Jia Y Y, Zhuang T G. Applying improved fast marching method to endocardial boundary detection in echocardiographic images. Pattern Recognition Letters, 2003, 24(15): 2777-2784
[2]
Descoteaux M, Collins L, Siddiqi K. A Multi-scale Geometric Flow for Segmenting Vasculature in MRI. Berlin: Springer-Verlag, 2004. 169-180
[3]
Mohammadi A, Asif A. Distributed particle filter implementation with intermittent/irregular consensus convergence. IEEE Transactions on Signal Processing, 2013, 61(10): 2572-2587
[4]
Florin C, Paragios N, Williams J. Globally optimal active contours, sequential Monte Carlo and on-line learning for vessel segmentation. In: Proceedings of the European Conference on Computer Vision-ECCV 2006. Graz, Austria: Springer, 2006. 476-489
[5]
Liu Song-Tao, Yin Fu-Liang. The basic principle and its new advances of image segmentation methods based on graph cuts. Acta Automatica Sinica, 2012, 32(1): 911-922(刘松涛, 殷福亮. 基于图割的图像分割方法及其新进展. 自动化学报, 2012, 32(1): 911-922)
[6]
Schaap M, van Walsum T, Neefjes L, Metz C, Capuano E, de Bruijne M, Niessen W. Robust shape regression for supervised vessel segmentation and its application to coronary segmentation in CTA. IEEE Transactions on Medical Imaging, 2011, 30(11): 1974-1986
[7]
Lin Q F. Enhancement, Extraction, and Visualization of 3D Volume Data [Ph.D. dissertation], Link？ping University, Sweden: 2003
[8]
Diciotti S, Lombardo S, Falchini M, Picozzi G, Mascalchi M. Automated segmentation refinement of small lung nodules in CT scans by local shape analysis. IEEE Transactions on Biomedical Engineering, 2011, 58(12): 3418-3428
[9]
Maurer C R, Qi R, Raghavan V. A linear time algorithm for computing exact Euclidean distance transforms of binary images in arbitrary dimensions. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003, 25(2): 265-270
[10]
Palá
[11]
gyi K. A 3D fully parallel surface-thinning algorithm. Theoretical Computer Science, 2008, 406(1-2): 119-135
[12]
Tang H, van Walsum T, van Onkelen R S, Hameeteman R, Klein S, Schaap M, Tori FL, van den Bouwhuijsen Q J, Witteman J C, van der Lugt A, van Vliet L J, Niessen W J. Semiautomatic carotid lumen segmentation for quantification of lumen geometry in multi-spectral MRI.
[13]
Hassouna M S, Faragand A A. Variational curve skeletons using gradient vector flow. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2009, 31(12): 2257-2274
[14]
Bouix S, Siddiqi K, Tannenbaum A. Flux driven automatic centerline extraction. Medical Image Analysis, 2005, 9(3): 209-221
[15]
Liu Wen-Yu, Bai Xiang, Zhu Guang-Xi. A skeleton-growing algorithm based on boundary curve evolution. Acta Automatica Sinica, 2008, 32(1): 255-262(刘文予, 白翔, 朱光喜. 基于边界曲线演化模型的生长骨架算法. 自动化学报, 2006, 32(1): 255-262)
[16]
Friman O, Hindennach M, Kü
[17]
Li H, Yezzi A. Vessels as 4D curves: Global minimal 4D paths to extract 3D tubular surfaces and centerlines. IEEE Transactions on Medical Imaging, 2007, 26(9): 1213-1223
[18]
Battagliero S, Puglia G, Vicario S, Rubino F, Scioscia G, Leo P. An efficient algorithm for approximating geodesic distances in tree space. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2011, 8(5): 1196-1207
[19]
Friman O, Hindennach M, Peitgen H O. Template-based multiple hypotheses tracking of small vessels. In: Proceedings of the 5th IEEE International Symposium on Biomedical Imaging. Paris, France: IEEE, 2008. 1047-1050
[20]
Jaeyoun Y, Jong B R. A locally adaptive region growing algorithm for vascular segmentation. Journal of Imaging Systems and Technology, 2003, 13(4): 208-214
[21]
Mille J, Boné R, Cohen L D. Region-based 2D deformable generalized cylinder for narrow structures segmentation. In: The European Conference on Computer Vision-ECCV 2008. Marseille, France: Springer, 2008. 392-404
[22]
Mille J, Cohen L D. Deformable tree models for 2D and 3D branching structures extraction. In: Proceedings of the Computer Vision and Pattern Recognition Workshops-CVPR2009. Miami, USA: IEEE, 2009. 149-156
[23]
Kimmel R, Bruckstein A M. Regularized Laplacian zero crossings as optimal edge integrators. International Journal of Computer Vision, 2003, 53(3): 225-243
[24]
Allen K, Yau C, Noble J. A recursive, stochastic vessel segmentation framework that robustly handles bifurcations. In: Proceedings of Medical Image Understanding and Analytics. Dundee, England: 2008
[25]
Han Shou-Dong, Zhao Yong, Tao Wen-Bing, Sang Nong. Gaussian super-pixel based fast image segmentation using graph cuts. Acta Automatica Sinica, 2011, 32(1): 11-20(韩守东, 赵勇, 陶文兵, 桑农. 基于高斯超像素的快速Graph Cuts图像分割方法. 自动化学报, 2011, 32(1): 11-20)
[26]
Frangi A F, Niessen W J, Vincken K L, Viergever M A. Multi-scale vessel enhancement filtering. In: Proceedings of the 1st International Conference on Medical Image Computing and Computer-assisted Intervention-MICCAI1998. Cambridge, England: Springer, 1998. 130-137
[27]
Bauer C, Pock T, Sorantin E, Bischof H, Beichel R. Segmentation of interwoven 3D tubular tree structures utilizing shape priors and graph cuts. Medical Image Analysis, 2010, 14(2): 172-184
[28]
Liu Jun-Tao, Liu Wen-Yu, Wu Cai-Hua, Yuan Liang. A new method of extracting object curve-skeleton. Acta Automatica Sinica, 2008, 32(1): 617-622(刘俊涛, 刘文予, 吴彩华, 原亮. 一种提取物体线形骨架的新方法. 自动化学报, 2008, 32(1): 617-622)
[29]
Hesselink W H, Roerdink J B. Euclidean skeletons of digital image and volume data in linear time by the integer medial axis transform. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2008, 30(12): 2204-2217
[30]
Medical Image Analysis, 2012, 16(6): 1202-1215
[31]
Xu Y, Zhang H, Li H, Hu G S. An improved algorithm for vessel centerline tracking in coronary angiograms. Computer Methods and Programs in Biomedicine, 2007, 88(2): 131-143
[32]
W？rz S, Rohr K. A new 3D parametric intensity model for accurate segmentation and quantification of human vessels. In: Proceedings of the 7th International Conference on Medical Image Computing and Computer-Assisted Intervention-MICCAI2004. Saint-Malo, France: Springer, 2004. 491-499
[33]
W？rz S, Rohr K. Segmentation and quantification of human vessels using a 3D cylindrical intensity model. IEEE Transactions on Image Processing, 2007, 16(8): 1994-2004
[34]
hnel, Peitgen H O. Multiple hypothesis template tracking of small 3D vessel structures. Medical Image Analysis, 2010, 14(2): 160-171
[35]
Kang D G, Suh D C, Ra J B. Three-dimensional blood vessel quantification via centerline deformation. IEEE Transactions on Medical Imaging, 2009, 28(3): 405-414
[36]
Bharath R S, Ramanathan M. The shortest path in a simply-connected domain having a curved boundary. Computer-Aided Design, 2011, 43(8): 923-933
