A multiple object geometric deformable model for image segmentation

Computer Vision and Image Understanding

Volumn 117, Issue 2, 2013, Pages 145-157

  Bogovic, John A ^a   Prince, Jerry L ^a   Bazin, Pierre Louis ^b  

^a JOHNS HOPKINS UNIVERSITY   (United States)

^b MAX PLANCK INSTITUTE FOR HUMAN COGNITIVE AND BRAIN SCIENCES   (Germany)

Author keywords

Geometric deformable model; Level sets; Multiple object segmentation; Topology preservation

Indexed keywords

DEFORMATION; MEDICAL IMAGING; TOPOLOGY;

COMPUTATIONALLY EFFICIENT; GEOMETRIC DEFORMABLE MODELS; LEVEL SET; MULTIPLE COMPARTMENTS; MULTIPLE OBJECTS; OBJECT REPRESENTATIONS; PERFORMANCE AND SCALABILITIES; TOPOLOGY PRESERVATION;

IMAGE SEGMENTATION;

EID: 84879854436     PISSN: 10773142     EISSN: 1090235X     Source Type: Journal    
DOI: 10.1016/j.cviu.2012.10.006     Document Type: Article

References (55)

1. B. Fischl, D. H. Salat, E. Busa, M. Albert, M. Dieterich, C. Haselgrove, A. Van der Kouwe, R. Killiany, D. Kennedy, S. Klaveness, A. Montillo, N. Makris, B. Rosen, A. M. Dale, Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain, Neuron 33 (3) (2002) 341-355. (Pubitemid 34162530)
2. T. Okada, R. Shimada, Y. Sato, M. Hori, K. Yokota, M. Nakamoto, Y.-W. Chen, H. Nakamura, S. Tamura, Automated segmentation of the liver from 3D CT images using probabilistic atlas and multi-level statistical shape model, Proc. MICCAI 10 (2007) 86-93.
3. V. Spitzer, M. J. Ackerman, A. L. Scherzinger, D. Whitlock, The visible human male: a technical report, JAMIA 3 (1996) 118-130. (Pubitemid 126445016)
4. T. Heimann, S. Münzing, H.-P. Meinzer, I. Wolf, A shape-guided deformable model with evolutionary algorithm initialization for 3D soft tissue segmentation, Proc. IPMI (2007) 1-12.
5. C. Lu, S. M. Pizer, S. Joshi, J.-Y. Jeong, Statistical multi-object shape models, Int. J. Comput. Vision 75 (3) (2007) 387-404. (Pubitemid 47383857)
6. P.-L. Bazin, D. L. Pham, Homeomorphic brain image segmentation with topological and statistical atlases, Med. Image Anal. 12 (5) (2008) 616-625.
7. O. Debeir, P. Van Ham, R. Kiss, C. Decaestecker, Tracking of migrating cells under phase-contrast video microscopy with combined mean-shift processes, IEEE TMI 24 (6) (2005) 697-711. (Pubitemid 40850522)
8. D. Padfield, J. Rittscher, B. Roysam, Coupled minimum-cost flow cell tracking, in: IPMI, vol. 21, 2009, pp. 374-85.
9. M. Kass, A. Witkin, D. Terzopoulos, Snakes: active contour models, Int. J. Comput. Vision 1 (1988) 321-331.
10. J. A. Sethian, Level Set Methods and Fast Marching Methods, Cambridge University Press, Cambridge, UK, 1999.
11. S. J. Osher, R. Fedkiw, Level Set Methods and Dynamic Implicit Surfaces, Springer, New York, 2003.
12. X. Han, C. Xu, J. L. Prince, A topology preserving level set method for geometric deformable models, IEEE Trans. Pattern Anal. Mach. Intell. 25 (6) (2003) 755-768.
13. F. Ségonne, Active contours under topology control - genus preserving level sets, Int. J. Comput. Vision 79 (2) (2007) 107-117.
14. G. Sundaramoorthi, A. Yezzi, Global regularizing flows with topology preservation for active contours and polygons, IEEE Trans. Image Process. 16 (3) (2007) 803-812. (Pubitemid 46431975)
15. L. A. Vese, T. F. Chan, A multiphase level set framework for image segmentation using the Mumford and Shah model, Int. J. Comput. Vision 50 (3) (2002) 271-293. (Pubitemid 35377416)
16. E. D. Angelini, T. Song, B. D. Mensh, A. Laine, Multi-phase three-dimensional level set segmentation of brain MRI, in: MICCAI, 2004, pp. 318-326. (Pubitemid 40787396)
17. A.-R. Mansouri, A. Mitiche, C. Vazquez, Multiregion competition: a level set extension of region competition to multiple region image partitioning, Comput. Vision Image Underst. 101 (3) (2006) 137-150. (Pubitemid 41767423)
18. N. Paragios, R. Deriche, Coupled geodesic active regions for image segmentation: a level set approach, in: Proc. ECCV, 2000, pp. 224-240.
19. C. Samson, L. Blanc-Feraud, G. Aubert, J. Zerubia, A level set model for image classification, Int. J. Comput. Vision 40 (3) (2000) 187-197. (Pubitemid 32251468)
20. C. Zimmer, J. C. Olivo-Marin, Coupled parametric active contours, IEEE Trans. Pattern Anal. Mach. Intell. 27 (11) (2005) 1838-1842. (Pubitemid 41685119)
21. K. M. Pohl, R. Kikinis, W. M. Wells, Active mean fields: solving the mean field approximation in the level set framework, Proc. IPMI (2007) 26-37.
22. A. Tsai, W. Wells, C. Tempany, E. Grimson, A. Willsky, Mutual information in coupled multi-shape model for medical image segmentation, Med. Image Anal. 8 (4) (2004) 429-445. (Pubitemid 39618469)
23. H. Zhao, T. Chan, B. Merriman, S. Osher, A variational level set approach to multiphase motion, J. Comput. Phys. 127 (1996) 179-195. (Pubitemid 126162336)
24. T. Brox, J. Weickert, Level set segmentation with multiple regions, IEEE Trans. Image Process. 15 (10) (2006) 3213-3218. (Pubitemid 44473660)
25. A. Yezzi, A. Tsai, A. Willsky, A fully global approach to image segmentation via coupled curve evolution equations, J. Visual Commun. Image Repres. 13 (2002) 195-216. (Pubitemid 34278491)
26. B. C. Russell, A. Torralba, K. P. Murphy, W. T. Freeman, LabelMe: a database and web-based tool for image annotation, Int. J. Comput. Vision 77 (1-3) (2007) 157-173.
27. D. Martin, C. Fowlkes, D. Tal, J. Malik, A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics, Proc. ICCV 2 (July) (2001) 416-423. (Pubitemid 32795086)
28. J. Wan, A. Carass, S. M. Resnick, J. L. Prince, Automated reliable labeling of the cortical surface, in: ISBI, Paris, 2008.
29. D. Mumford, J. Shah, Optimal approximations by piecewise smooth functions and associated variational problems, Commun. Pure Appl. Math. 42 (5) (1989) 577-685.
30. V. Israel-Jost, J. Darbon, E. D. Angelini, I. Bloch, Multi-phase and Multi-channel Region Segmentation and Application in Brain MRI, Tech. rep., UCLA CAM 08-75, 2008.
31. J. Lie, M. Lysaker, X.-c. Tai, A variant of the level set method and applications to image segmentation, Math. Comput. 75 (255) (2006) 1155-1174. (Pubitemid 44116291)
32. G. Chung, L. A. Vese, Image segmentation using a multilayer level-set approach, Comput. Visual. Sci. 12 (6) (2008) 267-285.
33. M. Uzunbas, O. Soldea, D. Unay, M. Cetin, G. Unal, A. Ercil, A. Ekin, Coupled non-parametric shape and moment-based inter-shape pose priors for multiple basal ganglia structure segmentation, IEEE Trans. Med. Image (c) (2010) 1-21.
34. A. Vazquez-Reina, E. Miller, H. Pfister, Multiphase geometric couplings for the segmentation of neural processes, in: CVPR, 2009, pp. 2020-2027.
35. M. Fussenegger, R. Deriche, A. Pinz, A multiphase level set based segmentation framework with pose invariant shape priors, in: ACCB, 2006, pp. 395-404. (Pubitemid 43849431)
36. J. Besag, On the statistical analysis of dirty pictures, J. Roy. Statist. Soc. 48 (1986) 259-302.
37. C. Zach, D. Gallup, J.-M. Frahm, M. Niethammer, Fast global labeling for realtime stereo using multiple plane sweeps, in: Vision, Modeling and Visualization Workshop, 2008.
38. J. Lellmann, J. Kappes, J. Yuan, F. Becker, C. Schnorr, Convex multi-class image labeling by simplex-constrained total variation, in: X.-C. Tai, K. Morken, M. Lysaker, K.-A. Lie (Eds.), SSVM, Springer, Voss, Norway, October 2009, pp. 150-162.
39. E. Bae, J. Yuan, X.-C. Tai, Global minimization for continuous multiphase partitioning problems using a dual approach, IJCV 92 (1) (2010) 1-35.
40. V. Kolmogorov, R. Zabih, What energy functions can be minimized via graph cuts?, IEEE Trans Pattern Anal. Mach. Intell. 26 (2) (2004) 147-159.
41. Y. Boykov, G. Funka-Lea, Graph cuts and efficient N-D image segmentation, Int. J. Comput. Vision 70 (2) (2006) 109-131. (Pubitemid 44127252)
42. Y. Zeng, D. Samaras, W. Chen, Q. Peng, Topology cuts: a novel min-cut/maxflow algorithm for topology preserving segmentation in ND images, Comput. Vision Image Underst. 112 (1) (2008) 81-90.
43. X. Liu, A. Carass, P.-L. Bazin, J. L. Prince, Topology preserving brain tissue segmentation using graph cuts, in: MMBIA, 2011.
44. X. Fan, P.-L. Bazin, J. Bogovic, J. L. Prince, A multiple geometric deformable model framework for homeomorphic 3D medical image segmentation, in: Proc. IEEE CVPR Workshops, 2008, pp. 1-7.
45. X. Fan, P.-L. Bazin, J. L. Prince, A multi-compartment segmentation framework with homeomorphic level sets, in: 2008 IEEE Conference on Computer Vision and Pattern Recognition, 2008, pp. 1-6.
46. G. Sapiro, Geometric Partial Differential Equations and Image Analysis, Cambridge University Press, Cambridge, UK, 2001.
47. V. Caselles, R. Kimmel, G. Sapiro, Geodesic active contours, Intl. J. Comput. Vision 22 (1) (1997) 61-79. (Pubitemid 127507390)
48. L. D. Cohen, I. Cohen, Finite element methods for active contour models and balloons for 2D and 3D images, IEEE Trans. Pattern Anal. Mach. Intell. 15 (1993) 1131-1147.
49. C. Xu, J. L. Prince, Snakes, shapes, and gradient vector flow, IEEE Trans. Image Process. 7 (3) (1998) 359-369. (Pubitemid 128745354)
50. D. Cremers, M. Rousson, R. Deriche, A review of statistical approaches to level set segmentation: integrating color, texture, motion and shape, Int. J. Comput. Vision 72 (2) (2007) 195-215. (Pubitemid 46094760)
51. M. E. Leventon, W. E. L. Grimson, O. Faugeras, Statistical shape influence in geodesic active contours, in: Proc. IEEE CVPR, 2000.
52. T. Kong, A. Rosenfeld, Digital topology: Introduction and survey, CVGIP: Image Underst. 48 (1989) 357-393.
53. G. Malandain, G. Bertrand, N. Ayache, Topological segmentation of discrete surfaces, Int. J. Comput. Vision 10 (2) (1993) 183-197.
54. P.-L. Bazin, L. M. Ellingsen, D. L. Pham, Digital homeomorphisms in deformable registration, in: Proc. IPMI, vol. 20, 2007, pp. 211-22.
55. J. A. Bogovic, B. A. Landman, P.-l. Bazin, J. L. Prince, Statistical fusion of surface labels provided by multiple raters, in: SPIEMI, San Diego, CA, 2010.