Adaptive registration of varying contrast-weighted images for improved tissue characterization (ARCTIC) : application to T1 mapping
Purpose: To propose and evaluate a novel nonrigid image registration approach for improved myocardial T1 mapping. Methods: Myocardial motion is estimated as global affine motion refined by a novel local nonrigid motion estimation algorithm. A variational framework is proposed, which simultaneously e...
Ausführliche Beschreibung
Autor*in: |
Roujol, Sébastien [verfasserIn] Weingärtner, Sebastian - 1991- [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
5 May 2014 |
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Anmerkung: |
Gesehen am 17.11.2017 Im Titelzusatz ist "1" tiefgestellt |
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Umfang: |
14 |
Übergeordnetes Werk: |
Enthalten in: Magnetic resonance in medicine - New York, NY [u.a.] : Wiley-Liss, 1984, 73(2015), 4, Seite 1469-1482 |
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Übergeordnetes Werk: |
volume:73 ; year:2015 ; number:4 ; pages:1469-1482 ; extent:14 |
Links: |
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DOI / URN: |
10.1002/mrm.25270 |
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Katalog-ID: |
1565476034 |
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245 | 1 | 0 | |a Adaptive registration of varying contrast-weighted images for improved tissue characterization (ARCTIC) |b application to T1 mapping |c Sébastien Roujol, Murilo Foppa, Sebastian Weingärtner, Warren J. Manning and Reza Nezafat |
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520 | |a Purpose: To propose and evaluate a novel nonrigid image registration approach for improved myocardial T1 mapping. Methods: Myocardial motion is estimated as global affine motion refined by a novel local nonrigid motion estimation algorithm. A variational framework is proposed, which simultaneously estimates motion field and intensity variations, and uses an additional regularization term to constrain the deformation field using automatic feature tracking. The method was evaluated in 29 patients by measuring the DICE similarity coefficient and the myocardial boundary error in short axis and four chamber data. Each image series was visually assessed as “no motion” or “with motion.” Overall T1 map quality and motion artifacts were assessed in the 85 T1 maps acquired in short axis view using a 4-point scale (1-nondiagnostic/severe motion artifact, 4-excellent/no motion artifact). Results: Increased DICE similarity coefficient (0.78 ± 0.14 to 0.87 ± 0.03, P < 0.001), reduced myocardial boundary error (1.29 ± 0.72 mm to 0.84 ± 0.20 mm, P < 0.001), improved overall T1 map quality (2.86 ± 1.04 to 3.49 ± 0.77, P < 0.001), and reduced T1 map motion artifacts (2.51 ± 0.84 to 3.61 ± 0.64, P < 0.001) were obtained after motion correction of “with motion” data (∼56% of data). Conclusions: The proposed nonrigid registration approach reduces the respiratory-induced motion that occurs during breath-hold T1 mapping, and significantly improves T1 map quality. | ||
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5 May 2014 |
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2015 |
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10.1002/mrm.25270 doi (DE-627)1565476034 (DE-576)49547603X (DE-599)BSZ49547603X (OCoLC)1340982123 DE-627 ger DE-627 rda eng Roujol, Sébastien verfasserin (DE-588)1144662052 (DE-627)1004957874 (DE-576)495475998 aut Adaptive registration of varying contrast-weighted images for improved tissue characterization (ARCTIC) application to T1 mapping Sébastien Roujol, Murilo Foppa, Sebastian Weingärtner, Warren J. Manning and Reza Nezafat 5 May 2014 14 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Gesehen am 17.11.2017 Im Titelzusatz ist "1" tiefgestellt Purpose: To propose and evaluate a novel nonrigid image registration approach for improved myocardial T1 mapping. Methods: Myocardial motion is estimated as global affine motion refined by a novel local nonrigid motion estimation algorithm. A variational framework is proposed, which simultaneously estimates motion field and intensity variations, and uses an additional regularization term to constrain the deformation field using automatic feature tracking. The method was evaluated in 29 patients by measuring the DICE similarity coefficient and the myocardial boundary error in short axis and four chamber data. Each image series was visually assessed as “no motion” or “with motion.” Overall T1 map quality and motion artifacts were assessed in the 85 T1 maps acquired in short axis view using a 4-point scale (1-nondiagnostic/severe motion artifact, 4-excellent/no motion artifact). Results: Increased DICE similarity coefficient (0.78 ± 0.14 to 0.87 ± 0.03, P < 0.001), reduced myocardial boundary error (1.29 ± 0.72 mm to 0.84 ± 0.20 mm, P < 0.001), improved overall T1 map quality (2.86 ± 1.04 to 3.49 ± 0.77, P < 0.001), and reduced T1 map motion artifacts (2.51 ± 0.84 to 3.61 ± 0.64, P < 0.001) were obtained after motion correction of “with motion” data (∼56% of data). Conclusions: The proposed nonrigid registration approach reduces the respiratory-induced motion that occurs during breath-hold T1 mapping, and significantly improves T1 map quality. 2014 image registration motion correction motion estimation myocardial tissue characterization T1 mapping Weingärtner, Sebastian 1991- verfasserin (DE-588)1051891507 (DE-627)786975199 (DE-576)407522883 aut Enthalten in Magnetic resonance in medicine New York, NY [u.a.] : Wiley-Liss, 1984 73(2015), 4, Seite 1469-1482 Online-Ressource (DE-627)303257040 (DE-600)1493786-4 (DE-576)096290455 1522-2594 nnns volume:73 year:2015 number:4 pages:1469-1482 extent:14 http://dx.doi.org/10.1002/mrm.25270 Verlag Resolving-System Volltext http://onlinelibrary.wiley.com.ezproxy.medma.uni-heidelberg.de/doi/10.1002/mrm.25270/abstract Verlag Volltext GBV_USEFLAG_U GBV_ILN_2013 ISIL_DE-16-250 SYSFLAG_1 GBV_KXP SSG-OLC-PHA 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_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_266 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 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_2018 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_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 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_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 73 2015 4 1469-1482 14 2013 01 DE-16-250 2987438419 00 --%%-- --%%-- --%%-- --%%-- l01 17-11-17 2013 01 DE-16-250 00 s hd2015 2013 01 DE-16-250 01 s (DE-627)1410508463 wissenschaftlicher Artikel (Zeitschrift) 2013 01 DE-16-250 02 s per_5 2013 01 DE-16-250 03 s s_14 2013 01 DE-16-250 04 p (DE-627)1477523898 Weingärtner, Sebastian 2013 01 DE-16-250 04 k (DE-627)1430735864 Lehrstuhl für Computerunterstützte Klinische Medizin (CKM) 2013 01 DE-16-250 04 s (DE-627)1410501914 Verfasser 2013 01 DE-16-250 04 s pos_3 |
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10.1002/mrm.25270 doi (DE-627)1565476034 (DE-576)49547603X (DE-599)BSZ49547603X (OCoLC)1340982123 DE-627 ger DE-627 rda eng Roujol, Sébastien verfasserin (DE-588)1144662052 (DE-627)1004957874 (DE-576)495475998 aut Adaptive registration of varying contrast-weighted images for improved tissue characterization (ARCTIC) application to T1 mapping Sébastien Roujol, Murilo Foppa, Sebastian Weingärtner, Warren J. Manning and Reza Nezafat 5 May 2014 14 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Gesehen am 17.11.2017 Im Titelzusatz ist "1" tiefgestellt Purpose: To propose and evaluate a novel nonrigid image registration approach for improved myocardial T1 mapping. Methods: Myocardial motion is estimated as global affine motion refined by a novel local nonrigid motion estimation algorithm. A variational framework is proposed, which simultaneously estimates motion field and intensity variations, and uses an additional regularization term to constrain the deformation field using automatic feature tracking. The method was evaluated in 29 patients by measuring the DICE similarity coefficient and the myocardial boundary error in short axis and four chamber data. Each image series was visually assessed as “no motion” or “with motion.” Overall T1 map quality and motion artifacts were assessed in the 85 T1 maps acquired in short axis view using a 4-point scale (1-nondiagnostic/severe motion artifact, 4-excellent/no motion artifact). Results: Increased DICE similarity coefficient (0.78 ± 0.14 to 0.87 ± 0.03, P < 0.001), reduced myocardial boundary error (1.29 ± 0.72 mm to 0.84 ± 0.20 mm, P < 0.001), improved overall T1 map quality (2.86 ± 1.04 to 3.49 ± 0.77, P < 0.001), and reduced T1 map motion artifacts (2.51 ± 0.84 to 3.61 ± 0.64, P < 0.001) were obtained after motion correction of “with motion” data (∼56% of data). Conclusions: The proposed nonrigid registration approach reduces the respiratory-induced motion that occurs during breath-hold T1 mapping, and significantly improves T1 map quality. 2014 image registration motion correction motion estimation myocardial tissue characterization T1 mapping Weingärtner, Sebastian 1991- verfasserin (DE-588)1051891507 (DE-627)786975199 (DE-576)407522883 aut Enthalten in Magnetic resonance in medicine New York, NY [u.a.] : Wiley-Liss, 1984 73(2015), 4, Seite 1469-1482 Online-Ressource (DE-627)303257040 (DE-600)1493786-4 (DE-576)096290455 1522-2594 nnns volume:73 year:2015 number:4 pages:1469-1482 extent:14 http://dx.doi.org/10.1002/mrm.25270 Verlag Resolving-System Volltext http://onlinelibrary.wiley.com.ezproxy.medma.uni-heidelberg.de/doi/10.1002/mrm.25270/abstract Verlag Volltext GBV_USEFLAG_U GBV_ILN_2013 ISIL_DE-16-250 SYSFLAG_1 GBV_KXP SSG-OLC-PHA 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_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_266 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 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_2018 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_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 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_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 73 2015 4 1469-1482 14 2013 01 DE-16-250 2987438419 00 --%%-- --%%-- --%%-- --%%-- l01 17-11-17 2013 01 DE-16-250 00 s hd2015 2013 01 DE-16-250 01 s (DE-627)1410508463 wissenschaftlicher Artikel (Zeitschrift) 2013 01 DE-16-250 02 s per_5 2013 01 DE-16-250 03 s s_14 2013 01 DE-16-250 04 p (DE-627)1477523898 Weingärtner, Sebastian 2013 01 DE-16-250 04 k (DE-627)1430735864 Lehrstuhl für Computerunterstützte Klinische Medizin (CKM) 2013 01 DE-16-250 04 s (DE-627)1410501914 Verfasser 2013 01 DE-16-250 04 s pos_3 |
allfields_unstemmed |
10.1002/mrm.25270 doi (DE-627)1565476034 (DE-576)49547603X (DE-599)BSZ49547603X (OCoLC)1340982123 DE-627 ger DE-627 rda eng Roujol, Sébastien verfasserin (DE-588)1144662052 (DE-627)1004957874 (DE-576)495475998 aut Adaptive registration of varying contrast-weighted images for improved tissue characterization (ARCTIC) application to T1 mapping Sébastien Roujol, Murilo Foppa, Sebastian Weingärtner, Warren J. Manning and Reza Nezafat 5 May 2014 14 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Gesehen am 17.11.2017 Im Titelzusatz ist "1" tiefgestellt Purpose: To propose and evaluate a novel nonrigid image registration approach for improved myocardial T1 mapping. Methods: Myocardial motion is estimated as global affine motion refined by a novel local nonrigid motion estimation algorithm. A variational framework is proposed, which simultaneously estimates motion field and intensity variations, and uses an additional regularization term to constrain the deformation field using automatic feature tracking. The method was evaluated in 29 patients by measuring the DICE similarity coefficient and the myocardial boundary error in short axis and four chamber data. Each image series was visually assessed as “no motion” or “with motion.” Overall T1 map quality and motion artifacts were assessed in the 85 T1 maps acquired in short axis view using a 4-point scale (1-nondiagnostic/severe motion artifact, 4-excellent/no motion artifact). Results: Increased DICE similarity coefficient (0.78 ± 0.14 to 0.87 ± 0.03, P < 0.001), reduced myocardial boundary error (1.29 ± 0.72 mm to 0.84 ± 0.20 mm, P < 0.001), improved overall T1 map quality (2.86 ± 1.04 to 3.49 ± 0.77, P < 0.001), and reduced T1 map motion artifacts (2.51 ± 0.84 to 3.61 ± 0.64, P < 0.001) were obtained after motion correction of “with motion” data (∼56% of data). Conclusions: The proposed nonrigid registration approach reduces the respiratory-induced motion that occurs during breath-hold T1 mapping, and significantly improves T1 map quality. 2014 image registration motion correction motion estimation myocardial tissue characterization T1 mapping Weingärtner, Sebastian 1991- verfasserin (DE-588)1051891507 (DE-627)786975199 (DE-576)407522883 aut Enthalten in Magnetic resonance in medicine New York, NY [u.a.] : Wiley-Liss, 1984 73(2015), 4, Seite 1469-1482 Online-Ressource (DE-627)303257040 (DE-600)1493786-4 (DE-576)096290455 1522-2594 nnns volume:73 year:2015 number:4 pages:1469-1482 extent:14 http://dx.doi.org/10.1002/mrm.25270 Verlag Resolving-System Volltext http://onlinelibrary.wiley.com.ezproxy.medma.uni-heidelberg.de/doi/10.1002/mrm.25270/abstract Verlag Volltext GBV_USEFLAG_U GBV_ILN_2013 ISIL_DE-16-250 SYSFLAG_1 GBV_KXP SSG-OLC-PHA 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_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_266 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 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_2018 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_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 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_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 73 2015 4 1469-1482 14 2013 01 DE-16-250 2987438419 00 --%%-- --%%-- --%%-- --%%-- l01 17-11-17 2013 01 DE-16-250 00 s hd2015 2013 01 DE-16-250 01 s (DE-627)1410508463 wissenschaftlicher Artikel (Zeitschrift) 2013 01 DE-16-250 02 s per_5 2013 01 DE-16-250 03 s s_14 2013 01 DE-16-250 04 p (DE-627)1477523898 Weingärtner, Sebastian 2013 01 DE-16-250 04 k (DE-627)1430735864 Lehrstuhl für Computerunterstützte Klinische Medizin (CKM) 2013 01 DE-16-250 04 s (DE-627)1410501914 Verfasser 2013 01 DE-16-250 04 s pos_3 |
allfieldsGer |
10.1002/mrm.25270 doi (DE-627)1565476034 (DE-576)49547603X (DE-599)BSZ49547603X (OCoLC)1340982123 DE-627 ger DE-627 rda eng Roujol, Sébastien verfasserin (DE-588)1144662052 (DE-627)1004957874 (DE-576)495475998 aut Adaptive registration of varying contrast-weighted images for improved tissue characterization (ARCTIC) application to T1 mapping Sébastien Roujol, Murilo Foppa, Sebastian Weingärtner, Warren J. Manning and Reza Nezafat 5 May 2014 14 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Gesehen am 17.11.2017 Im Titelzusatz ist "1" tiefgestellt Purpose: To propose and evaluate a novel nonrigid image registration approach for improved myocardial T1 mapping. Methods: Myocardial motion is estimated as global affine motion refined by a novel local nonrigid motion estimation algorithm. A variational framework is proposed, which simultaneously estimates motion field and intensity variations, and uses an additional regularization term to constrain the deformation field using automatic feature tracking. The method was evaluated in 29 patients by measuring the DICE similarity coefficient and the myocardial boundary error in short axis and four chamber data. Each image series was visually assessed as “no motion” or “with motion.” Overall T1 map quality and motion artifacts were assessed in the 85 T1 maps acquired in short axis view using a 4-point scale (1-nondiagnostic/severe motion artifact, 4-excellent/no motion artifact). Results: Increased DICE similarity coefficient (0.78 ± 0.14 to 0.87 ± 0.03, P < 0.001), reduced myocardial boundary error (1.29 ± 0.72 mm to 0.84 ± 0.20 mm, P < 0.001), improved overall T1 map quality (2.86 ± 1.04 to 3.49 ± 0.77, P < 0.001), and reduced T1 map motion artifacts (2.51 ± 0.84 to 3.61 ± 0.64, P < 0.001) were obtained after motion correction of “with motion” data (∼56% of data). Conclusions: The proposed nonrigid registration approach reduces the respiratory-induced motion that occurs during breath-hold T1 mapping, and significantly improves T1 map quality. 2014 image registration motion correction motion estimation myocardial tissue characterization T1 mapping Weingärtner, Sebastian 1991- verfasserin (DE-588)1051891507 (DE-627)786975199 (DE-576)407522883 aut Enthalten in Magnetic resonance in medicine New York, NY [u.a.] : Wiley-Liss, 1984 73(2015), 4, Seite 1469-1482 Online-Ressource (DE-627)303257040 (DE-600)1493786-4 (DE-576)096290455 1522-2594 nnns volume:73 year:2015 number:4 pages:1469-1482 extent:14 http://dx.doi.org/10.1002/mrm.25270 Verlag Resolving-System Volltext http://onlinelibrary.wiley.com.ezproxy.medma.uni-heidelberg.de/doi/10.1002/mrm.25270/abstract Verlag Volltext GBV_USEFLAG_U GBV_ILN_2013 ISIL_DE-16-250 SYSFLAG_1 GBV_KXP SSG-OLC-PHA 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_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_266 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 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_2018 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_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 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_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 73 2015 4 1469-1482 14 2013 01 DE-16-250 2987438419 00 --%%-- --%%-- --%%-- --%%-- l01 17-11-17 2013 01 DE-16-250 00 s hd2015 2013 01 DE-16-250 01 s (DE-627)1410508463 wissenschaftlicher Artikel (Zeitschrift) 2013 01 DE-16-250 02 s per_5 2013 01 DE-16-250 03 s s_14 2013 01 DE-16-250 04 p (DE-627)1477523898 Weingärtner, Sebastian 2013 01 DE-16-250 04 k (DE-627)1430735864 Lehrstuhl für Computerunterstützte Klinische Medizin (CKM) 2013 01 DE-16-250 04 s (DE-627)1410501914 Verfasser 2013 01 DE-16-250 04 s pos_3 |
allfieldsSound |
10.1002/mrm.25270 doi (DE-627)1565476034 (DE-576)49547603X (DE-599)BSZ49547603X (OCoLC)1340982123 DE-627 ger DE-627 rda eng Roujol, Sébastien verfasserin (DE-588)1144662052 (DE-627)1004957874 (DE-576)495475998 aut Adaptive registration of varying contrast-weighted images for improved tissue characterization (ARCTIC) application to T1 mapping Sébastien Roujol, Murilo Foppa, Sebastian Weingärtner, Warren J. Manning and Reza Nezafat 5 May 2014 14 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Gesehen am 17.11.2017 Im Titelzusatz ist "1" tiefgestellt Purpose: To propose and evaluate a novel nonrigid image registration approach for improved myocardial T1 mapping. Methods: Myocardial motion is estimated as global affine motion refined by a novel local nonrigid motion estimation algorithm. A variational framework is proposed, which simultaneously estimates motion field and intensity variations, and uses an additional regularization term to constrain the deformation field using automatic feature tracking. The method was evaluated in 29 patients by measuring the DICE similarity coefficient and the myocardial boundary error in short axis and four chamber data. Each image series was visually assessed as “no motion” or “with motion.” Overall T1 map quality and motion artifacts were assessed in the 85 T1 maps acquired in short axis view using a 4-point scale (1-nondiagnostic/severe motion artifact, 4-excellent/no motion artifact). Results: Increased DICE similarity coefficient (0.78 ± 0.14 to 0.87 ± 0.03, P < 0.001), reduced myocardial boundary error (1.29 ± 0.72 mm to 0.84 ± 0.20 mm, P < 0.001), improved overall T1 map quality (2.86 ± 1.04 to 3.49 ± 0.77, P < 0.001), and reduced T1 map motion artifacts (2.51 ± 0.84 to 3.61 ± 0.64, P < 0.001) were obtained after motion correction of “with motion” data (∼56% of data). Conclusions: The proposed nonrigid registration approach reduces the respiratory-induced motion that occurs during breath-hold T1 mapping, and significantly improves T1 map quality. 2014 image registration motion correction motion estimation myocardial tissue characterization T1 mapping Weingärtner, Sebastian 1991- verfasserin (DE-588)1051891507 (DE-627)786975199 (DE-576)407522883 aut Enthalten in Magnetic resonance in medicine New York, NY [u.a.] : Wiley-Liss, 1984 73(2015), 4, Seite 1469-1482 Online-Ressource (DE-627)303257040 (DE-600)1493786-4 (DE-576)096290455 1522-2594 nnns volume:73 year:2015 number:4 pages:1469-1482 extent:14 http://dx.doi.org/10.1002/mrm.25270 Verlag Resolving-System Volltext http://onlinelibrary.wiley.com.ezproxy.medma.uni-heidelberg.de/doi/10.1002/mrm.25270/abstract Verlag Volltext GBV_USEFLAG_U GBV_ILN_2013 ISIL_DE-16-250 SYSFLAG_1 GBV_KXP SSG-OLC-PHA 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_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_266 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 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_2018 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_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 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_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 73 2015 4 1469-1482 14 2013 01 DE-16-250 2987438419 00 --%%-- --%%-- --%%-- --%%-- l01 17-11-17 2013 01 DE-16-250 00 s hd2015 2013 01 DE-16-250 01 s (DE-627)1410508463 wissenschaftlicher Artikel (Zeitschrift) 2013 01 DE-16-250 02 s per_5 2013 01 DE-16-250 03 s s_14 2013 01 DE-16-250 04 p (DE-627)1477523898 Weingärtner, Sebastian 2013 01 DE-16-250 04 k (DE-627)1430735864 Lehrstuhl für Computerunterstützte Klinische Medizin (CKM) 2013 01 DE-16-250 04 s (DE-627)1410501914 Verfasser 2013 01 DE-16-250 04 s pos_3 |
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Adaptive registration of varying contrast-weighted images for improved tissue characterization (ARCTIC) application to T1 mapping |
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Adaptive registration of varying contrast-weighted images for improved tissue characterization (ARCTIC) application to T1 mapping Sébastien Roujol, Murilo Foppa, Sebastian Weingärtner, Warren J. Manning and Reza Nezafat |
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adaptive registration of varying contrast-weighted images for improved tissue characterization (arctic)application to t1 mapping |
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Adaptive registration of varying contrast-weighted images for improved tissue characterization (ARCTIC) application to T1 mapping |
abstract |
Purpose: To propose and evaluate a novel nonrigid image registration approach for improved myocardial T1 mapping. Methods: Myocardial motion is estimated as global affine motion refined by a novel local nonrigid motion estimation algorithm. A variational framework is proposed, which simultaneously estimates motion field and intensity variations, and uses an additional regularization term to constrain the deformation field using automatic feature tracking. The method was evaluated in 29 patients by measuring the DICE similarity coefficient and the myocardial boundary error in short axis and four chamber data. Each image series was visually assessed as “no motion” or “with motion.” Overall T1 map quality and motion artifacts were assessed in the 85 T1 maps acquired in short axis view using a 4-point scale (1-nondiagnostic/severe motion artifact, 4-excellent/no motion artifact). Results: Increased DICE similarity coefficient (0.78 ± 0.14 to 0.87 ± 0.03, P < 0.001), reduced myocardial boundary error (1.29 ± 0.72 mm to 0.84 ± 0.20 mm, P < 0.001), improved overall T1 map quality (2.86 ± 1.04 to 3.49 ± 0.77, P < 0.001), and reduced T1 map motion artifacts (2.51 ± 0.84 to 3.61 ± 0.64, P < 0.001) were obtained after motion correction of “with motion” data (∼56% of data). Conclusions: The proposed nonrigid registration approach reduces the respiratory-induced motion that occurs during breath-hold T1 mapping, and significantly improves T1 map quality. Gesehen am 17.11.2017 Im Titelzusatz ist "1" tiefgestellt |
abstractGer |
Purpose: To propose and evaluate a novel nonrigid image registration approach for improved myocardial T1 mapping. Methods: Myocardial motion is estimated as global affine motion refined by a novel local nonrigid motion estimation algorithm. A variational framework is proposed, which simultaneously estimates motion field and intensity variations, and uses an additional regularization term to constrain the deformation field using automatic feature tracking. The method was evaluated in 29 patients by measuring the DICE similarity coefficient and the myocardial boundary error in short axis and four chamber data. Each image series was visually assessed as “no motion” or “with motion.” Overall T1 map quality and motion artifacts were assessed in the 85 T1 maps acquired in short axis view using a 4-point scale (1-nondiagnostic/severe motion artifact, 4-excellent/no motion artifact). Results: Increased DICE similarity coefficient (0.78 ± 0.14 to 0.87 ± 0.03, P < 0.001), reduced myocardial boundary error (1.29 ± 0.72 mm to 0.84 ± 0.20 mm, P < 0.001), improved overall T1 map quality (2.86 ± 1.04 to 3.49 ± 0.77, P < 0.001), and reduced T1 map motion artifacts (2.51 ± 0.84 to 3.61 ± 0.64, P < 0.001) were obtained after motion correction of “with motion” data (∼56% of data). Conclusions: The proposed nonrigid registration approach reduces the respiratory-induced motion that occurs during breath-hold T1 mapping, and significantly improves T1 map quality. Gesehen am 17.11.2017 Im Titelzusatz ist "1" tiefgestellt |
abstract_unstemmed |
Purpose: To propose and evaluate a novel nonrigid image registration approach for improved myocardial T1 mapping. Methods: Myocardial motion is estimated as global affine motion refined by a novel local nonrigid motion estimation algorithm. A variational framework is proposed, which simultaneously estimates motion field and intensity variations, and uses an additional regularization term to constrain the deformation field using automatic feature tracking. The method was evaluated in 29 patients by measuring the DICE similarity coefficient and the myocardial boundary error in short axis and four chamber data. Each image series was visually assessed as “no motion” or “with motion.” Overall T1 map quality and motion artifacts were assessed in the 85 T1 maps acquired in short axis view using a 4-point scale (1-nondiagnostic/severe motion artifact, 4-excellent/no motion artifact). Results: Increased DICE similarity coefficient (0.78 ± 0.14 to 0.87 ± 0.03, P < 0.001), reduced myocardial boundary error (1.29 ± 0.72 mm to 0.84 ± 0.20 mm, P < 0.001), improved overall T1 map quality (2.86 ± 1.04 to 3.49 ± 0.77, P < 0.001), and reduced T1 map motion artifacts (2.51 ± 0.84 to 3.61 ± 0.64, P < 0.001) were obtained after motion correction of “with motion” data (∼56% of data). Conclusions: The proposed nonrigid registration approach reduces the respiratory-induced motion that occurs during breath-hold T1 mapping, and significantly improves T1 map quality. Gesehen am 17.11.2017 Im Titelzusatz ist "1" tiefgestellt |
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container_issue |
4 |
title_short |
Adaptive registration of varying contrast-weighted images for improved tissue characterization (ARCTIC) |
url |
http://dx.doi.org/10.1002/mrm.25270 http://onlinelibrary.wiley.com.ezproxy.medma.uni-heidelberg.de/doi/10.1002/mrm.25270/abstract |
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up_date |
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