Unsupervised segmentation of medical image based on difference of mutual information

Science in China, Series F: Information Sciences

Volumn 49, Issue 4, 2006, Pages 484-493

  Lü, Qingwen ^a   Chen, Wufan ^a  

^a SOUTHERN MEDICAL UNIVERSITY   (China)

Author keywords

Medical image; Mutual information; Pixon; Unsupervised segmentation

Indexed keywords

EID: 33750195903     PISSN: 10092757     EISSN: 18622836     Source Type: Journal    
DOI: 10.1007/s11432-006-0484-1     Document Type: Article

References (20)

1. Zhang Y, Brady M, Smith S. Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. IEEE Trans Med Imag, 2001, 20(1): 45-57
2. Ruan S, Moretti B, Fadili J, et al. Fuzzy Markovian segmentation in application of magnetic resonance images. Comp Vision Image Under, 2002, 85: 54-69
3. Feng Y, Chen W. Brain MR image segmentation using fuzzy clustering with spatial constraints based on Markov random field theory. In: Proc of MIAR 2004 (LNCS 3150, Beijing). Berlin: Springer-Verlag, 2004. 188-195
4. Yang F, Jiang T. Pixon-based image segmentation with Markov random fields. IEEE Trans Image Process, 2003, 12(12): 1552-1559
5. Wang A, Shen L. Study surveys on image segmentation. Meas Control Tech (in Chinese), 2000, 19(5): 1-16
6. Lin Y, Chen W, Yang F, et al. New approach for image segmentation based on generalized fuzzy Gibbs random fields. Chin J Comput (in Chinese), 2003, 26(11): 1465-1469
7. Dunn J C. A fuzzy relative of the ISODATA process and its use in detecting compact well-separated clusters. J Cybem, 1973, 3:32-57
8. Bezdek J C. Pattern Recognition with Fuzzy Objective Function Algorithms. New York: Plenum Press, 1981
9. Geman S, Geman D. Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images. IEEE Trans Pattern Anal Machine Intell, 1984, 6 (6): 721-741
10. Pina R K, Puetter R C. Bayesian image reconstruction: The pixon and optimal image modeling. Publ Astron SocPac, 1993, 105:630-637
11. Yang Y, Huang B, Wang Q, et al. Meaningful region segmentation of an image combined with intensity distribution and spatial information field. Acta Electron Sinica (in Chinese), 2003, 31(2): 252-254
12. Maes F, Collignon A. Multimodality image registration by maximization of mutual information. IEEE Trans Med Imag, 1997, 16(2): 187-198
13. Studholme C, Hill D L G, Hawkes D J. Incorporating connected region labeling into automated image registration using mutual information. In: Proc of MMBIA'96 (San Francisco). Piscataway: IEEE Press, 1996. 3-31
14. Rigau J, Feixas M, Sbert M, et al. Medical image segmentation based on mutual information maximization. In Proc of MICCAI2004 (Saint-Malo). Berlin: Springer-Verlag, 2004. 135-142
15. Kim J, Fisher III J W, Yezzi A, et al. A nonparametric statistical method for image segmentation using information theory and curve evolution. IEEE Trans Image Process, 2005, 14(10): 1486-1502
16. Descombes X, Kruggel F. A Markov pixon information approach for low-level image description. IEEE Trans Pattern Anal Machine Intell, 1999, 21(6): 482-493
17. Akaike H. Anew look at the statistical model identification. IEEE Trans Auto Contr, 1974, 19(6): 716-723
18. Cheng B, Wang Y, Zheng N, et al. MRF model and FRAME model-based unsupervised image segmentation. Sci China Ser F-Inf Sci, 2004, 47(6): 697-705
19. Li S Z. Markov Random Field Modeling in Image Analysis. 2nd ed. Berlin: Springer-Verlag, 2000
20. Chen W, Lu X, Chen J, et al. A new algorithm of edge detection for color image: Generalized fuzzy operator. Sci China Ser A-Math, 1995, 38(10): 1272-1280