Image Fusion Based on Evidence Theory for Multi-Energy X-Ray Computed Tomography
Abstract For diagnosis in industrial applications, X-Ray computed tomography (XCT) has proven its interest for various industrial applications where 3D imaging of complex shapes is required. However, it’s not possible to fully represent a multi-material object with a single XCT image. In such cases,...
Ausführliche Beschreibung
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| Autor*in: |
Oujebbour, Fatima Zahra [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2022 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 |
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| Übergeordnetes Werk: |
Enthalten in: Journal of nondestructive evaluation - Dordrecht [u.a.] : Springer Science + Business Media, 1980, 41(2022), 3 vom: 12. Juli |
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| Übergeordnetes Werk: |
volume:41 ; year:2022 ; number:3 ; day:12 ; month:07 |
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| DOI / URN: |
10.1007/s10921-022-00883-0 |
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SPR047572086 |
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| 520 | |a Abstract For diagnosis in industrial applications, X-Ray computed tomography (XCT) has proven its interest for various industrial applications where 3D imaging of complex shapes is required. However, it’s not possible to fully represent a multi-material object with a single XCT image. In such cases, valuable information can be revealed using multi-energy X-Ray computed tomography. This imaging technique has various advantages over standard XCT. Multi-energy XCT can either be done by using photon counting detectors in a single acquisition scan, or using energy integration detectors and several acquisition scans. In either case, several reconstructed images are obtained for each energy band. In the present study, a combination of projections acquired at different energy is done in such a way to provide the operator with a single XCT image where all the information is present. Although this information is qualitative, it allows to get the 3D imaging of the whole multi-material structure in a single reconstructed image. The proposed approach is based on the Dempster–Shafer evidence theory. | ||
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| 650 | 4 | |a Dempster–Shafer evidence theory |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Doudet, Valerie Kaftandjian |4 aut | |
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10.1007/s10921-022-00883-0 doi (DE-627)SPR047572086 (SPR)s10921-022-00883-0-e DE-627 ger DE-627 rakwb eng Oujebbour, Fatima Zahra verfasserin (orcid)0000-0003-0754-7634 aut Image Fusion Based on Evidence Theory for Multi-Energy X-Ray Computed Tomography 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 Abstract For diagnosis in industrial applications, X-Ray computed tomography (XCT) has proven its interest for various industrial applications where 3D imaging of complex shapes is required. However, it’s not possible to fully represent a multi-material object with a single XCT image. In such cases, valuable information can be revealed using multi-energy X-Ray computed tomography. This imaging technique has various advantages over standard XCT. Multi-energy XCT can either be done by using photon counting detectors in a single acquisition scan, or using energy integration detectors and several acquisition scans. In either case, several reconstructed images are obtained for each energy band. In the present study, a combination of projections acquired at different energy is done in such a way to provide the operator with a single XCT image where all the information is present. Although this information is qualitative, it allows to get the 3D imaging of the whole multi-material structure in a single reconstructed image. The proposed approach is based on the Dempster–Shafer evidence theory. X-ray computed tomography (dpeaa)DE-He213 Multi-material object (dpeaa)DE-He213 3D Imaging (dpeaa)DE-He213 Image reconstruction (dpeaa)DE-He213 Dempster–Shafer evidence theory (dpeaa)DE-He213 Doudet, Valerie Kaftandjian aut Enthalten in Journal of nondestructive evaluation Dordrecht [u.a.] : Springer Science + Business Media, 1980 41(2022), 3 vom: 12. Juli (DE-627)317859803 (DE-600)2017032-4 1573-4862 nnns volume:41 year:2022 number:3 day:12 month:07 https://dx.doi.org/10.1007/s10921-022-00883-0 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_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 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_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 41 2022 3 12 07 |
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10.1007/s10921-022-00883-0 doi (DE-627)SPR047572086 (SPR)s10921-022-00883-0-e DE-627 ger DE-627 rakwb eng Oujebbour, Fatima Zahra verfasserin (orcid)0000-0003-0754-7634 aut Image Fusion Based on Evidence Theory for Multi-Energy X-Ray Computed Tomography 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 Abstract For diagnosis in industrial applications, X-Ray computed tomography (XCT) has proven its interest for various industrial applications where 3D imaging of complex shapes is required. However, it’s not possible to fully represent a multi-material object with a single XCT image. In such cases, valuable information can be revealed using multi-energy X-Ray computed tomography. This imaging technique has various advantages over standard XCT. Multi-energy XCT can either be done by using photon counting detectors in a single acquisition scan, or using energy integration detectors and several acquisition scans. In either case, several reconstructed images are obtained for each energy band. In the present study, a combination of projections acquired at different energy is done in such a way to provide the operator with a single XCT image where all the information is present. Although this information is qualitative, it allows to get the 3D imaging of the whole multi-material structure in a single reconstructed image. The proposed approach is based on the Dempster–Shafer evidence theory. X-ray computed tomography (dpeaa)DE-He213 Multi-material object (dpeaa)DE-He213 3D Imaging (dpeaa)DE-He213 Image reconstruction (dpeaa)DE-He213 Dempster–Shafer evidence theory (dpeaa)DE-He213 Doudet, Valerie Kaftandjian aut Enthalten in Journal of nondestructive evaluation Dordrecht [u.a.] : Springer Science + Business Media, 1980 41(2022), 3 vom: 12. Juli (DE-627)317859803 (DE-600)2017032-4 1573-4862 nnns volume:41 year:2022 number:3 day:12 month:07 https://dx.doi.org/10.1007/s10921-022-00883-0 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_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 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_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 41 2022 3 12 07 |
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10.1007/s10921-022-00883-0 doi (DE-627)SPR047572086 (SPR)s10921-022-00883-0-e DE-627 ger DE-627 rakwb eng Oujebbour, Fatima Zahra verfasserin (orcid)0000-0003-0754-7634 aut Image Fusion Based on Evidence Theory for Multi-Energy X-Ray Computed Tomography 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 Abstract For diagnosis in industrial applications, X-Ray computed tomography (XCT) has proven its interest for various industrial applications where 3D imaging of complex shapes is required. However, it’s not possible to fully represent a multi-material object with a single XCT image. In such cases, valuable information can be revealed using multi-energy X-Ray computed tomography. This imaging technique has various advantages over standard XCT. Multi-energy XCT can either be done by using photon counting detectors in a single acquisition scan, or using energy integration detectors and several acquisition scans. In either case, several reconstructed images are obtained for each energy band. In the present study, a combination of projections acquired at different energy is done in such a way to provide the operator with a single XCT image where all the information is present. Although this information is qualitative, it allows to get the 3D imaging of the whole multi-material structure in a single reconstructed image. The proposed approach is based on the Dempster–Shafer evidence theory. X-ray computed tomography (dpeaa)DE-He213 Multi-material object (dpeaa)DE-He213 3D Imaging (dpeaa)DE-He213 Image reconstruction (dpeaa)DE-He213 Dempster–Shafer evidence theory (dpeaa)DE-He213 Doudet, Valerie Kaftandjian aut Enthalten in Journal of nondestructive evaluation Dordrecht [u.a.] : Springer Science + Business Media, 1980 41(2022), 3 vom: 12. Juli (DE-627)317859803 (DE-600)2017032-4 1573-4862 nnns volume:41 year:2022 number:3 day:12 month:07 https://dx.doi.org/10.1007/s10921-022-00883-0 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_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 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_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 41 2022 3 12 07 |
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10.1007/s10921-022-00883-0 doi (DE-627)SPR047572086 (SPR)s10921-022-00883-0-e DE-627 ger DE-627 rakwb eng Oujebbour, Fatima Zahra verfasserin (orcid)0000-0003-0754-7634 aut Image Fusion Based on Evidence Theory for Multi-Energy X-Ray Computed Tomography 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 Abstract For diagnosis in industrial applications, X-Ray computed tomography (XCT) has proven its interest for various industrial applications where 3D imaging of complex shapes is required. However, it’s not possible to fully represent a multi-material object with a single XCT image. In such cases, valuable information can be revealed using multi-energy X-Ray computed tomography. This imaging technique has various advantages over standard XCT. Multi-energy XCT can either be done by using photon counting detectors in a single acquisition scan, or using energy integration detectors and several acquisition scans. In either case, several reconstructed images are obtained for each energy band. In the present study, a combination of projections acquired at different energy is done in such a way to provide the operator with a single XCT image where all the information is present. Although this information is qualitative, it allows to get the 3D imaging of the whole multi-material structure in a single reconstructed image. The proposed approach is based on the Dempster–Shafer evidence theory. X-ray computed tomography (dpeaa)DE-He213 Multi-material object (dpeaa)DE-He213 3D Imaging (dpeaa)DE-He213 Image reconstruction (dpeaa)DE-He213 Dempster–Shafer evidence theory (dpeaa)DE-He213 Doudet, Valerie Kaftandjian aut Enthalten in Journal of nondestructive evaluation Dordrecht [u.a.] : Springer Science + Business Media, 1980 41(2022), 3 vom: 12. Juli (DE-627)317859803 (DE-600)2017032-4 1573-4862 nnns volume:41 year:2022 number:3 day:12 month:07 https://dx.doi.org/10.1007/s10921-022-00883-0 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_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 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_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 41 2022 3 12 07 |
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10.1007/s10921-022-00883-0 doi (DE-627)SPR047572086 (SPR)s10921-022-00883-0-e DE-627 ger DE-627 rakwb eng Oujebbour, Fatima Zahra verfasserin (orcid)0000-0003-0754-7634 aut Image Fusion Based on Evidence Theory for Multi-Energy X-Ray Computed Tomography 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 Abstract For diagnosis in industrial applications, X-Ray computed tomography (XCT) has proven its interest for various industrial applications where 3D imaging of complex shapes is required. However, it’s not possible to fully represent a multi-material object with a single XCT image. In such cases, valuable information can be revealed using multi-energy X-Ray computed tomography. This imaging technique has various advantages over standard XCT. Multi-energy XCT can either be done by using photon counting detectors in a single acquisition scan, or using energy integration detectors and several acquisition scans. In either case, several reconstructed images are obtained for each energy band. In the present study, a combination of projections acquired at different energy is done in such a way to provide the operator with a single XCT image where all the information is present. Although this information is qualitative, it allows to get the 3D imaging of the whole multi-material structure in a single reconstructed image. The proposed approach is based on the Dempster–Shafer evidence theory. X-ray computed tomography (dpeaa)DE-He213 Multi-material object (dpeaa)DE-He213 3D Imaging (dpeaa)DE-He213 Image reconstruction (dpeaa)DE-He213 Dempster–Shafer evidence theory (dpeaa)DE-He213 Doudet, Valerie Kaftandjian aut Enthalten in Journal of nondestructive evaluation Dordrecht [u.a.] : Springer Science + Business Media, 1980 41(2022), 3 vom: 12. Juli (DE-627)317859803 (DE-600)2017032-4 1573-4862 nnns volume:41 year:2022 number:3 day:12 month:07 https://dx.doi.org/10.1007/s10921-022-00883-0 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_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 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_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 41 2022 3 12 07 |
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Oujebbour, Fatima Zahra |
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image fusion based on evidence theory for multi-energy x-ray computed tomography |
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Image Fusion Based on Evidence Theory for Multi-Energy X-Ray Computed Tomography |
| abstract |
Abstract For diagnosis in industrial applications, X-Ray computed tomography (XCT) has proven its interest for various industrial applications where 3D imaging of complex shapes is required. However, it’s not possible to fully represent a multi-material object with a single XCT image. In such cases, valuable information can be revealed using multi-energy X-Ray computed tomography. This imaging technique has various advantages over standard XCT. Multi-energy XCT can either be done by using photon counting detectors in a single acquisition scan, or using energy integration detectors and several acquisition scans. In either case, several reconstructed images are obtained for each energy band. In the present study, a combination of projections acquired at different energy is done in such a way to provide the operator with a single XCT image where all the information is present. Although this information is qualitative, it allows to get the 3D imaging of the whole multi-material structure in a single reconstructed image. The proposed approach is based on the Dempster–Shafer evidence theory. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 |
| abstractGer |
Abstract For diagnosis in industrial applications, X-Ray computed tomography (XCT) has proven its interest for various industrial applications where 3D imaging of complex shapes is required. However, it’s not possible to fully represent a multi-material object with a single XCT image. In such cases, valuable information can be revealed using multi-energy X-Ray computed tomography. This imaging technique has various advantages over standard XCT. Multi-energy XCT can either be done by using photon counting detectors in a single acquisition scan, or using energy integration detectors and several acquisition scans. In either case, several reconstructed images are obtained for each energy band. In the present study, a combination of projections acquired at different energy is done in such a way to provide the operator with a single XCT image where all the information is present. Although this information is qualitative, it allows to get the 3D imaging of the whole multi-material structure in a single reconstructed image. The proposed approach is based on the Dempster–Shafer evidence theory. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 |
| abstract_unstemmed |
Abstract For diagnosis in industrial applications, X-Ray computed tomography (XCT) has proven its interest for various industrial applications where 3D imaging of complex shapes is required. However, it’s not possible to fully represent a multi-material object with a single XCT image. In such cases, valuable information can be revealed using multi-energy X-Ray computed tomography. This imaging technique has various advantages over standard XCT. Multi-energy XCT can either be done by using photon counting detectors in a single acquisition scan, or using energy integration detectors and several acquisition scans. In either case, several reconstructed images are obtained for each energy band. In the present study, a combination of projections acquired at different energy is done in such a way to provide the operator with a single XCT image where all the information is present. Although this information is qualitative, it allows to get the 3D imaging of the whole multi-material structure in a single reconstructed image. The proposed approach is based on the Dempster–Shafer evidence theory. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 |
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Image Fusion Based on Evidence Theory for Multi-Energy X-Ray Computed Tomography |
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