Clinical feasibility of a myocardial signal intensity threshold-based semi-automated cardiac magnetic resonance segmentation method
Objectives To assess the accuracy and efficiency of a threshold-based, semi-automated cardiac MRI segmentation algorithm in comparison with conventional contour-based segmentation and aortic flow measurements. Methods Short-axis cine images of 148 patients (55 ± 18 years, 81 men) were used to evalua...
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| Vydáno v: | European radiology Ročník 26; číslo 5; s. 1503 - 1511 |
|---|---|
| Hlavní autoři: | , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.05.2016
Springer Nature B.V |
| Témata: | |
| ISSN: | 0938-7994, 1432-1084, 1432-1084 |
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| Abstract | Objectives
To assess the accuracy and efficiency of a threshold-based, semi-automated cardiac MRI segmentation algorithm in comparison with conventional contour-based segmentation and aortic flow measurements.
Methods
Short-axis cine images of 148 patients (55 ± 18 years, 81 men) were used to evaluate left ventricular (LV) volumes and mass (LVM) using conventional and threshold-based segmentations. Phase-contrast images were used to independently measure stroke volume (SV). LV parameters were evaluated by two independent readers.
Results
Evaluation times using the conventional and threshold-based methods were 8.4 ± 1.9 and 4.2 ± 1.3 min, respectively (
P
< 0.0001). LV parameters measured by the conventional and threshold-based methods, respectively, were end-diastolic volume (EDV) 146 ± 59 and 134 ± 53 ml; end-systolic volume (ESV) 64 ± 47 and 59 ± 46 ml; SV 82 ± 29 and 74 ± 28 ml (flow-based 74 ± 30 ml); ejection fraction (EF) 59 ± 16 and 58 ± 17 %; and LVM 141 ± 55 and 159 ± 58 g. Significant differences between the conventional and threshold-based methods were observed in EDV, ESV, and LVM mesurements; SV from threshold-based and flow-based measurements were in agreement (
P
> 0.05) but were significantly different from conventional analysis (
P
< 0.05). Excellent inter-observer agreement was observed.
Conclusions
Threshold-based LV segmentation provides improved accuracy and faster assessment compared to conventional contour-based methods.
Key Points
•
Threshold-based left ventricular segmentation provides time-efficient assessment of left ventricular parameters
•
The threshold-based method can discriminate between blood and papillary muscles
•
This method provides improved accuracy compared to aortic flow measurements as a reference |
|---|---|
| AbstractList | Objectives To assess the accuracy and efficiency of a threshold-based, semi-automated cardiac MRI segmentation algorithm in comparison with conventional contour-based segmentation and aortic flow measurements. Methods Short-axis cine images of 148 patients (55±18 years, 81 men) were used to evaluate left ventricular (LV) volumes and mass (LVM) using conventional and threshold-based segmentations. Phase-contrast images were used to independently measure stroke volume (SV). LV parameters were evaluated by two independent readers. Results Evaluation times using the conventional and threshold-based methods were 8.4±1.9 and 4.2±1.3 min, respectively (P<0.0001). LV parameters measured by the conventional and threshold-based methods, respectively, were end-diastolic volume (EDV) 146±59 and 134±53 ml; end-systolic volume (ESV) 64±47 and 59±46 ml; SV 82±29 and 74±28 ml (flow-based 74±30 ml); ejection fraction (EF) 59±16 and 58±17 %; and LVM 141±55 and 159±58 g. Significant differences between the conventional and threshold-based methods were observed in EDV, ESV, and LVM mesurements; SV from threshold-based and flow-based measurements were in agreement (P>0.05) but were significantly different from conventional analysis (P<0.05). Excellent inter-observer agreement was observed. Conclusions Threshold-based LV segmentation provides improved accuracy and faster assessment compared to conventional contour-based methods. Key Points * Threshold-based left ventricular segmentation provides time-efficient assessment of left ventricular parameters * The threshold-based method can discriminate between blood and papillary muscles * This method provides improved accuracy compared to aortic flow measurements as a reference To assess the accuracy and efficiency of a threshold-based, semi-automated cardiac MRI segmentation algorithm in comparison with conventional contour-based segmentation and aortic flow measurements.OBJECTIVESTo assess the accuracy and efficiency of a threshold-based, semi-automated cardiac MRI segmentation algorithm in comparison with conventional contour-based segmentation and aortic flow measurements.Short-axis cine images of 148 patients (55 ± 18 years, 81 men) were used to evaluate left ventricular (LV) volumes and mass (LVM) using conventional and threshold-based segmentations. Phase-contrast images were used to independently measure stroke volume (SV). LV parameters were evaluated by two independent readers.METHODSShort-axis cine images of 148 patients (55 ± 18 years, 81 men) were used to evaluate left ventricular (LV) volumes and mass (LVM) using conventional and threshold-based segmentations. Phase-contrast images were used to independently measure stroke volume (SV). LV parameters were evaluated by two independent readers.Evaluation times using the conventional and threshold-based methods were 8.4 ± 1.9 and 4.2 ± 1.3 min, respectively (P < 0.0001). LV parameters measured by the conventional and threshold-based methods, respectively, were end-diastolic volume (EDV) 146 ± 59 and 134 ± 53 ml; end-systolic volume (ESV) 64 ± 47 and 59 ± 46 ml; SV 82 ± 29 and 74 ± 28 ml (flow-based 74 ± 30 ml); ejection fraction (EF) 59 ± 16 and 58 ± 17%; and LVM 141 ± 55 and 159 ± 58 g. Significant differences between the conventional and threshold-based methods were observed in EDV, ESV, and LVM mesurements; SV from threshold-based and flow-based measurements were in agreement (P > 0.05) but were significantly different from conventional analysis (P < 0.05). Excellent inter-observer agreement was observed.RESULTSEvaluation times using the conventional and threshold-based methods were 8.4 ± 1.9 and 4.2 ± 1.3 min, respectively (P < 0.0001). LV parameters measured by the conventional and threshold-based methods, respectively, were end-diastolic volume (EDV) 146 ± 59 and 134 ± 53 ml; end-systolic volume (ESV) 64 ± 47 and 59 ± 46 ml; SV 82 ± 29 and 74 ± 28 ml (flow-based 74 ± 30 ml); ejection fraction (EF) 59 ± 16 and 58 ± 17%; and LVM 141 ± 55 and 159 ± 58 g. Significant differences between the conventional and threshold-based methods were observed in EDV, ESV, and LVM mesurements; SV from threshold-based and flow-based measurements were in agreement (P > 0.05) but were significantly different from conventional analysis (P < 0.05). Excellent inter-observer agreement was observed.Threshold-based LV segmentation provides improved accuracy and faster assessment compared to conventional contour-based methods.CONCLUSIONSThreshold-based LV segmentation provides improved accuracy and faster assessment compared to conventional contour-based methods.• Threshold-based left ventricular segmentation provides time-efficient assessment of left ventricular parameters • The threshold-based method can discriminate between blood and papillary muscles • This method provides improved accuracy compared to aortic flow measurements as a reference.KEY POINTS• Threshold-based left ventricular segmentation provides time-efficient assessment of left ventricular parameters • The threshold-based method can discriminate between blood and papillary muscles • This method provides improved accuracy compared to aortic flow measurements as a reference. To assess the accuracy and efficiency of a threshold-based, semi-automated cardiac MRI segmentation algorithm in comparison with conventional contour-based segmentation and aortic flow measurements. Short-axis cine images of 148 patients (55 ± 18 years, 81 men) were used to evaluate left ventricular (LV) volumes and mass (LVM) using conventional and threshold-based segmentations. Phase-contrast images were used to independently measure stroke volume (SV). LV parameters were evaluated by two independent readers. Evaluation times using the conventional and threshold-based methods were 8.4 ± 1.9 and 4.2 ± 1.3 min, respectively (P < 0.0001). LV parameters measured by the conventional and threshold-based methods, respectively, were end-diastolic volume (EDV) 146 ± 59 and 134 ± 53 ml; end-systolic volume (ESV) 64 ± 47 and 59 ± 46 ml; SV 82 ± 29 and 74 ± 28 ml (flow-based 74 ± 30 ml); ejection fraction (EF) 59 ± 16 and 58 ± 17%; and LVM 141 ± 55 and 159 ± 58 g. Significant differences between the conventional and threshold-based methods were observed in EDV, ESV, and LVM mesurements; SV from threshold-based and flow-based measurements were in agreement (P > 0.05) but were significantly different from conventional analysis (P < 0.05). Excellent inter-observer agreement was observed. Threshold-based LV segmentation provides improved accuracy and faster assessment compared to conventional contour-based methods. • Threshold-based left ventricular segmentation provides time-efficient assessment of left ventricular parameters • The threshold-based method can discriminate between blood and papillary muscles • This method provides improved accuracy compared to aortic flow measurements as a reference. Objectives To assess the accuracy and efficiency of a threshold-based, semi-automated cardiac MRI segmentation algorithm in comparison with conventional contour-based segmentation and aortic flow measurements. Methods Short-axis cine images of 148 patients (55 ± 18 years, 81 men) were used to evaluate left ventricular (LV) volumes and mass (LVM) using conventional and threshold-based segmentations. Phase-contrast images were used to independently measure stroke volume (SV). LV parameters were evaluated by two independent readers. Results Evaluation times using the conventional and threshold-based methods were 8.4 ± 1.9 and 4.2 ± 1.3 min, respectively ( P < 0.0001). LV parameters measured by the conventional and threshold-based methods, respectively, were end-diastolic volume (EDV) 146 ± 59 and 134 ± 53 ml; end-systolic volume (ESV) 64 ± 47 and 59 ± 46 ml; SV 82 ± 29 and 74 ± 28 ml (flow-based 74 ± 30 ml); ejection fraction (EF) 59 ± 16 and 58 ± 17 %; and LVM 141 ± 55 and 159 ± 58 g. Significant differences between the conventional and threshold-based methods were observed in EDV, ESV, and LVM mesurements; SV from threshold-based and flow-based measurements were in agreement ( P > 0.05) but were significantly different from conventional analysis ( P < 0.05). Excellent inter-observer agreement was observed. Conclusions Threshold-based LV segmentation provides improved accuracy and faster assessment compared to conventional contour-based methods. Key Points • Threshold-based left ventricular segmentation provides time-efficient assessment of left ventricular parameters • The threshold-based method can discriminate between blood and papillary muscles • This method provides improved accuracy compared to aortic flow measurements as a reference |
| Author | De Cecco, Carlo N. Varga-Szemes, Akos Wichmann, Julian L. Suranyi, Pal Schoepf, U. Joseph Mangold, Stefanie Ruzsics, Balazs Fox, Mary A. Renker, Matthias Cannaò, Paola M. Muscogiuri, Giuseppe |
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/26267520$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1016/j.ijcard.2007.04.179 10.1007/s10554-012-0130-5 10.1016/j.media.2011.01.002 10.1109/42.925294 10.1161/CIRCIMAGING.111.966754 10.1007/s00330-006-0226-1 10.1109/83.847836 10.1080/02841850801998847 10.1016/S0140-6736(86)90837-8 10.1016/j.media.2010.12.004 10.1002/jmri.22080 10.1002/jmri.21451 10.1016/S0002-9149(02)02381-0 10.1002/jmri.10262 10.1148/radiol.2482072016 10.1109/TMI.2010.2086465 10.1186/1532-429X-13-S1-P355 10.1148/radiol.2353040601 10.1186/1532-429X-12-5 10.1109/TMI.2003.814785 10.1016/j.jcmg.2012.05.015 10.1186/1532-429X-13-S1-P213 10.1109/TBME.2008.2005957 10.1016/j.media.2004.06.015 |
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| Keywords | Aortic flow Cine magnetic resonance imaging Left ventricular mass Left ventricular function Semi-automated segmentation |
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| References | Bland, Altman (CR12) 1986; 1 Mitchell, Lelieveldt, van der Geest, Bosch, Reiber, Sonka (CR20) 2011; 20 Kurkure, Pednekar, Muthupillai, Flamm, Kakadiaris Ast (CR16) 2009; 56 Grothues, Smith, Moon (CR1) 2002; 90 Alfakih, Plein, Thiele, Jones, Ridgway, Sivananthan (CR2) 2003; 17 Petitjean, Dacher (CR6) 2011; 15 Jeltsch, Ranft, Klass, Aschoff, Hoffmann (CR9) 2008; 49 Rezaee, van der Zwet, Lelieveldt, van der Geest, Reiber (CR17) 2000; 9 Chuang, Gona, Hautvast (CR4) 2012; 5 Codella, Lee, Fieno (CR26) 2012; 5 Codella, Cham, Wong (CR14) 2010; 31 Cheng (CR27) 2011; 13 Codella, Weinsaft, Cham, Janik, Prince, Wang (CR13) 2008; 248 Ben Ayed, Lu, Li, Ross (CR23) 2008; 11 Weinsaft, Cham, Janik (CR5) 2008; 126 Paragios (CR22) 2003; 22 Papavassiliu, Kuhl, Schroder (CR3) 2005; 236 Jaspers, Freling, van Wijk, Romijn, Greuter, Willems (CR7) 2013; 29 Gatehouse, Rolf, Graves (CR10) 2010; 12 Mahnken, Muhlenbruch, Koos (CR8) 2006; 16 Misra, Shah, Lai (CR11) 2011; 13 Cocosco, Niessen, Netsch (CR25) 2008; 28 Lu, Connelly, Dick, Wright, Radau (CR15) 2013; 3 Kaus, von Berg, Weese, Niessen, Pekar (CR18) 2004; 8 Lin, Cowan, Young (CR24) 2005; 3 O'Brien, Ghita, Whelan (CR21) 2011; 30 Cordero-Grande, Vegas-Sanchez-Ferrero, Casaseca-de-la-Higuera (CR19) 2011; 15 N Misra (3952_CR11) 2011; 13 PD Gatehouse (3952_CR10) 2010; 12 NC Codella (3952_CR26) 2012; 5 SC Mitchell (3952_CR20) 2011; 20 MR Kaus (3952_CR18) 2004; 8 M Jeltsch (3952_CR9) 2008; 49 T Papavassiliu (3952_CR3) 2005; 236 L Cordero-Grande (3952_CR19) 2011; 15 MR Rezaee (3952_CR17) 2000; 9 F Grothues (3952_CR1) 2002; 90 JW Weinsaft (3952_CR5) 2008; 126 I Ben Ayed (3952_CR23) 2008; 11 JY Cheng (3952_CR27) 2011; 13 NC Codella (3952_CR13) 2008; 248 K Jaspers (3952_CR7) 2013; 29 JM Bland (3952_CR12) 1986; 1 X Lin (3952_CR24) 2005; 3 AH Mahnken (3952_CR8) 2006; 16 NC Codella (3952_CR14) 2010; 31 SP O'Brien (3952_CR21) 2011; 30 N Paragios (3952_CR22) 2003; 22 CA Cocosco (3952_CR25) 2008; 28 K Alfakih (3952_CR2) 2003; 17 U Kurkure (3952_CR16) 2009; 56 ML Chuang (3952_CR4) 2012; 5 YL Lu (3952_CR15) 2013; 3 C Petitjean (3952_CR6) 2011; 15 |
| References_xml | – volume: 126 start-page: 359 year: 2008 end-page: 365 ident: CR5 article-title: Left ventricular papillary muscles and trabeculae are significant determinants of cardiac MRI volumetric measurements: effects on clinical standards in patients with advanced systolic dysfunction publication-title: Int J Cardiol doi: 10.1016/j.ijcard.2007.04.179 – volume: 29 start-page: 617 year: 2013 end-page: 623 ident: CR7 article-title: Improving the reproducibility of MR-derived left ventricular volume and function measurements with a semi-automatic threshold-based segmentation algorithm publication-title: Int J Cardiovasc Imaging doi: 10.1007/s10554-012-0130-5 – volume: 15 start-page: 283 year: 2011 end-page: 301 ident: CR19 article-title: Unsupervised 4D myocardium segmentation with a Markov random field based deformable model publication-title: Med Image Anal doi: 10.1016/j.media.2011.01.002 – volume: 3 start-page: 3059 year: 2005 end-page: 3062 ident: CR24 article-title: Model-based graph cut method for segmentation of the left ventricle publication-title: Conf Proc IEEE Eng Med Biol Soc – volume: 20 start-page: 415 year: 2011 end-page: 423 ident: CR20 article-title: Multistage hybrid active appearance model matching: segmentation of left and right ventricles in cardiac MR images publication-title: IEEE Trans Med Imaging doi: 10.1109/42.925294 – volume: 5 start-page: 137 year: 2012 end-page: 146 ident: CR26 article-title: Improved left ventricular mass quantification with partial voxel interpolation: in vivo and necropsy validation of a novel cardiac MRI segmentation algorithm publication-title: Circ Cardiovasc Imaging doi: 10.1161/CIRCIMAGING.111.966754 – volume: 16 start-page: 1416 year: 2006 end-page: 1423 ident: CR8 article-title: Automated vs. manual assessment of left ventricular function in cardiac multidetector row computed tomography: comparison with magnetic resonance imaging publication-title: Eur Radiol doi: 10.1007/s00330-006-0226-1 – volume: 9 start-page: 1238 year: 2000 end-page: 1248 ident: CR17 article-title: A multiresolution image segmentation technique based on pyramidal segmentation and fuzzy clustering publication-title: IEEE Trans Image Process doi: 10.1109/83.847836 – volume: 49 start-page: 530 year: 2008 end-page: 539 ident: CR9 article-title: Evaluation of accordance of magnetic resonance volumetric and flow measurements in determining ventricular stroke volume in cardiac patients publication-title: Acta Radiol doi: 10.1080/02841850801998847 – volume: 1 start-page: 307 year: 1986 end-page: 310 ident: CR12 article-title: Statistical methods for assessing agreement between two methods of clinical measurement publication-title: Lancet doi: 10.1016/S0140-6736(86)90837-8 – volume: 3 start-page: 200 year: 2013 end-page: 209 ident: CR15 article-title: Automatic functional analysis of left ventricle in cardiac cine MRI publication-title: Quant Imaging Med Surg – volume: 15 start-page: 169 year: 2011 end-page: 184 ident: CR6 article-title: A review of segmentation methods in short axis cardiac MR images publication-title: Med Image Anal doi: 10.1016/j.media.2010.12.004 – volume: 31 start-page: 845 year: 2010 end-page: 853 ident: CR14 article-title: Rapid and accurate left ventricular chamber quantification using a novel CMR segmentation algorithm: a clinical validation study publication-title: J Magn Reson Imaging doi: 10.1002/jmri.22080 – volume: 28 start-page: 366 year: 2008 end-page: 374 ident: CR25 article-title: Automatic image-driven segmentation of the ventricles in cardiac cine MRI publication-title: J Magn Reson Imaging doi: 10.1002/jmri.21451 – volume: 90 start-page: 29 year: 2002 end-page: 34 ident: CR1 article-title: Comparison of interstudy reproducibility of cardiovascular magnetic resonance with two-dimensional echocardiography in normal subjects and in patients with heart failure or left ventricular hypertrophy publication-title: Am J Cardiol doi: 10.1016/S0002-9149(02)02381-0 – volume: 17 start-page: 323 year: 2003 end-page: 329 ident: CR2 article-title: Normal human left and right ventricular dimensions for MRI as assessed by turbo gradient echo and steady-state free precession imaging sequences publication-title: J Magn Reson Imaging doi: 10.1002/jmri.10262 – volume: 248 start-page: 1004 year: 2008 end-page: 1012 ident: CR13 article-title: Left ventricle: automated segmentation by using myocardial effusion threshold reduction and intravoxel computation at MR imaging publication-title: Radiology doi: 10.1148/radiol.2482072016 – volume: 30 start-page: 461 year: 2011 end-page: 474 ident: CR21 article-title: A novel model-based 3D + time left ventricular segmentation technique publication-title: IEEE Trans Med Imaging doi: 10.1109/TMI.2010.2086465 – volume: 13 start-page: P355 issue: Suppl 1 year: 2011 ident: CR27 article-title: Image based background magnetic field correction for aortic and pulmonary artery flow measurement using phase contrast publication-title: J Cardiovasc Magn Reson doi: 10.1186/1532-429X-13-S1-P355 – volume: 236 start-page: 57 year: 2005 end-page: 64 ident: CR3 article-title: Effect of endocardial trabeculae on left ventricular measurements and measurement reproducibility at cardiovascular MR imaging publication-title: Radiology doi: 10.1148/radiol.2353040601 – volume: 12 start-page: 5 year: 2010 ident: CR10 article-title: Flow measurement by cardiovascular magnetic resonance: a multi-center multi-vendor study of background phase offset errors that can compromise the accuracy of derived regurgitant or shunt flow measurements publication-title: J Cardiovasc Magn Reson doi: 10.1186/1532-429X-12-5 – volume: 22 start-page: 773 year: 2003 end-page: 776 ident: CR22 article-title: A level set approach for shape-driven segmentation and tracking of the left ventricle publication-title: IEEE Trans Med Imaging doi: 10.1109/TMI.2003.814785 – volume: 5 start-page: 1115 year: 2012 end-page: 1123 ident: CR4 article-title: Correlation of trabeculae and papillary muscles with clinical and cardiac characteristics and impact on CMR measures of LV anatomy and function publication-title: JACC Cardiovasc Imaging doi: 10.1016/j.jcmg.2012.05.015 – volume: 11 start-page: 1025 issue: Pt 1 year: 2008 end-page: 1033 ident: CR23 article-title: Left ventricle tracking using overlap priors publication-title: Med Image Comput Comput Assist Interv – volume: 13 start-page: P213 issue: Suppl 1 year: 2011 ident: CR11 article-title: Correction of phase offset errors in cardiovascular magnetic resonance using background subtraction from stationary tissue publication-title: J Cardiovasc Magn Reson doi: 10.1186/1532-429X-13-S1-P213 – volume: 56 start-page: 1360 year: 2009 end-page: 1370 ident: CR16 article-title: Localization and segmentation of left ventricle in cardiac cine-MR images publication-title: IEEE Trans Biomed Eng doi: 10.1109/TBME.2008.2005957 – volume: 8 start-page: 245 year: 2004 end-page: 254 ident: CR18 article-title: Automated segmentation of the left ventricle in cardiac MRI publication-title: Med Image Anal doi: 10.1016/j.media.2004.06.015 – volume: 31 start-page: 845 year: 2010 ident: 3952_CR14 publication-title: J Magn Reson Imaging doi: 10.1002/jmri.22080 – volume: 30 start-page: 461 year: 2011 ident: 3952_CR21 publication-title: IEEE Trans Med Imaging doi: 10.1109/TMI.2010.2086465 – volume: 3 start-page: 3059 year: 2005 ident: 3952_CR24 publication-title: Conf Proc IEEE Eng Med Biol Soc – volume: 28 start-page: 366 year: 2008 ident: 3952_CR25 publication-title: J Magn Reson Imaging doi: 10.1002/jmri.21451 – volume: 5 start-page: 137 year: 2012 ident: 3952_CR26 publication-title: Circ Cardiovasc Imaging doi: 10.1161/CIRCIMAGING.111.966754 – volume: 17 start-page: 323 year: 2003 ident: 3952_CR2 publication-title: J Magn Reson Imaging doi: 10.1002/jmri.10262 – volume: 29 start-page: 617 year: 2013 ident: 3952_CR7 publication-title: Int J Cardiovasc Imaging doi: 10.1007/s10554-012-0130-5 – volume: 12 start-page: 5 year: 2010 ident: 3952_CR10 publication-title: J Cardiovasc Magn Reson doi: 10.1186/1532-429X-12-5 – volume: 49 start-page: 530 year: 2008 ident: 3952_CR9 publication-title: Acta Radiol doi: 10.1080/02841850801998847 – volume: 9 start-page: 1238 year: 2000 ident: 3952_CR17 publication-title: IEEE Trans Image Process doi: 10.1109/83.847836 – volume: 5 start-page: 1115 year: 2012 ident: 3952_CR4 publication-title: JACC Cardiovasc Imaging doi: 10.1016/j.jcmg.2012.05.015 – volume: 126 start-page: 359 year: 2008 ident: 3952_CR5 publication-title: Int J Cardiol doi: 10.1016/j.ijcard.2007.04.179 – volume: 90 start-page: 29 year: 2002 ident: 3952_CR1 publication-title: Am J Cardiol doi: 10.1016/S0002-9149(02)02381-0 – volume: 248 start-page: 1004 year: 2008 ident: 3952_CR13 publication-title: Radiology doi: 10.1148/radiol.2482072016 – volume: 8 start-page: 245 year: 2004 ident: 3952_CR18 publication-title: Med Image Anal doi: 10.1016/j.media.2004.06.015 – volume: 16 start-page: 1416 year: 2006 ident: 3952_CR8 publication-title: Eur Radiol doi: 10.1007/s00330-006-0226-1 – volume: 3 start-page: 200 year: 2013 ident: 3952_CR15 publication-title: Quant Imaging Med Surg – volume: 13 start-page: P355 issue: Suppl 1 year: 2011 ident: 3952_CR27 publication-title: J Cardiovasc Magn Reson doi: 10.1186/1532-429X-13-S1-P355 – volume: 20 start-page: 415 year: 2011 ident: 3952_CR20 publication-title: IEEE Trans Med Imaging doi: 10.1109/42.925294 – volume: 22 start-page: 773 year: 2003 ident: 3952_CR22 publication-title: IEEE Trans Med Imaging doi: 10.1109/TMI.2003.814785 – volume: 1 start-page: 307 year: 1986 ident: 3952_CR12 publication-title: Lancet doi: 10.1016/S0140-6736(86)90837-8 – volume: 11 start-page: 1025 issue: Pt 1 year: 2008 ident: 3952_CR23 publication-title: Med Image Comput Comput Assist Interv – volume: 236 start-page: 57 year: 2005 ident: 3952_CR3 publication-title: Radiology doi: 10.1148/radiol.2353040601 – volume: 56 start-page: 1360 year: 2009 ident: 3952_CR16 publication-title: IEEE Trans Biomed Eng doi: 10.1109/TBME.2008.2005957 – volume: 15 start-page: 283 year: 2011 ident: 3952_CR19 publication-title: Med Image Anal doi: 10.1016/j.media.2011.01.002 – volume: 13 start-page: P213 issue: Suppl 1 year: 2011 ident: 3952_CR11 publication-title: J Cardiovasc Magn Reson doi: 10.1186/1532-429X-13-S1-P213 – volume: 15 start-page: 169 year: 2011 ident: 3952_CR6 publication-title: Med Image Anal doi: 10.1016/j.media.2010.12.004 |
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To assess the accuracy and efficiency of a threshold-based, semi-automated cardiac MRI segmentation algorithm in comparison with conventional... To assess the accuracy and efficiency of a threshold-based, semi-automated cardiac MRI segmentation algorithm in comparison with conventional contour-based... Objectives To assess the accuracy and efficiency of a threshold-based, semi-automated cardiac MRI segmentation algorithm in comparison with conventional... |
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| SubjectTerms | Accuracy Algorithms Automation Cardiac Diagnostic Radiology Feasibility Studies Female Heart Ventricles - pathology Humans Imaging Internal Medicine Interventional Radiology Magnetic Resonance Angiography - methods Magnetic resonance imaging Magnetic Resonance Imaging, Cine Magnetic Resonance Spectroscopy Male Medicine Medicine & Public Health Methods Middle Aged Myocardium - pathology Neuroradiology Observer Variation Radiology Reproducibility of Results Stroke Volume - physiology Ultrasound Ventricular Dysfunction, Left - pathology Ventricular Dysfunction, Left - physiopathology |
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| Title | Clinical feasibility of a myocardial signal intensity threshold-based semi-automated cardiac magnetic resonance segmentation method |
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