Utility of real-time prospective motion correction (PROMO) for segmentation of cerebral cortex on 3D T1-weighted imaging: Voxel-based morphometry analysis for uncooperative patients
Objective To assess the utility of the motion correction method with prospective motion correction (PROMO) in a voxel-based morphometry (VBM) analysis for ‘uncooperative’ patient populations. Methods High-resolution 3D T1-weighted imaging both with and without PROMO were performed in 33 uncooperativ...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Igata, Natsuki [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2017 |
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| Schlagwörter: |
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| Anmerkung: |
© European Society of Radiology 2017 |
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| Übergeordnetes Werk: |
Enthalten in: European radiology - Berlin : Springer, 1991, 27(2017), 8 vom: 23. Jan., Seite 3554-3562 |
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| Übergeordnetes Werk: |
volume:27 ; year:2017 ; number:8 ; day:23 ; month:01 ; pages:3554-3562 |
| Links: |
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| DOI / URN: |
10.1007/s00330-016-4730-7 |
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| Katalog-ID: |
SPR004031741 |
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| 100 | 1 | |a Igata, Natsuki |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Utility of real-time prospective motion correction (PROMO) for segmentation of cerebral cortex on 3D T1-weighted imaging: Voxel-based morphometry analysis for uncooperative patients |
| 264 | 1 | |c 2017 | |
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| 520 | |a Objective To assess the utility of the motion correction method with prospective motion correction (PROMO) in a voxel-based morphometry (VBM) analysis for ‘uncooperative’ patient populations. Methods High-resolution 3D T1-weighted imaging both with and without PROMO were performed in 33 uncooperative patients with Parkinson's disease (n = 11) or dementia (n = 22). We compared the grey matter (GM) volumes and cortical thickness between the scans with and without PROMO. Results For the mean total GM volume with the VBM analysis, the scan without PROMO showed a significantly smaller volume than that with PROMO (p < 0.05), which was caused by segmentation problems due to motion during acquisition. The whole-brain VBM analysis showed significant GM volume reductions in some regions in the scans without PROMO (familywise error corrected p < 0.05). In the cortical thickness analysis, the scans without PROMO also showed decreased cortical thickness compared to the scan with PROMO (p < 0.05). Conclusion Our results with the uncooperative patients indicate that the use of PROMO can reduce misclassification during segmentation of the VBM analyses, although it may not prevent GM volume reduction. Key Points • Motion artifacts pose significant problems for VBM analyses. • PROMO correction can reduce the motion artifacts in high-resolution 3D T1WI. • The use of PROMO may improve the precision of VBM analyses. | ||
| 650 | 4 | |a Prospective motion correction |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Voxel-based morphometry |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Motion artifacts |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Extended Kalman Filter (EKF) motion estimates |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Parkinson’s disease |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Kakeda, Shingo |4 aut | |
| 700 | 1 | |a Watanabe, Keita |4 aut | |
| 700 | 1 | |a Nozaki, Atsushi |4 aut | |
| 700 | 1 | |a Rettmann, Dan |4 aut | |
| 700 | 1 | |a Narimatsu, Hidekuni |4 aut | |
| 700 | 1 | |a Ide, Satoru |4 aut | |
| 700 | 1 | |a Abe, Osamu |4 aut | |
| 700 | 1 | |a Korogi, Yukunori |4 aut | |
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10.1007/s00330-016-4730-7 doi (DE-627)SPR004031741 (SPR)s00330-016-4730-7-e DE-627 ger DE-627 rakwb eng Igata, Natsuki verfasserin aut Utility of real-time prospective motion correction (PROMO) for segmentation of cerebral cortex on 3D T1-weighted imaging: Voxel-based morphometry analysis for uncooperative patients 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © European Society of Radiology 2017 Objective To assess the utility of the motion correction method with prospective motion correction (PROMO) in a voxel-based morphometry (VBM) analysis for ‘uncooperative’ patient populations. Methods High-resolution 3D T1-weighted imaging both with and without PROMO were performed in 33 uncooperative patients with Parkinson's disease (n = 11) or dementia (n = 22). We compared the grey matter (GM) volumes and cortical thickness between the scans with and without PROMO. Results For the mean total GM volume with the VBM analysis, the scan without PROMO showed a significantly smaller volume than that with PROMO (p < 0.05), which was caused by segmentation problems due to motion during acquisition. The whole-brain VBM analysis showed significant GM volume reductions in some regions in the scans without PROMO (familywise error corrected p < 0.05). In the cortical thickness analysis, the scans without PROMO also showed decreased cortical thickness compared to the scan with PROMO (p < 0.05). Conclusion Our results with the uncooperative patients indicate that the use of PROMO can reduce misclassification during segmentation of the VBM analyses, although it may not prevent GM volume reduction. Key Points • Motion artifacts pose significant problems for VBM analyses. • PROMO correction can reduce the motion artifacts in high-resolution 3D T1WI. • The use of PROMO may improve the precision of VBM analyses. Prospective motion correction (dpeaa)DE-He213 Voxel-based morphometry (dpeaa)DE-He213 Motion artifacts (dpeaa)DE-He213 Extended Kalman Filter (EKF) motion estimates (dpeaa)DE-He213 Parkinson’s disease (dpeaa)DE-He213 Kakeda, Shingo aut Watanabe, Keita aut Nozaki, Atsushi aut Rettmann, Dan aut Narimatsu, Hidekuni aut Ide, Satoru aut Abe, Osamu aut Korogi, Yukunori aut Enthalten in European radiology Berlin : Springer, 1991 27(2017), 8 vom: 23. Jan., Seite 3554-3562 (DE-627)268757526 (DE-600)1472718-3 1432-1084 nnns volume:27 year:2017 number:8 day:23 month:01 pages:3554-3562 https://dx.doi.org/10.1007/s00330-016-4730-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_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_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 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_2446 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 27 2017 8 23 01 3554-3562 |
| spelling |
10.1007/s00330-016-4730-7 doi (DE-627)SPR004031741 (SPR)s00330-016-4730-7-e DE-627 ger DE-627 rakwb eng Igata, Natsuki verfasserin aut Utility of real-time prospective motion correction (PROMO) for segmentation of cerebral cortex on 3D T1-weighted imaging: Voxel-based morphometry analysis for uncooperative patients 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © European Society of Radiology 2017 Objective To assess the utility of the motion correction method with prospective motion correction (PROMO) in a voxel-based morphometry (VBM) analysis for ‘uncooperative’ patient populations. Methods High-resolution 3D T1-weighted imaging both with and without PROMO were performed in 33 uncooperative patients with Parkinson's disease (n = 11) or dementia (n = 22). We compared the grey matter (GM) volumes and cortical thickness between the scans with and without PROMO. Results For the mean total GM volume with the VBM analysis, the scan without PROMO showed a significantly smaller volume than that with PROMO (p < 0.05), which was caused by segmentation problems due to motion during acquisition. The whole-brain VBM analysis showed significant GM volume reductions in some regions in the scans without PROMO (familywise error corrected p < 0.05). In the cortical thickness analysis, the scans without PROMO also showed decreased cortical thickness compared to the scan with PROMO (p < 0.05). Conclusion Our results with the uncooperative patients indicate that the use of PROMO can reduce misclassification during segmentation of the VBM analyses, although it may not prevent GM volume reduction. Key Points • Motion artifacts pose significant problems for VBM analyses. • PROMO correction can reduce the motion artifacts in high-resolution 3D T1WI. • The use of PROMO may improve the precision of VBM analyses. Prospective motion correction (dpeaa)DE-He213 Voxel-based morphometry (dpeaa)DE-He213 Motion artifacts (dpeaa)DE-He213 Extended Kalman Filter (EKF) motion estimates (dpeaa)DE-He213 Parkinson’s disease (dpeaa)DE-He213 Kakeda, Shingo aut Watanabe, Keita aut Nozaki, Atsushi aut Rettmann, Dan aut Narimatsu, Hidekuni aut Ide, Satoru aut Abe, Osamu aut Korogi, Yukunori aut Enthalten in European radiology Berlin : Springer, 1991 27(2017), 8 vom: 23. Jan., Seite 3554-3562 (DE-627)268757526 (DE-600)1472718-3 1432-1084 nnns volume:27 year:2017 number:8 day:23 month:01 pages:3554-3562 https://dx.doi.org/10.1007/s00330-016-4730-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_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_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 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_2446 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 27 2017 8 23 01 3554-3562 |
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10.1007/s00330-016-4730-7 doi (DE-627)SPR004031741 (SPR)s00330-016-4730-7-e DE-627 ger DE-627 rakwb eng Igata, Natsuki verfasserin aut Utility of real-time prospective motion correction (PROMO) for segmentation of cerebral cortex on 3D T1-weighted imaging: Voxel-based morphometry analysis for uncooperative patients 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © European Society of Radiology 2017 Objective To assess the utility of the motion correction method with prospective motion correction (PROMO) in a voxel-based morphometry (VBM) analysis for ‘uncooperative’ patient populations. Methods High-resolution 3D T1-weighted imaging both with and without PROMO were performed in 33 uncooperative patients with Parkinson's disease (n = 11) or dementia (n = 22). We compared the grey matter (GM) volumes and cortical thickness between the scans with and without PROMO. Results For the mean total GM volume with the VBM analysis, the scan without PROMO showed a significantly smaller volume than that with PROMO (p < 0.05), which was caused by segmentation problems due to motion during acquisition. The whole-brain VBM analysis showed significant GM volume reductions in some regions in the scans without PROMO (familywise error corrected p < 0.05). In the cortical thickness analysis, the scans without PROMO also showed decreased cortical thickness compared to the scan with PROMO (p < 0.05). Conclusion Our results with the uncooperative patients indicate that the use of PROMO can reduce misclassification during segmentation of the VBM analyses, although it may not prevent GM volume reduction. Key Points • Motion artifacts pose significant problems for VBM analyses. • PROMO correction can reduce the motion artifacts in high-resolution 3D T1WI. • The use of PROMO may improve the precision of VBM analyses. Prospective motion correction (dpeaa)DE-He213 Voxel-based morphometry (dpeaa)DE-He213 Motion artifacts (dpeaa)DE-He213 Extended Kalman Filter (EKF) motion estimates (dpeaa)DE-He213 Parkinson’s disease (dpeaa)DE-He213 Kakeda, Shingo aut Watanabe, Keita aut Nozaki, Atsushi aut Rettmann, Dan aut Narimatsu, Hidekuni aut Ide, Satoru aut Abe, Osamu aut Korogi, Yukunori aut Enthalten in European radiology Berlin : Springer, 1991 27(2017), 8 vom: 23. Jan., Seite 3554-3562 (DE-627)268757526 (DE-600)1472718-3 1432-1084 nnns volume:27 year:2017 number:8 day:23 month:01 pages:3554-3562 https://dx.doi.org/10.1007/s00330-016-4730-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_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_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 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_2446 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 27 2017 8 23 01 3554-3562 |
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10.1007/s00330-016-4730-7 doi (DE-627)SPR004031741 (SPR)s00330-016-4730-7-e DE-627 ger DE-627 rakwb eng Igata, Natsuki verfasserin aut Utility of real-time prospective motion correction (PROMO) for segmentation of cerebral cortex on 3D T1-weighted imaging: Voxel-based morphometry analysis for uncooperative patients 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © European Society of Radiology 2017 Objective To assess the utility of the motion correction method with prospective motion correction (PROMO) in a voxel-based morphometry (VBM) analysis for ‘uncooperative’ patient populations. Methods High-resolution 3D T1-weighted imaging both with and without PROMO were performed in 33 uncooperative patients with Parkinson's disease (n = 11) or dementia (n = 22). We compared the grey matter (GM) volumes and cortical thickness between the scans with and without PROMO. Results For the mean total GM volume with the VBM analysis, the scan without PROMO showed a significantly smaller volume than that with PROMO (p < 0.05), which was caused by segmentation problems due to motion during acquisition. The whole-brain VBM analysis showed significant GM volume reductions in some regions in the scans without PROMO (familywise error corrected p < 0.05). In the cortical thickness analysis, the scans without PROMO also showed decreased cortical thickness compared to the scan with PROMO (p < 0.05). Conclusion Our results with the uncooperative patients indicate that the use of PROMO can reduce misclassification during segmentation of the VBM analyses, although it may not prevent GM volume reduction. Key Points • Motion artifacts pose significant problems for VBM analyses. • PROMO correction can reduce the motion artifacts in high-resolution 3D T1WI. • The use of PROMO may improve the precision of VBM analyses. Prospective motion correction (dpeaa)DE-He213 Voxel-based morphometry (dpeaa)DE-He213 Motion artifacts (dpeaa)DE-He213 Extended Kalman Filter (EKF) motion estimates (dpeaa)DE-He213 Parkinson’s disease (dpeaa)DE-He213 Kakeda, Shingo aut Watanabe, Keita aut Nozaki, Atsushi aut Rettmann, Dan aut Narimatsu, Hidekuni aut Ide, Satoru aut Abe, Osamu aut Korogi, Yukunori aut Enthalten in European radiology Berlin : Springer, 1991 27(2017), 8 vom: 23. Jan., Seite 3554-3562 (DE-627)268757526 (DE-600)1472718-3 1432-1084 nnns volume:27 year:2017 number:8 day:23 month:01 pages:3554-3562 https://dx.doi.org/10.1007/s00330-016-4730-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_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_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 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_2446 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 27 2017 8 23 01 3554-3562 |
| allfieldsSound |
10.1007/s00330-016-4730-7 doi (DE-627)SPR004031741 (SPR)s00330-016-4730-7-e DE-627 ger DE-627 rakwb eng Igata, Natsuki verfasserin aut Utility of real-time prospective motion correction (PROMO) for segmentation of cerebral cortex on 3D T1-weighted imaging: Voxel-based morphometry analysis for uncooperative patients 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © European Society of Radiology 2017 Objective To assess the utility of the motion correction method with prospective motion correction (PROMO) in a voxel-based morphometry (VBM) analysis for ‘uncooperative’ patient populations. Methods High-resolution 3D T1-weighted imaging both with and without PROMO were performed in 33 uncooperative patients with Parkinson's disease (n = 11) or dementia (n = 22). We compared the grey matter (GM) volumes and cortical thickness between the scans with and without PROMO. Results For the mean total GM volume with the VBM analysis, the scan without PROMO showed a significantly smaller volume than that with PROMO (p < 0.05), which was caused by segmentation problems due to motion during acquisition. The whole-brain VBM analysis showed significant GM volume reductions in some regions in the scans without PROMO (familywise error corrected p < 0.05). In the cortical thickness analysis, the scans without PROMO also showed decreased cortical thickness compared to the scan with PROMO (p < 0.05). Conclusion Our results with the uncooperative patients indicate that the use of PROMO can reduce misclassification during segmentation of the VBM analyses, although it may not prevent GM volume reduction. Key Points • Motion artifacts pose significant problems for VBM analyses. • PROMO correction can reduce the motion artifacts in high-resolution 3D T1WI. • The use of PROMO may improve the precision of VBM analyses. Prospective motion correction (dpeaa)DE-He213 Voxel-based morphometry (dpeaa)DE-He213 Motion artifacts (dpeaa)DE-He213 Extended Kalman Filter (EKF) motion estimates (dpeaa)DE-He213 Parkinson’s disease (dpeaa)DE-He213 Kakeda, Shingo aut Watanabe, Keita aut Nozaki, Atsushi aut Rettmann, Dan aut Narimatsu, Hidekuni aut Ide, Satoru aut Abe, Osamu aut Korogi, Yukunori aut Enthalten in European radiology Berlin : Springer, 1991 27(2017), 8 vom: 23. Jan., Seite 3554-3562 (DE-627)268757526 (DE-600)1472718-3 1432-1084 nnns volume:27 year:2017 number:8 day:23 month:01 pages:3554-3562 https://dx.doi.org/10.1007/s00330-016-4730-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_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_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 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_2446 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 27 2017 8 23 01 3554-3562 |
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Enthalten in European radiology 27(2017), 8 vom: 23. Jan., Seite 3554-3562 volume:27 year:2017 number:8 day:23 month:01 pages:3554-3562 |
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Enthalten in European radiology 27(2017), 8 vom: 23. Jan., Seite 3554-3562 volume:27 year:2017 number:8 day:23 month:01 pages:3554-3562 |
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Prospective motion correction Voxel-based morphometry Motion artifacts Extended Kalman Filter (EKF) motion estimates Parkinson’s disease |
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European radiology |
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Igata, Natsuki @@aut@@ Kakeda, Shingo @@aut@@ Watanabe, Keita @@aut@@ Nozaki, Atsushi @@aut@@ Rettmann, Dan @@aut@@ Narimatsu, Hidekuni @@aut@@ Ide, Satoru @@aut@@ Abe, Osamu @@aut@@ Korogi, Yukunori @@aut@@ |
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2017-01-23T00:00:00Z |
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Methods High-resolution 3D T1-weighted imaging both with and without PROMO were performed in 33 uncooperative patients with Parkinson's disease (n = 11) or dementia (n = 22). We compared the grey matter (GM) volumes and cortical thickness between the scans with and without PROMO. Results For the mean total GM volume with the VBM analysis, the scan without PROMO showed a significantly smaller volume than that with PROMO (p < 0.05), which was caused by segmentation problems due to motion during acquisition. The whole-brain VBM analysis showed significant GM volume reductions in some regions in the scans without PROMO (familywise error corrected p < 0.05). In the cortical thickness analysis, the scans without PROMO also showed decreased cortical thickness compared to the scan with PROMO (p < 0.05). Conclusion Our results with the uncooperative patients indicate that the use of PROMO can reduce misclassification during segmentation of the VBM analyses, although it may not prevent GM volume reduction. 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Igata, Natsuki |
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Igata, Natsuki misc Prospective motion correction misc Voxel-based morphometry misc Motion artifacts misc Extended Kalman Filter (EKF) motion estimates misc Parkinson’s disease Utility of real-time prospective motion correction (PROMO) for segmentation of cerebral cortex on 3D T1-weighted imaging: Voxel-based morphometry analysis for uncooperative patients |
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Utility of real-time prospective motion correction (PROMO) for segmentation of cerebral cortex on 3D T1-weighted imaging: Voxel-based morphometry analysis for uncooperative patients Prospective motion correction (dpeaa)DE-He213 Voxel-based morphometry (dpeaa)DE-He213 Motion artifacts (dpeaa)DE-He213 Extended Kalman Filter (EKF) motion estimates (dpeaa)DE-He213 Parkinson’s disease (dpeaa)DE-He213 |
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Igata, Natsuki Kakeda, Shingo Watanabe, Keita Nozaki, Atsushi Rettmann, Dan Narimatsu, Hidekuni Ide, Satoru Abe, Osamu Korogi, Yukunori |
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Igata, Natsuki |
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10.1007/s00330-016-4730-7 |
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utility of real-time prospective motion correction (promo) for segmentation of cerebral cortex on 3d t1-weighted imaging: voxel-based morphometry analysis for uncooperative patients |
| title_auth |
Utility of real-time prospective motion correction (PROMO) for segmentation of cerebral cortex on 3D T1-weighted imaging: Voxel-based morphometry analysis for uncooperative patients |
| abstract |
Objective To assess the utility of the motion correction method with prospective motion correction (PROMO) in a voxel-based morphometry (VBM) analysis for ‘uncooperative’ patient populations. Methods High-resolution 3D T1-weighted imaging both with and without PROMO were performed in 33 uncooperative patients with Parkinson's disease (n = 11) or dementia (n = 22). We compared the grey matter (GM) volumes and cortical thickness between the scans with and without PROMO. Results For the mean total GM volume with the VBM analysis, the scan without PROMO showed a significantly smaller volume than that with PROMO (p < 0.05), which was caused by segmentation problems due to motion during acquisition. The whole-brain VBM analysis showed significant GM volume reductions in some regions in the scans without PROMO (familywise error corrected p < 0.05). In the cortical thickness analysis, the scans without PROMO also showed decreased cortical thickness compared to the scan with PROMO (p < 0.05). Conclusion Our results with the uncooperative patients indicate that the use of PROMO can reduce misclassification during segmentation of the VBM analyses, although it may not prevent GM volume reduction. Key Points • Motion artifacts pose significant problems for VBM analyses. • PROMO correction can reduce the motion artifacts in high-resolution 3D T1WI. • The use of PROMO may improve the precision of VBM analyses. © European Society of Radiology 2017 |
| abstractGer |
Objective To assess the utility of the motion correction method with prospective motion correction (PROMO) in a voxel-based morphometry (VBM) analysis for ‘uncooperative’ patient populations. Methods High-resolution 3D T1-weighted imaging both with and without PROMO were performed in 33 uncooperative patients with Parkinson's disease (n = 11) or dementia (n = 22). We compared the grey matter (GM) volumes and cortical thickness between the scans with and without PROMO. Results For the mean total GM volume with the VBM analysis, the scan without PROMO showed a significantly smaller volume than that with PROMO (p < 0.05), which was caused by segmentation problems due to motion during acquisition. The whole-brain VBM analysis showed significant GM volume reductions in some regions in the scans without PROMO (familywise error corrected p < 0.05). In the cortical thickness analysis, the scans without PROMO also showed decreased cortical thickness compared to the scan with PROMO (p < 0.05). Conclusion Our results with the uncooperative patients indicate that the use of PROMO can reduce misclassification during segmentation of the VBM analyses, although it may not prevent GM volume reduction. Key Points • Motion artifacts pose significant problems for VBM analyses. • PROMO correction can reduce the motion artifacts in high-resolution 3D T1WI. • The use of PROMO may improve the precision of VBM analyses. © European Society of Radiology 2017 |
| abstract_unstemmed |
Objective To assess the utility of the motion correction method with prospective motion correction (PROMO) in a voxel-based morphometry (VBM) analysis for ‘uncooperative’ patient populations. Methods High-resolution 3D T1-weighted imaging both with and without PROMO were performed in 33 uncooperative patients with Parkinson's disease (n = 11) or dementia (n = 22). We compared the grey matter (GM) volumes and cortical thickness between the scans with and without PROMO. Results For the mean total GM volume with the VBM analysis, the scan without PROMO showed a significantly smaller volume than that with PROMO (p < 0.05), which was caused by segmentation problems due to motion during acquisition. The whole-brain VBM analysis showed significant GM volume reductions in some regions in the scans without PROMO (familywise error corrected p < 0.05). In the cortical thickness analysis, the scans without PROMO also showed decreased cortical thickness compared to the scan with PROMO (p < 0.05). Conclusion Our results with the uncooperative patients indicate that the use of PROMO can reduce misclassification during segmentation of the VBM analyses, although it may not prevent GM volume reduction. Key Points • Motion artifacts pose significant problems for VBM analyses. • PROMO correction can reduce the motion artifacts in high-resolution 3D T1WI. • The use of PROMO may improve the precision of VBM analyses. © European Society of Radiology 2017 |
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Utility of real-time prospective motion correction (PROMO) for segmentation of cerebral cortex on 3D T1-weighted imaging: Voxel-based morphometry analysis for uncooperative patients |
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| score |
7.4011784 |