參考文獻 |
1. A. Andreopoulos and Tsotsos, J.K., "Efficient and generalizable statistical models of shape and appearance for analysis of cardiac MRI," Medical Image Analysis, vol. 12, no. 3, pp. 335-357, 2008.
2. K.K. Shyu, V.T. Pham, T.T. Tran, and P.L. Lee, "Unsupervised active contours driven by density distance and local fitting energy with applications to medical image segmentation," Machine Vision and Applications, vol. 23, no. 6, pp. 1159-1175, 2012.
3. L. He, Peng, Z., Everding, B., Wang, X., Han, C., Weiss, K., and Wee, W. G., "A comparative study of deformable contour methods on medical image segmentation," Image Vision Comput., vol. 26, no. 2, pp. 141-163, 2008.
4. D. Cremers, M. Rousson, and R. Deriche, "A review of statistical approaches to level set segmentation: Integrating color, texture, motion and shape," International Journal of Computer Vision, vol. 72, no. 2, pp. 195-215, 2007.
5. M. Kass, A. Witkin, and D. Terzopoulos, "Snakes: Active contour models," International Journal of Computer Vision, vol. 1, no. 4, pp. 321-331, 1988.
6. V.T. Pham, T.T. Tran, Y.J. Chiu, and K.K. Shyu, "Region-aided Geodesic Active Contour Model for Image Segmentation," in: Proc. of the 3rd IEEE International Conference on Computer Science and Information Technology, 2010. pp. 318-321.
7. S. Osher and R. Fedkiw, Level Set Methods and Dynamic Implicit Surfaces, Springer-Verlag, New York, 2002.
8. T.T Tran, V.T. Pham, and K.K. Shyu, "Zernike Moment and Local Distribution Fuzzy Energy based Active Contours for Image Segmentation," Signal, Image and Video Processing, vol. 8, no. 1, pp. 11-25, 2012.
9. R. Ronfard, "Region-based strategies for active contour models," International Journal of Computer Vision, vol. 13, no. 2, pp. 229-251, 1994.
10. T. Chan and L. Vese, "Active contours without edges," IEEE Trans. Image Processing, vol. 10, no. 2, pp. 266-277, 2001.
11. V. Caselles, F. Catte, T. Coll, and F. Dibos, "A geometric model for active contours in image processing," Numerische Mathematik, vol. 66, no. 1, pp. 1-31, 1993.
12. V. Caselles, R. Kimmel, and G. Sapiro, "Geodesic active contours," International Journal of Computer Vision, vol. 22, no. 1, pp. 61-79, 1997.
13. D. Mumford and J. Shah, "Optimal approximations by piecewise smooth functions and associated variational problems," Communication on Pure and Applied Mathematics vol. 42, no. 5, pp. 577-685, 1989.
14. I.B. Ayed, S. Li, and I. Ross, "Level set image segmentation with a statistical overlap constraint.," in: Proc. of Information Processing in Medical Imaging (IPMI), 2009. pp. 589-601.
15. K. Ni, X. Bresson, T. Chan, and S. Esedoglu, "Local histogram based segmentation using the Wasserstein distance," International Journal of Computer Vision, vol. 84, no. 1, pp. 97-111, 2009.
16. S. Krinidis and V. Chatzis, "Fuzzy energy-based active contour," IEEE Trans. Image Processing, vol. 18, no. 12, pp. 2747-2755, 2009.
17. K.K. Shyu, T.T. Tran, V.T. Pham, P.L. Lee, and L.J. Shang, "Fuzzy distribution fitting energy-based active contours for image segmentation," Nonlinear Dynamics, vol. 69, no. 1-2, pp. 295-312, 2012.
18. O. Bernard, Friboulet, D., Thevenaz, P., and Unser, M., "Variational B-Spline Level-Set: A Linear Filtering Approach for Fast Deformable Model Evolution," IEEE Trans. Image Processing, vol. 18, no. 6, pp. 1179-1191, 2009.
19. C. Li, C. Kao, C. Gui, and M.D. Fox, "Level set evolution without re-inittialization," in: Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2005. pp. 430-436.
20. B. Song and T. Chan, A Fast Algorithm for Level Set Based Optimization, in UCLA CAM Report 02-68. 2002.
21. K.K. Shyu, V.T. Pham, T.T. Tran, and P.L. Lee, "Global and local fuzzy energy based-active contours for image segmentation," Nonlinear Dynamics, vol. 67, no. 2, pp. 1559-1578, 2012.
22. Y. Chen, Tagare, H.D., Thiruvenkadam, S., Huang, F., Wilson, D., Gopinath, K.S., Briggs, R.W., Geiser, E.A., and . "Using prior shapes in geometric active contours in a variational framework," International Journal of Computer Vision, vol. 50, no. 3, pp. 315-328, 2002.
23. M. Rousson and Paragios, N., "Shape priors for level set representations," in: Proc. of European Conference in Computer Vision (ECCV), Copenhagen, Denmark, 2002. pp. 78–92.
24. T. Chan and Zhu, W., "Level set based shape prior segmentation," in: Proc. of Computer Vision and Pattern Recognition (CVPR), San Diego, CA, USA, 2005. pp. 1164-1170.
25. T.T Tran, Pham, V.T., and Shyu, K.K., "Image Segmentation using Fuzzy Energy-based Active Contour with Shape Prior," J. Visual Commun. Image Represent. , vol. 25, no. 7, pp. 1732–1745, 2014.
26. D. Cremers, Kohlberger, T., and Schnorr, C., "Shape statistics in kernel space for variational image segmentation," Pattern Recognition, vol. 36, no. 9, pp. 1929-1943, 2003.
27. D. Cremers, Osher, S.J., and Schnorr, C., "Kernel density estimation and intrinsic alignment for shape priors in level set segmentation," International Journal of Computer Vision, vol. 69, no. 3, pp. 335-351, 2006.
28. T.T Tran, V.T. Pham, and K.K. Shyu, "Moment-based Alignment for Shape Prior with Variational B-Spline Level Set," Machine Vision and Applications, vol. 24, no. 5, pp. 1075-1091, 2013.
29. J.G. Leu, "Shape normalization through compacting," Patten Recognition Letters, vol. 10, no. 4, pp. 243-250, 1989.
30. S. Pei and Lin, C., "Normalization of Rotationally Symmetric Shapes for Pattern Recognition," Pattern Recognition, vol. 25, no. 9, pp. 913-920, 1992.
31. A. Blake and M. Isard, Active Contours, Springer, Cambridge, 1998.
32. S. Osher and J.A. Sethian, "Fronts propagating with curvature dependent speed: algorithms based on Hamilton–Jacobi formulation," Journal of Computational Physics, vol. 79, no., pp. 12-49, 1988.
33. J.A. Sethian, Level Set Methods and Fast Marching Methods, Cambridge University Press, Cambridge, 1999.
34. S. Osher and N. Paragios, "Level Set Methods", in Geometric Level Set Methods in Imaging, Vision and Graphics, Springer-Verlag NY, 2003.
35. C. Li, C. Kao, J.C. Gore, and Z. Ding, "Minimization of region-scalable fitting energy for image segmentation," IEEE Trans. Image Processing, vol. 17, no. 10, pp. 1940-1949, 2008.
36. T.T. Tran, V.T. Pham, Y.J. Chiu, and K.K. Shyu, "Image Segmentation based on Geodesic aided Chan-Vese Model," in: Proc. of the 3rd IEEE International Conference on Computer Science and Information Technology, 2010. pp. 315-317.
37. T.T. Tran, V.T. Pham, Y.J. Chiu, and K.K. Shyu, "Active Contour with Selective Local or Global Segmentation for Intensity Inhomogeneous Image," in: Proc. of the 3rd IEEE International Conference on Computer Science and Information Technology, 2010. pp. 306-310.
38. R. Malladi and J. Sethian, "Image processing via level set curvature flow," in: Proc. of National Academy of Science, 1995. pp. 7046–7050.
39. R. Malladi, J. Sethian, and C. Vemuri, "Shape modeling with front propagation: a level set approach," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 17, no. 2, pp. 158-175, 1995.
40. A. Yezzi, S. Kichenassamy, A. Kumar, P. Olver, and A. Tannenbaum, "A geometric snake model for segmentation of medical imagery," IEEE Trans. Medical Imaging, vol. 16, no. 2, pp. 199-209, 1997.
41. L.D. Cohen, "On Active Contour Models and Balloons," Computer Vision Graphics Image Processing, vol. 53, no. 2, pp. 211-218, 1991.
42. S. Kichenassamy, A. Kumar, P. Olver, A. Tannenbaum, and A. Yezzi, "Gradient flows and geometric active contour models," in: Proc. of IEEE International Conference on Computer Vision, 1995. pp. 810-815.
43. G. Sapiro, "Color snakes," Computer Vision and Image Understanding, vol. 68, no. 2, pp. 247-253, 1997.
44. A. Tsai, A. Yezzi, and A.S. Willsky, "Curve evolution implementation of the Mumford-Shah functional for image segmentation, denoising, interpolation, and magnification," IEEE Trans. Image Processing, vol. 10, no. 8, pp. 1169-1186, 2001.
45. L. Vese and T. Chan, "A multiphase level set framework for image segmentation using the Mumford and Shah model," International Journal of Computer Vision, vol. 50, no. 3, pp. 271-293, 2002.
46. L. He, S. Zheng, and L. Wang, "Integrating local distribution information with level set for boundary extraction," Journal of Visual Communication and Image Representation vol. 21, no. 4, pp. 343-354, 2010.
47. M. Unser, "Splines: A perfect fit for signal and image processing," IEEE Signal Processing Magazine, vol. 16, no. 6, pp. 22-38, 1999.
48. J Kybic and Unser, M, "Fast parametric elastic image registration," IEEE Trans. Image Processing, vol. 12, no. 11, pp. 1427-1442, 2003.
49. M.K. Hu, "Visual pattern recognition by moments invariants," IRE Trans. Information Theory, vol. 8, no. 1, pp. 179-187, 1962.
50. S. Pei and Lin, C., "Image normalization for pattern recognition," Image and Vision computing, vol. 13, no. 10, pp. 711-723, 1995.
51. X.H. Wang and Zhao, R.C., "A new method for image normalization," in: Proc. of international symposium on intelligent multimedia, video, and speech processing, Hong Kong, 2001. pp. 356-359.
52. M.R. Teague, "Image analysis via the general theory of moments," J. Opt. Soc. Am. , vol. 70, no. 8, pp. 920-930, 1980.
53. X. Xie and Mirmehdi, M., "MAC: Magnetostatic Active Contour Model," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 30, no. 4, pp. 632-646, 2008.
54. S. Lankton and A. Tannenbaum, "Localizing region-based active contour," IEEE Trans. Image Processing, vol. 17, no. 11, pp. 2029-2039, 2008.
55. A. Yezzi, A. Tsai, and A. Willsky, "A fully global approach to image segmentation via coupled curve evolution equations," Journal of Visual Communication and Image Representation, vol. 13, no. 1, pp. 195-216, 2002.
56. O. Michailovich, Y. Rathi, and A. Tannenbaum, "Image segmentation using active-contours driven by the Bhattacharyya gradient flow," IEEE Trans. Image Processing, vol. 16, no. 11, pp. 2787-2801, 2007.
57. M. Rousson and R. Deriche, "A variational framework for active and adaptive segmentation of vector valued images," in: Proc. of IEEE Workshop on Motion and Video Computing, 2002. pp.
58. J. Gomes and Faugeras, O., "Reconciling distance functions and level sets," Journal of Visual Communication and Image Representation, vol. 11, no. 2, pp. 209-223, 2000.
59. N. Xu, R. Bansal, and N. Ahuja, "Object segmentation using graph cuts based active contours," in: Proc. of IEEE International Conference Computer Vision and Pattern Recognition(CVPR), Madison, Wisconsin, USA, 2003. pp. 46-53.
60. N. Xu, N. Ahuja, and R. Bansal, "Object segmentation using graph cuts based active contours.," Computer Vision Image Understanding, vol. 107, no. 3, pp. 210-224, 2007.
61. F. Gibou and R. Fedkiw, "A fast hybrid k-means level set algorithm for segmentation," in: Proc. of 4th Annual Hawaii International Conference on Statistics and Mathematics, Honolulu, Hawaii, USA, 2005. pp. 281-291.
62. X. Bresson, Vandergheynst, P., and Thiran, J.P., "A variational model for object segmentation using boundary information and shape prior driven by the Mumford-Shah functional," International Journal of Computer Vision, vol. 28, no. 2, pp. 145-162, 2006.
63. T. Riklin-Raviv, Kiryati, N., and Sochen, N., "Prior-based Segmentation and Shape Registration in the Presence of Projective Distortion," International Journal of Computer Vision, vol. 72, no. 3, pp. 309-328, 2007.
64. M. Leventon, Grimson, E., and Faugeras, O., "Statistical shape influence in geodesic active contours," in: Proc. of Computer Vision and Pattern Recognition (CVPR), Hilton Head Island, SC , USA 2000. pp. 316-323.
65. A. Tsai, Yezzi, A., Wells, W., Temany, C., Tucker, D., Fan, A., Grimson, W.E., and Willsky, A., " A shape-based approach to the segmentation of medical imagery using level sets," IEEE Trans. Medical Imaging, vol. 22, no. 2, pp. 137-154, 2003.
66. S. Dambreville, Y. Rathi, and Tannenbaum, A., "A Framework for Image Segmentation Using Shape Models and Kernel Space Shape Priors," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 30, no. 8, pp. 1385-1399, 2008.
67. N. Vu and Manjunath, B.S., "Shape prior segmentation of multiple objects with graph cuts," in: Proc. of Computer Vision and Pattern Recognition (CVPR), Anchorage, AK 2008. pp.
68. S. Dambreville, Y. Rathi, and Tannenbaum, A., "A shape-based approach to robust image segmentation," in: Proceedings of the Third international conference on Image Analysis and Recognition, 2006. pp.
69. M. Hansson, Fundana, K., S. Brandt, S., and Gudmundsson, P., "Convex spatio-temporal segmentation of the endocardium in ultrasound data using distribution and shape priors," in: Proceedings of IEEE Symposium on Biomedical Imaging, 2011. pp. 626 - 629
70. M. Morse, Liu, W., Yoo, T., and Subramanian, K., "Active Contours Using a Constraint-Based Implicit Representation," in: Proc. of Computer Vision and Pattern Recognition (CVPR), New York, 2005. pp.
71. A. Gelas, Bernard, O., Friboulet, D., and Prost, R., "Compactly supported radial basic functions based collocation method for level set evolution in image segmentation," IEEE Trans. Image Processing, vol. 16, no. 7, pp. 1873-1887, 2007.
72. H.E. Munim and Farag, A.A., "Curve/surface representation and evolution using vector level set with application to the shape-based segmentation problem," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 29, no. 6, pp. 945-958, 2007.
73. N. Paragios, Rousson, M., and Ramesh, V., "Matching distance functions a shape-to area variational approach for global-to-local registration," in: Proc. of European Conference in Computer Vision (ECCV), Copenhagen, Denmark, 2002. pp. 775-789.
74. J. Yang and Duncan, J.S., "3D image segmentation of deformable objects with joint shape-intensity prior models using level sets," Medical Image Analysis, vol. 8, no. 3, pp. 285-294, 2004.
75. M. Rousson and Paragios, N., "Prior knowledge, level set representation & visual grouping," International Journal of Computer Vision, vol. 76, no. 3, pp. 231-243, 2008.
76. A. Foulonneau, Charbonnier, P., and Heitz, F., "Affine-invariant geometric shape priors for region-based active contours," IEEE Trans. Pattern Analysis and Machine Intelligence vol. 28, no. 8, pp. 1352-1357, 2006.
77. W. Liu, Shang, Y., Yang, X., Deklerck, R., and Cornelis, J., "A shape prior constraint for implicit active contours," Patten Recognition Letters, vol. 32, no. 15, pp. 1937-1947, 2011.
78. J Tohka, "Surface extraction from volumetric images using deformable meshes: a comparative study," in: Proc. of the seventh European Conference in Computer Vision (ECCV), Copenhagen, Denmark, 2002. pp. 350-364.
79. N Paragios, "A variational approach for the segmentation of the left ventricle in cardiac image analysis," Int J Comput Vis, vol. 50, no. 3, pp. 345-362, 2002.
80. T. Cootes, Taylor, C., Cooper, D., and Graham, J., "Active shape models-their training and application," Comput Vis Image Understand, vol. 61, no. 1, pp. 38-59, 1995.
81. D. Ross, Lim, J., Lin, R.-S., and Yang, M.-H., "Incremental learning for robust visual tracking," Int J Comput Vis, vol. 77, no. 1, pp. 125-141, 2008.
82. A. Levy and Lindenbaum, M., "Sequential Karhunen–Loeve basis extraction and its application to images," IEEE Trans Image Process, vol. 9, no. 8, pp. 1371–1374, 2000.
83. G. Aubert, Barlaud, M., Faugeras, O., and Jehan-Besson, S., "Image segmentation using active contours: Calculus of variations or shape gradients?," SIAM Appl Math, vol. 63, no. 6, pp. 2128-2154, 2003.
84. J.-H. Woo, Slomka, P., Kuo, J., and Hong, B.-W., "Multiphase segmentation using an implicit dual shape prior: Application to detection of left ventricle in cardiac MRI," Comput. Vis. and Image Understand., vol. 117, no. 9, pp. 1084-1094, 2013.
85. JM Bland and Altman, DG, "Statiscal methods for assessing agreement between two methods of clinical measurements," Lancet 1, vol., no., pp. 307-310, 1986. |