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Yen-Wen Wu, E. Tadamura, S. Kanao, Masaki Yamamuro, Satoshi Okayama, N. Ozasa, M. Toma, Takeshi Kimura, T. Kita, A. Marui, M. Komeda, K. Togashi (2007)
Left Ventricular Functional Analysis Using 64-Slice Multidetector Row Computed Tomography: Comparison with Left Ventriculography and Cardiovascular Magnetic ResonanceCardiology, 109
Yefeng Zheng, Adrian Barbu, B. Georgescu, M. Scheuering, D. Comaniciu (2008)
Four-Chamber Heart Modeling and Automatic Segmentation for 3-D Cardiac CT Volumes Using Marginal Space Learning and Steerable FeaturesIEEE Transactions on Medical Imaging, 27
L. Grady, G. Funka-Lea (2004)
Multi-label Image Segmentation for Medical Applications Based on Graph-Theoretic Electrical Potentials
P. Wighton, Maryam Sadegh, Tim Lee, M. Atkins, Simon Fraser (2009)
A Fully Automatic Random Walker Segmentation for Skin Lesions in a Supervised SettingMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 12 Pt 2
R. Geest, J. Reiber (1999)
Quantification in cardiac MRIJournal of Magnetic Resonance Imaging, 10
L. Grady (2006)
Random Walks for Image SegmentationIEEE Transactions on Pattern Analysis and Machine Intelligence, 28
Yang Lu, Zhijun Cai, Ge Wang, Jun Zhao, E. Bai (2009)
Preliminary experimental results on controlled cardiac computed tomography: a phantom study.Journal of X-ray science and technology, 17 2
L. Sugeng, V. Mor-Avi, L. Weinert, J. Niel, C. Ebner, R. Steringer‐Mascherbauer, F. Schmidt, Christian Galuschky, G. Schummers, R. Lang, H. Nesser (2006)
Quantitative Assessment of Left Ventricular Size and Function: Side-by-Side Comparison of Real-Time Three-Dimensional Echocardiography and Computed Tomography With Magnetic Resonance ReferenceCirculation, 114
S. Dakua, J. Sahambi (2009)
LV Contour Extraction from Cardiac MR Images Using Random Walks Approach2009 IEEE International Advance Computing Conference
J. Earls, E. Berman, B. Urban, C. Curry, J. Lane, R. Jennings, C. McCulloch, J. Hsieh, J. Londt (2008)
Prospectively gated transverse coronary CT angiography versus retrospectively gated helical technique: improved image quality and reduced radiation dose.Radiology, 246 3
P. Pattynama, H. Lamb, E. Velde, E. Wall, A. Roos (1993)
Left ventricular measurements with cine and spin-echo MR imaging: a study of reproducibility with variance component analysis.Radiology, 187 1
S. Busch, T. Johnson, B. Wintersperger, N. Minaifar, A. Bhargava, C. Rist, M. Reiser, C. Becker, Konstantin Nikolaou (2008)
Quantitative assessment of left ventricular function with dual-source CT in comparison to cardiac magnetic resonance imaging: initial findingsEuropean Radiology, 18
S. Raman, M. Shah, B. Mccarthy, Anne Garcia, A. Ferketich (2006)
Multi-detector row cardiac computed tomography accurately quantifies right and left ventricular size and function compared with cardiac magnetic resonance.American heart journal, 151 3
T. Karamitsos, J. Francis, S. Myerson, J. Selvanayagam, S. Neubauer (2009)
The role of cardiovascular magnetic resonance imaging in heart failure.Journal of the American College of Cardiology, 54 15
B. Chow, G. Wells, Li Chen, Yeung Yam, P. Galiwango, A. Abraham, T. Sheth, C. Dennie, R. Beanlands, T. Ruddy (2010)
Prognostic value of 64-slice cardiac computed tomography severity of coronary artery disease, coronary atherosclerosis, and left ventricular ejection fraction.Journal of the American College of Cardiology, 55 10
S. Dakua, J. Sahambi (2010)
Automatic Left Ventricular Contour Extraction from Cardiac Magnetic Resonance Images Using Cantilever Beam and Random Walk ApproachCardiovascular Engineering, 10
D. Kitzman, W. Little, P. Brubaker, Roger Anderson, W. Hundley, C. Marburger, B. Brosnihan, T. Morgan, K. Stewart (2002)
Pathophysiological characterization of isolated diastolic heart failure in comparison to systolic heart failure.JAMA, 288 17
Yu-Kun Lai, Shimin Hu, Ralph Martin, Paul Rosin (2009)
Rapid and effective segmentation of 3D models using random walksComput. Aided Geom. Des., 26
Yang-Hsien Lin, Yung-Hui Huang, Kang-Ping Lin, Juhn‐Cherng Liu, Tzung-Chi Huang (2014)
Ventricular hemodynamics using cardiac computed tomography and optical flow method.Journal of X-ray science and technology, 22 1
L. Grady, T. Schiwietz, S. Aharon, R. Westermann (2005)
Random Walks for Interactive Organ Segmentation in Two and Three Dimensions: Implementation and ValidationMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 8 Pt 2
J. Berg, C. Lorenz (2005)
Multi-surface Cardiac Modelling, Segmentation, and Tracking
R. Bhatia, J. Tu, J. Tu, Douglas Lee, P. Austin, Jiming Fang, A. Haouzi, Y. Gong, Peter Liu, Peter Liu (2006)
Outcome of heart failure with preserved ejection fraction in a population-based study.The New England journal of medicine, 355 3
T. McInerney, Demetri Terzopoulos (1995)
A dynamic finite element surface model for segmentation and tracking in multidimensional medical images with application to cardiac 4D image analysis.Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society, 19 1
G. Mühlenbruch, M. Das, C. Hohl, J. Wildberger, D. Rinck, T. Flohr, R. Koos, C. Knackstedt, R. Günther, A. Mahnken (2006)
Global left ventricular function in cardiac CT. Evaluation of an automated 3D region-growing segmentation algorithmEuropean Radiology, 16
K. Juergens, H. Seifarth, F. Range, S. Wienbeck, M. Wenker, W. Heindel, R. Fischbach (2008)
Automated threshold-based 3D segmentation versus short-axis planimetry for assessment of global left ventricular function with dual-source MDCT.AJR. American journal of roentgenology, 190 2
PURPOSE: Segmentation of the left ventricle (LV) in cardiac CT (CCT) images is difficult due to the intensity heterogeneity arising from accumulation of contrast agent in papillary muscle and trabeculae carneae. In this study, we demonstrated the random walks method for LV segmentation in CCT through cardiac phases. METHODS: 63 CCT data sets from 7 patients with 9 cardiac phases were included in this study. All cardiac CT examinations were performed with GE 64-detector CT scanner with ECG gating. In each patient, 60–80 ml iohexol was injected at a flow rate of 5 ml/sec followed by 60 ml normal saline solution. Random walks (RW) based on probability of labels was used for LV segmentation. The LV delineations generated by the experienced physician (MD), conventional image-based method (IB), and RW were compared. RESULTS: In general the contours segment the LV closely by RW and MD, but the discrepancies in papillary muscle and trabeculae carneae were observed while using the IB method. CONCLUSION: We showed the RW method potentially improved LV segmentation as compared to the volume by conventional IB method. In this study, we demonstrated the clinical feasibility of LV volume segmentation using random walks algorithm.
Journal of X-Ray Science and Technology – IOS Press
Published: Jan 1, 2015
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