Improved Cohen-Sutherland algorithm for TGS transmission imaging
Abstract Tomographic gamma scanner (TGS), an advanced γ-ray nondestructive analysis technique, can locate and analyze nuclides in radioactive nuclear waste, and TGS can be categorized into two processes: e.g., transmission measurement and emission measurement. Specifically, transmission measurements...
Ausführliche Beschreibung
Autor*in: |
Yan, Yu-Cheng [verfasserIn] |
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E-Artikel |
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Englisch |
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2023 |
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Anmerkung: |
© The Author(s), under exclusive licence to China Science Publishing & Media Ltd. (Science Press), Shanghai Institute of Applied Physics, the Chinese Academy of Sciences, Chinese Nuclear Society 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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Übergeordnetes Werk: |
Enthalten in: Nuclear science and techniques - Singapore : Springer, 2006, 34(2023), 6 vom: Juni |
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Übergeordnetes Werk: |
volume:34 ; year:2023 ; number:6 ; month:06 |
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DOI / URN: |
10.1007/s41365-023-01238-8 |
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Katalog-ID: |
SPR052076768 |
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520 | |a Abstract Tomographic gamma scanner (TGS), an advanced γ-ray nondestructive analysis technique, can locate and analyze nuclides in radioactive nuclear waste, and TGS can be categorized into two processes: e.g., transmission measurement and emission measurement. Specifically, transmission measurements provide the basis for accurate measurement of nonuniform radionuclide content in TGS scanning. The scan data were obtained using the Monte Carlo tool Geant4 simulation, and 25 voxels were divided into five lengths and five widths in a square barrel. In this study, an encoding cropping algorithm based on draped foot vector judgment was adopted to rapidly calculate the voxel trace matrix within a square bucket of nuclear waste, and the transmission images were reconstructed using ordered subset expectation maximization. The results indicated that the cropping speed of the improved coding algorithm was significantly higher than that of the original algorithm, and the relative mean deviation and root-mean-square error between the reconstructed attenuation coefficient and the reference standard value tended to decrease with an increase in the cropped line segments in the voxel; the Pearson correlation coefficient tended to converge to 1.0. The image quality evaluation parameters of the high media-density materials were better than those of the low media-density materials in the above three indexes. The reconstruction effect was relatively poor for more complex filling materials. When there were more than 10 cropped line segments in the voxel, the reconstruction data generally tended to be stable. The graphical trimming algorithm can rapidly calculate the trace matrix of the scanned voxels; it exhibits the advantages of speed and efficiency and can serve as a novel method to solve the trace matrix of TGS nuclear waste transmission scans. | ||
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700 | 1 | |a Chang, Lan |4 aut | |
700 | 1 | |a Li, Cui |4 aut | |
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10.1007/s41365-023-01238-8 doi (DE-627)SPR052076768 (SPR)s41365-023-01238-8-e DE-627 ger DE-627 rakwb eng Yan, Yu-Cheng verfasserin aut Improved Cohen-Sutherland algorithm for TGS transmission imaging 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to China Science Publishing & Media Ltd. (Science Press), Shanghai Institute of Applied Physics, the Chinese Academy of Sciences, Chinese Nuclear Society 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Tomographic gamma scanner (TGS), an advanced γ-ray nondestructive analysis technique, can locate and analyze nuclides in radioactive nuclear waste, and TGS can be categorized into two processes: e.g., transmission measurement and emission measurement. Specifically, transmission measurements provide the basis for accurate measurement of nonuniform radionuclide content in TGS scanning. The scan data were obtained using the Monte Carlo tool Geant4 simulation, and 25 voxels were divided into five lengths and five widths in a square barrel. In this study, an encoding cropping algorithm based on draped foot vector judgment was adopted to rapidly calculate the voxel trace matrix within a square bucket of nuclear waste, and the transmission images were reconstructed using ordered subset expectation maximization. The results indicated that the cropping speed of the improved coding algorithm was significantly higher than that of the original algorithm, and the relative mean deviation and root-mean-square error between the reconstructed attenuation coefficient and the reference standard value tended to decrease with an increase in the cropped line segments in the voxel; the Pearson correlation coefficient tended to converge to 1.0. The image quality evaluation parameters of the high media-density materials were better than those of the low media-density materials in the above three indexes. The reconstruction effect was relatively poor for more complex filling materials. When there were more than 10 cropped line segments in the voxel, the reconstruction data generally tended to be stable. The graphical trimming algorithm can rapidly calculate the trace matrix of the scanned voxels; it exhibits the advantages of speed and efficiency and can serve as a novel method to solve the trace matrix of TGS nuclear waste transmission scans. TGS (dpeaa)DE-He213 Cohen-Sutherland (dpeaa)DE-He213 Transmission scanning (dpeaa)DE-He213 Trace matrix (dpeaa)DE-He213 Liu, Ming-Zhe (orcid)0000-0002-5060-5492 aut Li, Xing-Yu aut Xiong, Yu-Ting aut Tan, Yao aut Zuo, Zhuo aut Chang, Lan aut Li, Cui aut Enthalten in Nuclear science and techniques Singapore : Springer, 2006 34(2023), 6 vom: Juni (DE-627)513219439 (DE-600)2238719-5 2210-3147 nnns volume:34 year:2023 number:6 month:06 https://dx.doi.org/10.1007/s41365-023-01238-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 34 2023 6 06 |
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10.1007/s41365-023-01238-8 doi (DE-627)SPR052076768 (SPR)s41365-023-01238-8-e DE-627 ger DE-627 rakwb eng Yan, Yu-Cheng verfasserin aut Improved Cohen-Sutherland algorithm for TGS transmission imaging 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to China Science Publishing & Media Ltd. (Science Press), Shanghai Institute of Applied Physics, the Chinese Academy of Sciences, Chinese Nuclear Society 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Tomographic gamma scanner (TGS), an advanced γ-ray nondestructive analysis technique, can locate and analyze nuclides in radioactive nuclear waste, and TGS can be categorized into two processes: e.g., transmission measurement and emission measurement. Specifically, transmission measurements provide the basis for accurate measurement of nonuniform radionuclide content in TGS scanning. The scan data were obtained using the Monte Carlo tool Geant4 simulation, and 25 voxels were divided into five lengths and five widths in a square barrel. In this study, an encoding cropping algorithm based on draped foot vector judgment was adopted to rapidly calculate the voxel trace matrix within a square bucket of nuclear waste, and the transmission images were reconstructed using ordered subset expectation maximization. The results indicated that the cropping speed of the improved coding algorithm was significantly higher than that of the original algorithm, and the relative mean deviation and root-mean-square error between the reconstructed attenuation coefficient and the reference standard value tended to decrease with an increase in the cropped line segments in the voxel; the Pearson correlation coefficient tended to converge to 1.0. The image quality evaluation parameters of the high media-density materials were better than those of the low media-density materials in the above three indexes. The reconstruction effect was relatively poor for more complex filling materials. When there were more than 10 cropped line segments in the voxel, the reconstruction data generally tended to be stable. The graphical trimming algorithm can rapidly calculate the trace matrix of the scanned voxels; it exhibits the advantages of speed and efficiency and can serve as a novel method to solve the trace matrix of TGS nuclear waste transmission scans. TGS (dpeaa)DE-He213 Cohen-Sutherland (dpeaa)DE-He213 Transmission scanning (dpeaa)DE-He213 Trace matrix (dpeaa)DE-He213 Liu, Ming-Zhe (orcid)0000-0002-5060-5492 aut Li, Xing-Yu aut Xiong, Yu-Ting aut Tan, Yao aut Zuo, Zhuo aut Chang, Lan aut Li, Cui aut Enthalten in Nuclear science and techniques Singapore : Springer, 2006 34(2023), 6 vom: Juni (DE-627)513219439 (DE-600)2238719-5 2210-3147 nnns volume:34 year:2023 number:6 month:06 https://dx.doi.org/10.1007/s41365-023-01238-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 34 2023 6 06 |
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10.1007/s41365-023-01238-8 doi (DE-627)SPR052076768 (SPR)s41365-023-01238-8-e DE-627 ger DE-627 rakwb eng Yan, Yu-Cheng verfasserin aut Improved Cohen-Sutherland algorithm for TGS transmission imaging 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to China Science Publishing & Media Ltd. (Science Press), Shanghai Institute of Applied Physics, the Chinese Academy of Sciences, Chinese Nuclear Society 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Tomographic gamma scanner (TGS), an advanced γ-ray nondestructive analysis technique, can locate and analyze nuclides in radioactive nuclear waste, and TGS can be categorized into two processes: e.g., transmission measurement and emission measurement. Specifically, transmission measurements provide the basis for accurate measurement of nonuniform radionuclide content in TGS scanning. The scan data were obtained using the Monte Carlo tool Geant4 simulation, and 25 voxels were divided into five lengths and five widths in a square barrel. In this study, an encoding cropping algorithm based on draped foot vector judgment was adopted to rapidly calculate the voxel trace matrix within a square bucket of nuclear waste, and the transmission images were reconstructed using ordered subset expectation maximization. The results indicated that the cropping speed of the improved coding algorithm was significantly higher than that of the original algorithm, and the relative mean deviation and root-mean-square error between the reconstructed attenuation coefficient and the reference standard value tended to decrease with an increase in the cropped line segments in the voxel; the Pearson correlation coefficient tended to converge to 1.0. The image quality evaluation parameters of the high media-density materials were better than those of the low media-density materials in the above three indexes. The reconstruction effect was relatively poor for more complex filling materials. When there were more than 10 cropped line segments in the voxel, the reconstruction data generally tended to be stable. The graphical trimming algorithm can rapidly calculate the trace matrix of the scanned voxels; it exhibits the advantages of speed and efficiency and can serve as a novel method to solve the trace matrix of TGS nuclear waste transmission scans. TGS (dpeaa)DE-He213 Cohen-Sutherland (dpeaa)DE-He213 Transmission scanning (dpeaa)DE-He213 Trace matrix (dpeaa)DE-He213 Liu, Ming-Zhe (orcid)0000-0002-5060-5492 aut Li, Xing-Yu aut Xiong, Yu-Ting aut Tan, Yao aut Zuo, Zhuo aut Chang, Lan aut Li, Cui aut Enthalten in Nuclear science and techniques Singapore : Springer, 2006 34(2023), 6 vom: Juni (DE-627)513219439 (DE-600)2238719-5 2210-3147 nnns volume:34 year:2023 number:6 month:06 https://dx.doi.org/10.1007/s41365-023-01238-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 34 2023 6 06 |
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10.1007/s41365-023-01238-8 doi (DE-627)SPR052076768 (SPR)s41365-023-01238-8-e DE-627 ger DE-627 rakwb eng Yan, Yu-Cheng verfasserin aut Improved Cohen-Sutherland algorithm for TGS transmission imaging 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to China Science Publishing & Media Ltd. (Science Press), Shanghai Institute of Applied Physics, the Chinese Academy of Sciences, Chinese Nuclear Society 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Tomographic gamma scanner (TGS), an advanced γ-ray nondestructive analysis technique, can locate and analyze nuclides in radioactive nuclear waste, and TGS can be categorized into two processes: e.g., transmission measurement and emission measurement. Specifically, transmission measurements provide the basis for accurate measurement of nonuniform radionuclide content in TGS scanning. The scan data were obtained using the Monte Carlo tool Geant4 simulation, and 25 voxels were divided into five lengths and five widths in a square barrel. In this study, an encoding cropping algorithm based on draped foot vector judgment was adopted to rapidly calculate the voxel trace matrix within a square bucket of nuclear waste, and the transmission images were reconstructed using ordered subset expectation maximization. The results indicated that the cropping speed of the improved coding algorithm was significantly higher than that of the original algorithm, and the relative mean deviation and root-mean-square error between the reconstructed attenuation coefficient and the reference standard value tended to decrease with an increase in the cropped line segments in the voxel; the Pearson correlation coefficient tended to converge to 1.0. The image quality evaluation parameters of the high media-density materials were better than those of the low media-density materials in the above three indexes. The reconstruction effect was relatively poor for more complex filling materials. When there were more than 10 cropped line segments in the voxel, the reconstruction data generally tended to be stable. The graphical trimming algorithm can rapidly calculate the trace matrix of the scanned voxels; it exhibits the advantages of speed and efficiency and can serve as a novel method to solve the trace matrix of TGS nuclear waste transmission scans. TGS (dpeaa)DE-He213 Cohen-Sutherland (dpeaa)DE-He213 Transmission scanning (dpeaa)DE-He213 Trace matrix (dpeaa)DE-He213 Liu, Ming-Zhe (orcid)0000-0002-5060-5492 aut Li, Xing-Yu aut Xiong, Yu-Ting aut Tan, Yao aut Zuo, Zhuo aut Chang, Lan aut Li, Cui aut Enthalten in Nuclear science and techniques Singapore : Springer, 2006 34(2023), 6 vom: Juni (DE-627)513219439 (DE-600)2238719-5 2210-3147 nnns volume:34 year:2023 number:6 month:06 https://dx.doi.org/10.1007/s41365-023-01238-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 34 2023 6 06 |
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10.1007/s41365-023-01238-8 doi (DE-627)SPR052076768 (SPR)s41365-023-01238-8-e DE-627 ger DE-627 rakwb eng Yan, Yu-Cheng verfasserin aut Improved Cohen-Sutherland algorithm for TGS transmission imaging 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to China Science Publishing & Media Ltd. (Science Press), Shanghai Institute of Applied Physics, the Chinese Academy of Sciences, Chinese Nuclear Society 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Tomographic gamma scanner (TGS), an advanced γ-ray nondestructive analysis technique, can locate and analyze nuclides in radioactive nuclear waste, and TGS can be categorized into two processes: e.g., transmission measurement and emission measurement. Specifically, transmission measurements provide the basis for accurate measurement of nonuniform radionuclide content in TGS scanning. The scan data were obtained using the Monte Carlo tool Geant4 simulation, and 25 voxels were divided into five lengths and five widths in a square barrel. In this study, an encoding cropping algorithm based on draped foot vector judgment was adopted to rapidly calculate the voxel trace matrix within a square bucket of nuclear waste, and the transmission images were reconstructed using ordered subset expectation maximization. The results indicated that the cropping speed of the improved coding algorithm was significantly higher than that of the original algorithm, and the relative mean deviation and root-mean-square error between the reconstructed attenuation coefficient and the reference standard value tended to decrease with an increase in the cropped line segments in the voxel; the Pearson correlation coefficient tended to converge to 1.0. The image quality evaluation parameters of the high media-density materials were better than those of the low media-density materials in the above three indexes. The reconstruction effect was relatively poor for more complex filling materials. When there were more than 10 cropped line segments in the voxel, the reconstruction data generally tended to be stable. The graphical trimming algorithm can rapidly calculate the trace matrix of the scanned voxels; it exhibits the advantages of speed and efficiency and can serve as a novel method to solve the trace matrix of TGS nuclear waste transmission scans. TGS (dpeaa)DE-He213 Cohen-Sutherland (dpeaa)DE-He213 Transmission scanning (dpeaa)DE-He213 Trace matrix (dpeaa)DE-He213 Liu, Ming-Zhe (orcid)0000-0002-5060-5492 aut Li, Xing-Yu aut Xiong, Yu-Ting aut Tan, Yao aut Zuo, Zhuo aut Chang, Lan aut Li, Cui aut Enthalten in Nuclear science and techniques Singapore : Springer, 2006 34(2023), 6 vom: Juni (DE-627)513219439 (DE-600)2238719-5 2210-3147 nnns volume:34 year:2023 number:6 month:06 https://dx.doi.org/10.1007/s41365-023-01238-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 34 2023 6 06 |
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Yan, Yu-Cheng @@aut@@ Liu, Ming-Zhe @@aut@@ Li, Xing-Yu @@aut@@ Xiong, Yu-Ting @@aut@@ Tan, Yao @@aut@@ Zuo, Zhuo @@aut@@ Chang, Lan @@aut@@ Li, Cui @@aut@@ |
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(Science Press), Shanghai Institute of Applied Physics, the Chinese Academy of Sciences, Chinese Nuclear Society 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Tomographic gamma scanner (TGS), an advanced γ-ray nondestructive analysis technique, can locate and analyze nuclides in radioactive nuclear waste, and TGS can be categorized into two processes: e.g., transmission measurement and emission measurement. Specifically, transmission measurements provide the basis for accurate measurement of nonuniform radionuclide content in TGS scanning. The scan data were obtained using the Monte Carlo tool Geant4 simulation, and 25 voxels were divided into five lengths and five widths in a square barrel. In this study, an encoding cropping algorithm based on draped foot vector judgment was adopted to rapidly calculate the voxel trace matrix within a square bucket of nuclear waste, and the transmission images were reconstructed using ordered subset expectation maximization. The results indicated that the cropping speed of the improved coding algorithm was significantly higher than that of the original algorithm, and the relative mean deviation and root-mean-square error between the reconstructed attenuation coefficient and the reference standard value tended to decrease with an increase in the cropped line segments in the voxel; the Pearson correlation coefficient tended to converge to 1.0. The image quality evaluation parameters of the high media-density materials were better than those of the low media-density materials in the above three indexes. The reconstruction effect was relatively poor for more complex filling materials. When there were more than 10 cropped line segments in the voxel, the reconstruction data generally tended to be stable. The graphical trimming algorithm can rapidly calculate the trace matrix of the scanned voxels; it exhibits the advantages of speed and efficiency and can serve as a novel method to solve the trace matrix of TGS nuclear waste transmission scans.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">TGS</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Cohen-Sutherland</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Transmission scanning</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Trace matrix</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Liu, Ming-Zhe</subfield><subfield code="0">(orcid)0000-0002-5060-5492</subfield><subfield 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Yan, Yu-Cheng |
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Yan, Yu-Cheng misc TGS misc Cohen-Sutherland misc Transmission scanning misc Trace matrix Improved Cohen-Sutherland algorithm for TGS transmission imaging |
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Improved Cohen-Sutherland algorithm for TGS transmission imaging TGS (dpeaa)DE-He213 Cohen-Sutherland (dpeaa)DE-He213 Transmission scanning (dpeaa)DE-He213 Trace matrix (dpeaa)DE-He213 |
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improved cohen-sutherland algorithm for tgs transmission imaging |
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Improved Cohen-Sutherland algorithm for TGS transmission imaging |
abstract |
Abstract Tomographic gamma scanner (TGS), an advanced γ-ray nondestructive analysis technique, can locate and analyze nuclides in radioactive nuclear waste, and TGS can be categorized into two processes: e.g., transmission measurement and emission measurement. Specifically, transmission measurements provide the basis for accurate measurement of nonuniform radionuclide content in TGS scanning. The scan data were obtained using the Monte Carlo tool Geant4 simulation, and 25 voxels were divided into five lengths and five widths in a square barrel. In this study, an encoding cropping algorithm based on draped foot vector judgment was adopted to rapidly calculate the voxel trace matrix within a square bucket of nuclear waste, and the transmission images were reconstructed using ordered subset expectation maximization. The results indicated that the cropping speed of the improved coding algorithm was significantly higher than that of the original algorithm, and the relative mean deviation and root-mean-square error between the reconstructed attenuation coefficient and the reference standard value tended to decrease with an increase in the cropped line segments in the voxel; the Pearson correlation coefficient tended to converge to 1.0. The image quality evaluation parameters of the high media-density materials were better than those of the low media-density materials in the above three indexes. The reconstruction effect was relatively poor for more complex filling materials. When there were more than 10 cropped line segments in the voxel, the reconstruction data generally tended to be stable. The graphical trimming algorithm can rapidly calculate the trace matrix of the scanned voxels; it exhibits the advantages of speed and efficiency and can serve as a novel method to solve the trace matrix of TGS nuclear waste transmission scans. © The Author(s), under exclusive licence to China Science Publishing & Media Ltd. (Science Press), Shanghai Institute of Applied Physics, the Chinese Academy of Sciences, Chinese Nuclear Society 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
abstractGer |
Abstract Tomographic gamma scanner (TGS), an advanced γ-ray nondestructive analysis technique, can locate and analyze nuclides in radioactive nuclear waste, and TGS can be categorized into two processes: e.g., transmission measurement and emission measurement. Specifically, transmission measurements provide the basis for accurate measurement of nonuniform radionuclide content in TGS scanning. The scan data were obtained using the Monte Carlo tool Geant4 simulation, and 25 voxels were divided into five lengths and five widths in a square barrel. In this study, an encoding cropping algorithm based on draped foot vector judgment was adopted to rapidly calculate the voxel trace matrix within a square bucket of nuclear waste, and the transmission images were reconstructed using ordered subset expectation maximization. The results indicated that the cropping speed of the improved coding algorithm was significantly higher than that of the original algorithm, and the relative mean deviation and root-mean-square error between the reconstructed attenuation coefficient and the reference standard value tended to decrease with an increase in the cropped line segments in the voxel; the Pearson correlation coefficient tended to converge to 1.0. The image quality evaluation parameters of the high media-density materials were better than those of the low media-density materials in the above three indexes. The reconstruction effect was relatively poor for more complex filling materials. When there were more than 10 cropped line segments in the voxel, the reconstruction data generally tended to be stable. The graphical trimming algorithm can rapidly calculate the trace matrix of the scanned voxels; it exhibits the advantages of speed and efficiency and can serve as a novel method to solve the trace matrix of TGS nuclear waste transmission scans. © The Author(s), under exclusive licence to China Science Publishing & Media Ltd. (Science Press), Shanghai Institute of Applied Physics, the Chinese Academy of Sciences, Chinese Nuclear Society 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
abstract_unstemmed |
Abstract Tomographic gamma scanner (TGS), an advanced γ-ray nondestructive analysis technique, can locate and analyze nuclides in radioactive nuclear waste, and TGS can be categorized into two processes: e.g., transmission measurement and emission measurement. Specifically, transmission measurements provide the basis for accurate measurement of nonuniform radionuclide content in TGS scanning. The scan data were obtained using the Monte Carlo tool Geant4 simulation, and 25 voxels were divided into five lengths and five widths in a square barrel. In this study, an encoding cropping algorithm based on draped foot vector judgment was adopted to rapidly calculate the voxel trace matrix within a square bucket of nuclear waste, and the transmission images were reconstructed using ordered subset expectation maximization. The results indicated that the cropping speed of the improved coding algorithm was significantly higher than that of the original algorithm, and the relative mean deviation and root-mean-square error between the reconstructed attenuation coefficient and the reference standard value tended to decrease with an increase in the cropped line segments in the voxel; the Pearson correlation coefficient tended to converge to 1.0. The image quality evaluation parameters of the high media-density materials were better than those of the low media-density materials in the above three indexes. The reconstruction effect was relatively poor for more complex filling materials. When there were more than 10 cropped line segments in the voxel, the reconstruction data generally tended to be stable. The graphical trimming algorithm can rapidly calculate the trace matrix of the scanned voxels; it exhibits the advantages of speed and efficiency and can serve as a novel method to solve the trace matrix of TGS nuclear waste transmission scans. © The Author(s), under exclusive licence to China Science Publishing & Media Ltd. (Science Press), Shanghai Institute of Applied Physics, the Chinese Academy of Sciences, Chinese Nuclear Society 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
collection_details |
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container_issue |
6 |
title_short |
Improved Cohen-Sutherland algorithm for TGS transmission imaging |
url |
https://dx.doi.org/10.1007/s41365-023-01238-8 |
remote_bool |
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author2 |
Liu, Ming-Zhe Li, Xing-Yu Xiong, Yu-Ting Tan, Yao Zuo, Zhuo Chang, Lan Li, Cui |
author2Str |
Liu, Ming-Zhe Li, Xing-Yu Xiong, Yu-Ting Tan, Yao Zuo, Zhuo Chang, Lan Li, Cui |
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doi_str |
10.1007/s41365-023-01238-8 |
up_date |
2024-07-04T01:09:16.466Z |
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|
score |
7.3986673 |