PURPOSE: To validate a volumetric biventricular segmentation solution for multiaxis cardiac magnetic resonance (CMR) images. MATERIALS AND METHODS: The study population comprised 40 subjects. Biventricular end-diastolic and -systolic phases were segmented from both short-axis and horizontal long-axis or transaxial cine CMR images. Segmentation was based on fitting nonrigidly a 3D surface model to multiaxis CMR images. Five segmentations were performed: two manual segmentations by experts, automatic segmentation, and two segmentations where a user was allowed to correct errors in the automatic segmentation for 2 minutes and without time limits. Volumetry, distance measures, and visual grading were used to evaluate the quality of the segmentation. RESULTS: No difference was observed between automatic and manual segmentations in volumetric measures of the ventricles. The manual segmentation performed better for left-ventricular myocardial volume. The distance between surfaces as well as visual analysis did not show differences between automatic and manual segmentation for the endocardial border of the left ventricle but some corrections are needed for the right ventricle. CONCLUSION: Fully automatic segmentation produces good results in the assessment of left ventricular volume andendocardial border. Two minutes of user interaction are needed to obtain accurate results for the right ventricle. Copyright (c) 2008 Wiley-Liss, Inc.
PURPOSE: To validate a volumetric biventricular segmentation solution for multiaxis cardiac magnetic resonance (CMR) images. MATERIALS AND METHODS: The study population comprised 40 subjects. Biventricular end-diastolic and -systolic phases were segmented from both short-axis and horizontal long-axis or transaxial cine CMR images. Segmentation was based on fitting nonrigidly a 3D surface model to multiaxis CMR images. Five segmentations were performed: two manual segmentations by experts, automatic segmentation, and two segmentations where a user was allowed to correct errors in the automatic segmentation for 2 minutes and without time limits. Volumetry, distance measures, and visual grading were used to evaluate the quality of the segmentation. RESULTS: No difference was observed between automatic and manual segmentations in volumetric measures of the ventricles. The manual segmentation performed better for left-ventricular myocardial volume. The distance between surfaces as well as visual analysis did not show differences between automatic and manual segmentation for the endocardial border of the left ventricle but some corrections are needed for the right ventricle. CONCLUSION: Fully automatic segmentation produces good results in the assessment of left ventricular volume andendocardial border. Two minutes of user interaction are needed to obtain accurate results for the right ventricle. Copyright (c) 2008 Wiley-Liss, Inc.
Authors: Gilion L T F Hautvast; Carol J Salton; Michael L Chuang; Marcel Breeuwer; Christopher J O'Donnell; Warren J Manning Journal: Magn Reson Med Date: 2011-10-21 Impact factor: 4.668
Authors: Richard Kasch; Birger Mensel; Florian Schmidt; Wolf Drescher; Ralf Pfuhl; Sebastian Ruetten; Harry R Merk; Ralph Kayser Journal: PLoS One Date: 2012-07-25 Impact factor: 3.240
Authors: Miguel Souto; Lambert Raul Masip; Miguel Couto; Jorge Juan Suárez-Cuenca; Amparo Martínez; Pablo G Tahoces; Jose Martin Carreira; Pierre Croisille Journal: Diagnostics (Basel) Date: 2013-04-03