Efficient Monte Carlo Image Analysis for the Location of Vascular Entity
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Kei Ito | Shin Ishii | Shigeyuki Oba | Shin-ichi Maeda | Masanori Koyama | Marco Reisert | Henrik Skibbe
[1] Douglas B. Ehlenberger,et al. Rayburst sampling, an algorithm for automated three-dimensional shape analysis from laser scanning microscopy images , 2006, Nature Protocols.
[2] Guido Gerig,et al. Three-dimensional multi-scale line filter for segmentation and visualization of curvilinear structures in medical images , 1998, Medical Image Anal..
[3] Hans Burkhardt,et al. Harmonic Filters for Generic Feature Detection in 3D , 2009, DAGM-Symposium.
[4] Horst Bischof,et al. Segmentation of Airways Based on Gradient Vector Flow , 2009, MICCAI 2009.
[5] Heinz-Otto Peitgen,et al. Multiple hypothesis template tracking of small 3D vessel structures , 2010, Medical Image Anal..
[6] Xenophon Papademetris,et al. Vascular tree reconstruction by minimizing a physiological functional cost , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops.
[7] Jeroen J. Bax,et al. Automatic centerline extraction of coronary arteries in coronary computed tomographic angiography , 2011, The International Journal of Cardiovascular Imaging.
[8] Horst Bischof,et al. Multiscale Medialness for Robust Segmentation of 3 D Tubular Structures ∗ , 2005 .
[9] David Menotti,et al. A Semi-Automatic Method for Segmentation of the Coronary Artery Tree from Angiography , 2009, 2009 XXII Brazilian Symposium on Computer Graphics and Image Processing.
[10] Ju Lu,et al. The DIADEM Data Sets: Representative Light Microscopy Images of Neuronal Morphology to Advance Automation of Digital Reconstructions , 2011, Neuroinformatics.
[11] Kaleem Siddiqi,et al. Flux driven automatic centerline extraction , 2005, Medical Image Anal..
[12] Yoshiro Kitamura,et al. Automatic coronary extraction by supervised detection and shape matching , 2012, 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI).
[13] Josiane Zerubia,et al. Point processes for unsupervised line network extraction in remote sensing , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[14] H. Bischof,et al. Edge Based Tube Detection for Coronary Artery Centerline Extraction , 2008, The MIDAS Journal.
[15] Bipul Das,et al. Generic rebooting scheme and model-based probabilistic pruning algorithm for tree-like structure tracking , 2012, 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI).
[16] Armin Kanitsar,et al. Shape and Appearance Models for Automatic Coronary Artery Tracking , 2008, The MIDAS Journal.
[17] Nicholas Ayache,et al. Model-Based Detection of Tubular Structures in 3D Images , 2000, Comput. Vis. Image Underst..
[18] P. Green. Reversible jump Markov chain Monte Carlo computation and Bayesian model determination , 1995 .
[19] Ghassan Hamarneh,et al. VascuSynth: Simulating vascular trees for generating volumetric image data with ground-truth segmentation and tree analysis , 2010, Comput. Medical Imaging Graph..
[20] Theo van Walsum,et al. SEMI-AUTOMATIC CORONARY ARTERY CENTERLINE EXTRACTION IN COMPUTED TOMOGRAPHY ANGIOGRAPHY DATA , 2007, 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro.
[21] David A. Steinman,et al. A Framework for Geometric Analysis of Vascular Structures: Application to Cerebral Aneurysms , 2009, IEEE Transactions on Medical Imaging.
[22] Hüseyin Tek,et al. Robust Vessel Tree Modeling , 2008, MICCAI.
[23] Stephen R. Aylward,et al. Initialization, noise, singularities, and scale in height ridge traversal for tubular object centerline extraction , 2002, IEEE Transactions on Medical Imaging.
[24] Florent Lafarge,et al. Recovering Line-Networks in Images by Junction-Point Processes , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[25] Pascal Fua,et al. Automated Reconstruction of Dendritic and Axonal Trees by Global Optimization with Geometric Priors , 2011, Neuroinformatics.
[26] Anthony J. Yezzi,et al. Vessel Tractography Using an Intensity Based Tensor Model With Branch Detection , 2013, IEEE Transactions on Medical Imaging.
[27] Xin Wang,et al. Liver Vessel Segmentation Using Gradient Vector Flow , 2011, Bildverarbeitung für die Medizin.
[28] James V. Miller,et al. Adaptive intensity models for probabilistic tracking of 3D vasculature , 2010, 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.
[29] Roland Wilson,et al. Inferring Vascular Structure from 2D and 3D Imagery , 2001, MICCAI.
[30] Wiro J. Niessen,et al. Level set based cerebral vasculature segmentation and diameter quantification in CT angiography , 2006, Medical Image Anal..
[31] Fei Zhao,et al. Coronary artery tree tracking with robust junction detection in 3D CT Angiography , 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.
[32] Badrinath Roysam,et al. Robust 3-D Modeling of Vasculature Imagery Using Superellipsoids , 2007, IEEE Transactions on Medical Imaging.
[33] Martin Styner,et al. Standardized evaluation methodology and reference database for evaluating coronary artery centerline extraction algorithms , 2009, Medical Image Anal..
[34] Karl Rohr,et al. Robust segmentation of tubular structures in 3-D medical images by parametric object detection and tracking , 2003, IEEE Trans. Syst. Man Cybern. Part B.
[35] Isabelle Bloch,et al. A review of 3D vessel lumen segmentation techniques: Models, features and extraction schemes , 2009, Medical Image Anal..
[36] Milan Sonka,et al. Segmentation of Pulmonary Vascular Trees from Thoracic 3D CT Images , 2009, Int. J. Biomed. Imaging.
[37] Wei Tsang Ooi,et al. A Stochastic Model for Automatic Extraction of 3D Neuronal Morphology , 2013, MICCAI.
[38] G. Funka-Lea,et al. Author ' s personal copy A review of 3 D vessel lumen segmentation techniques : Models , features and extraction schemes , 2009 .
[39] Horst Bischof,et al. A Novel Approach for Detection of Tubular Objects and Its Application to Medical Image Analysis , 2008, DAGM-Symposium.
[40] W. K. Hastings,et al. Monte Carlo Sampling Methods Using Markov Chains and Their Applications , 1970 .
[41] Alejandro F. Frangi,et al. Automated segmentation of cerebral vasculature with aneurysms in 3DRA and TOF-MRA using geodesic active regions: an evaluation study. , 2010, Medical physics.
[42] Susanne Schnell,et al. Global fiber reconstruction becomes practical , 2011, NeuroImage.
[43] Alejandro F. Frangi,et al. Muliscale Vessel Enhancement Filtering , 1998, MICCAI.
[44] Alejandro F. Frangi,et al. Automated landmarking and geometric characterization of the carotid siphon , 2012, Medical Image Anal..
[45] Tianxu Zhang,et al. Marked Point Process for Vascular Tree Extraction on Angiogram , 2007, EMMCVPR.
[46] S. Pizer,et al. Intensity ridge and widths for tubular object segmentation and description , 1996, Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis.
[47] Yefeng Zheng,et al. Robust and Accurate Coronary Artery Centerline Extraction in CTA by Combining Model-Driven and Data-Driven Approaches , 2013, MICCAI.
[48] Alejandro F. Frangi,et al. Image intensity standardization in 3D rotational angiography and its application to vascular segmentation , 2008, SPIE Medical Imaging.
[49] N. Metropolis,et al. Equation of State Calculations by Fast Computing Machines , 1953, Resonance.
[50] Karl Rohr,et al. Segmentation and Quantification of Human Vessels Using a 3-D Cylindrical Intensity Model , 2007, IEEE Transactions on Image Processing.