained a high CNR. Furthermore, the SwiftScan planar image was able to reduce the acquisition time by 25% when the blend ratio of Clarity 2D processing set to more than 40%.

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          Bayesian-Based Iterative Method of Image Restoration*

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            An iterative technique for the rectification of observed distributions

            L. B. Lucy (1974)
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              On the origin of the bilateral filter and ways to improve it.

              M Elad (2002)
              Additive noise removal from a given signal is an important problem in signal processing. Among the most appealing aspects of this field are the ability to refer it to a well-established theory, and the fact that the proposed algorithms in this field are efficient and practical. Adaptive methods based on anisotropic diffusion (AD), weighted least squares (WLS), and robust estimation (RE) were proposed as iterative locally adaptive machines for noise removal. Tomasi and Manduchi (see Proc. 6th Int. Conf. Computer Vision, New Delhi, India, p.839-46, 1998) proposed an alternative noniterative bilateral filter for removing noise from images. This filter was shown to give similar and possibly better results to the ones obtained by iterative approaches. However, the bilateral filter was proposed as an intuitive tool without theoretical connection to the classical approaches. We propose such a bridge, and show that the bilateral filter also emerges from the Bayesian approach, as a single iteration of some well-known iterative algorithm. Based on this observation, we also show how the bilateral filter can be improved and extended to treat more general reconstruction problems.
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                Author and article information

                Contributors
                onoguchi@staff.kanazawa-u.ac.jp
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                29 January 2021
                29 January 2021
                2021
                : 11
                : 2644
                Affiliations
                [1 ]GRID grid.9707.9, ISNI 0000 0001 2308 3329, Department of Quantum Medical Technology, Institute of Medical, Pharmaceutical and Health Sciences, , Kanazawa University, ; Kanazawa, Japan
                [2 ]GRID grid.410821.e, ISNI 0000 0001 2173 8328, Clinical Imaging Center for Healthcare, , Nippon Medical School, ; Tokyo, Japan
                [3 ]GRID grid.412002.5, ISNI 0000 0004 0615 9100, Department of Radiological Technology, , Kanazawa University Hospital, ; Kanazawa, Japan
                [4 ]GRID grid.414830.a, ISNI 0000 0000 9573 4170, Department of Radiological Technology, , Ishikawa Prefectural Central Hospital, ; Kanazawa, Japan
                [5 ]GRID grid.9707.9, ISNI 0000 0001 2308 3329, Department of Functional Imaging and Artificial Intelligence, , Kanazawa University, ; Kanazawa, Japan
                Article
                82082
                10.1038/s41598-021-82082-x
                7846574
                33514818
                4cc2f1df-b111-49a9-9d98-540da6a37b8e
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 21 July 2020
                : 13 January 2021
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                © The Author(s) 2021

                Uncategorized
                medical research,molecular medicine,materials science
                Uncategorized
                medical research, molecular medicine, materials science

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