Bayesian image segmentation using local iso-intensity structural orientation

IEEE Transactions on Image Processing

Volumn 14, Issue 10, 2005, Pages 1512-1523

  Wong, Wilbur C K ^a   Chung, Albert C S ^a  

^a HONG KONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Hong Kong)

Author keywords

Biomedical image processing; Hessian matrices; Image segmentation; Markov processes; Maximum a posteriori (MAP) estimation; Maximum likelihood estimation; Spatial data structures; Stochastic fields

Indexed keywords

ALGORITHMS; COMPUTER VISION; DATA STRUCTURES; IMAGE QUALITY; MARKOV PROCESSES; MATHEMATICAL MODELS; MATRIX ALGEBRA; MAXIMUM LIKELIHOOD ESTIMATION; MEDICAL IMAGING; MONTE CARLO METHODS; STATISTICAL METHODS; TENSORS;

BAYESIAN FRAMEWORK; BIOMEDICAL IMAGE PROCESSING; HESSIAN MATRICES; MAXIMUM A POSTERIORI (MAP) ESTIMATION; SPATIAL DATA STRUCTURES; STOCHASTIC FIELDS; STRUCTURAL ORIENTATION ESTIMATION; SYNTHETIC IMAGES;

IMAGE SEGMENTATION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BAYES THEOREM; COMPARATIVE STUDY; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; EVALUATION; IMAGE ENHANCEMENT; INFORMATION RETRIEVAL; METHODOLOGY; SIGNAL PROCESSING; STATISTICAL MODEL; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; COMPUTER SIMULATION; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; INFORMATION STORAGE AND RETRIEVAL; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 27744493738     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2005.852199     Document Type: Article

References (53)

1. R. C. Gonzalez and R. E. Woods, Digital Image Processing, 2nd ed. Reading, MA: Addison-Wesley, 2002.
2. N. R. Pal and S. K. Pal, "A review on image segmentation techniques," Pattern Recognit., vol. 26, no. 9, pp. 1277-1294, 1993.
3. J. S. Suri, K. Liu, S. Singh, S. N. Laxminarayan, X. Zeng, and L. Reden, "Shape recovery algorithms using level sets in 2-D/3-D medical imagery: A state-of-the-art review," IEEE Trans. Inf. Technol. Biomed., vol. 6, no. 1, pp. 8-28, Mar. 2002.
4. H. Trichili, M. S. Bouhlel, and F Kammoun, "A review and evaluation of medical image segmentation using methods of optimal filtering," J. Test. Eval., vol. 31, no. 5, pp. 398-404, 2003.
5. T. McInerney and D. Terzopoulos, "Topology adaptive deformable surfaces for medical image volume segmentation," IEEE Trans. Med. Imag., vol. 18, no. 6, pp. 840-850, Jun. 1999.
6. L. M. Lorigo, O. Faugeras, W. E. L. Grimson, R. Keriven, R. Kikinis, and C.-F. Westin, "Co-dimension 2 geodesic active contours for MRA segmentation," in Proc. Int. Conf. Information Processing in Medical Imaging, 1999, pp. 126-139.
7. K. C. Wang, R. W. Dutton, and C. A. Taylor, "Improving geometric model construction for blood flow modeling," IEEE Eng. Med. Biol. Mag., vol. 18, no. 6, pp. 33-39, Jun. 1999.
8. C.-F. Westin, L. M. Lorigo, O. Faugeras, W. E. L. Grimson, S. Dawson, A. Norbash, and R. Kinkinis, "Segmentation by adaptive geodesic active contours," in Medical Image Computing and Computer-Assisted Intervention. Berlin, Germany: Springer-Verlag, 2000, vol. 1935, pp. 266-275.
9. H. T. Nguyen, M. Worring, and R. van den Boomgaard, "Watersnakes: Energy-driven watershed segmentation," IEEE Trans. Pattern Anal. Mach. Intell., vol. 25, no. 3, pp. 330-342, Mar. 2003.
10. J. McLachlan and D. Peel, Finite Mixture Models. New York: Wiley, 2000.
11. J. K. Fwu and P. M. Djurić, "Unsupervised vector image segmentation by a tree structure-ICM algorithm," IEEE Trans. Med. Imag., vol. 15, no. 6, pp. 871-880, Jun. 1996.
12. Y. W. Lim and S. U. Lee, "On the color image segmentation algorithm based on the thresholding and the fuzzy c-means technique," Pattern Recognit., vol. 23, no. 9, pp. 935-952, 1990.
13. M. R. Rezaec, P. M. J. van der Zwet, B. P. F. Lelieveldt, R. J. van der Geest, and J. H. C. Reiber, "A multiresolution image segmentation technique based on pyramidal segmentation and fuzzy clustering," IEEE Trans. Image Process., vol. 9, no. 10, pp. 1238-1248, Oct. 2000.
14. M. N. Ahmed, S. M. Yamany, N. Mohamed, A. A. Farag, and T. Moriarty, "A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data," IEEE Trans. Med Imag., vol. 21, no. 2, pp. 193-199, Feb. 2002.
15. T. F. Chan and L. A. Vese, "Active contours without edges," IEEE Trans. Image Process., vol. 10, no. 2, pp. 266-277, Feb. 2001.
16. L. Liu and S. Sclaroff, "Region segmentation via deformable model-guided split and merge," in Proc. Int. Conf. Computer Vision, vol. 1, 2001, pp. 98-104.
17. Y. Wang, T. Adali, J. Xuan, and Z. Szabo, "Magnetic resonance image analysis by information theoretic criteria and stochastic site models," IEEE Trans. Inf. Technol. Biomed., vol. 5, no. 1, pp. 150-158, Mar. 2001.
18. M. Egmont-Petersen, D. de Ridder, and H. Handels, "Image processing with neural networks-A review," Pattern Recognit., vol. 35, pp. 2279-2301, 2002.
19. S. Ruan, B. Moretti, J. Fadili, and D. Bloyet, "Fuzzy Markovian segmentation in application of magnetic resonance images," Comput. Vis. Image Understand., vol. 85, pp. 54-69, 2002.
20. S. Y. Wan and W. E. Higgins, "Symmetric region growing," IEEE Trans. Image Process., vol. 12, no. 9, pp. 1007-1015, Sep. 2003.
21. C. D'Elia, G. Poggi, and G. Scarpa, "A tree-structured Markov random field model for Bayesian image segmentation," IEEE Trans. Image Process., vol. 12, no. 9, pp. 1259-1273, Oct. 2003.
22. S. Z. Li, Markov Random Field Modeling in Image Analysis, 2nd ed. Tokyo, Japan: Springer-Verlag, 2001.
23. H. Guillemaud and M. Brady, "Estimating the bias field of MR images," IEEE Trans. Med. Imag., vol. 16, no. 2, pp. 238-251, Feb. 1997.
24. Y. C. Fung, Biomechanics: Circulation, 2nd ed. New York: Springer-Verlag, 1996.
25. P. J. Besl and R. C. Jain, "Segmentation through variable-order surface fitting," IEEE Trans. Pattern Anal. Mach. Intell., vol. 10, no. 2, pp. 167-192, Feb. 1988.
26. Y. G. Leclerc, "Constructing simple stable description for image partitioning," Int. J Comput. Vis., vol. 3, no. 1, pp. 73-102, 1989.
27. Z. Tu and S. C. Zhu, "Image segmentation by data-driven Markov chain Monte Carlo," IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 5, pp. 657-673, May 2002.
28. D. Geiger and R Girosi, "Parallel and deterministic algorithms from MRF's: Surface reconstruction," IEEE Trans. Pattern Anal. Mach. Intell., vol. 13, no. 5, pp. 401-412, May 1991.
29. J. Besag, "On the statistical analysis of dirty pictures," J. Roy. Stat. Soc. B, vol. 48, no. 3, pp. 259-302, 1986.
30. C. Tomasi and R. Manduchi, "Bilateral filtering for gray and color images," in Proc. Int. Conf. Computer Vision, 1998, pp. 839-846.
31. H. Knutsson, "Representing local structure using tensors," in Proc. Scandinavian Conf. Image Analysis, 1989, pp. 244-251.
32. G. H. Granlund and H. Knutssan, Signal Processing for Computer Vision. Norwell, MA: Kluwer, 1995.
33. Y. Sato, S. Nakajima, N. Shiraga, H. Atsumi, S. Yoshida, T. Koller, G. Gerig, and R. Kikinis, "3-D multi-scale line filter for segmentation and visualization of curvilinear structures in medical images," Med. Imag. Anal., vol. 2, no. 2, pp. 143-168, 1998.
34. S. Aylward and E. Bullitt, "Initialization, noise, singularities, and scale in height ridge traversal for tubular object centerline extraction," IEEE Trans. Med. Imag., vol. 21, no. 1, pp. 61-75, Jan. 2002.
35. K. Krissian, G. Maladain, R. Vaillant, Y. Trousset, and N. Ayache, "Model-based multiscale detection of 3-D vessels," Comput. Vis. Pattern Recognit., pp. 722-727, 1998.
36. S. Lakshmanan and H. Derin, "Simultaneous parameter estimation and segmentation of Gibbs random fields using simulated annealing," IEEE Trans. Pattern Anal. Mach. Intell., vol. 11, no. 8, pp. 799-813, Aug. 1989.
37. Z. Kato, J. Zerubia, and M. Berthod, "Unsupervised parallel image classification using Markovian models," Pattern Recognit., vol. 32, pp. 591-604, 1999.
38. J. M. Laferté, P. Pérez, and F. Heitz, "Discrete Markov image modeling and inference on the quatree," IEEE Trans. Image Process., vol. 9, no. 4, pp. 390-404, Apr. 2000.
39. M. Mignotte, C. Collet, P. Perez, and P. Bouthemy, "Sonar image segmentation using an unsupervised hierarchical MRF model," IEEE Trans. Image Process., vol. 9, no. 10, pp. 1216-1231, Oct. 2000.
40. R. Wilson and C. T. Li, "A class of discrete multiresolution random fields and its application to image segmentation," IEEE Trans. Pattern Anal. Mach. Intell., vol. 25, no. 1, pp. 42-56, Jan. 2003.
41. Y. Boykov, O. Veksler, and R. Zabih, "Fast approximate energy minimization via graph cuts," IEEE Trans. Pattern Anal. Mach. Intell., vol. 23, no. 11, pp. 1222-1239, Nov. 2001.
42. S. Geman and D. Geman, "Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images," IEEE Trans. Pattern Anal. Mach. Intell., vol. PAMI-6, no. 6, pp. 721-741, Jun. 1984.
43. A. Blake and A. Zisserman, Visual Reconstruction. Cambridge, MA: MIT Press, 1987.
44. C. Peterson and B. Soderberg, "A new method for mapping optimization problems onto neural networks," Int. J Neur. Syst., vol. 1, no. 1, pp. 3-22, 1989.
45. D. J. Miller and Q. Zhao, "A sequence-based extension of mean-field annealing using the forward/backward algorithm: Application to image segmentation," IEEE Trans. Signal Process., vol. 51, no. 12, pp. 2692-2705, Dec. 2003.
46. J. L. Marroquin, E. A. Santana, and S. Botello, "Hidden Markov measure field models for image segmentation," IEEE Trans. Pattern Anal. Mach. Intell., vol. 25, no. 12, pp. 1380-1387, Dec. 2003.
47. H. Ishikawa, "Exact optimization for Markov random fields with convex priors," IEEE Trans. Pattern Anal. Mach. Intell., vol. 25, no. 10, pp. 1333-1336, Oct. 2003.
48. K. V. Leemput, F. Maes, D. Vandermeulen, A. Colchester, and P. Suetens, "Automated segmentation of MS lesions from multi-channel MR images," in Medical Image Computing and Computer Assisted Intervention. Berlin, Germany: Springer-Verlag, 1999, vol. 1679, pp. 11-21.
49. J. S. Suri, K. Liu, L. Reden, and S. Laxminarayan, "A review on MR vascular image processing algorithms: Acquisition and prefiltering: Part I," IEEE Trans. Inform. Technol. Biomed., vol. 6, no. 2, pp. 324-337, Jun. 2002.
50. A. C. S. Chung, J. A. Noble, and P. Summers, "Fusing speed and phase information for vascular segmentation of phase contrast MR angiograms," Med. Imag. Anal., vol. 6, no. 2, pp. 109-128, 2002.
51. J. Weickert, "Coherence-enhancing diffusion filtering," Int. J. Comput. Vis., vol. 31, no. 2-3, pp. 111-127, 1999.
52. D. Barash, "A fundamental relationship between bilateral filtering, adaptive smoothing, and the nonlinear diffusion equation," IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 6, pp. 844-847, Jun. 2002.
53. Y. T. Cui and Q. Huang, "Character extraction of license plates from video," Comput. Vis. Pattern Recognit., pp. 502-507, 1997.