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Volumn 152, Issue 2, 2005, Pages 184-190

EM image segmentation algorithm based on an inhomogeneous hidden MRF model

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTATIONAL METHODS; GAUSSIAN NOISE (ELECTRONIC); MARKOV PROCESSES; MATHEMATICAL MODELS; PROBABILITY; STATISTICAL METHODS;

EID: 18444413263     PISSN: 1350245X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1049/ip-vis:20041210     Document Type: Article
Times cited : (16)

References (10)
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  • 2
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    • Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images
    • Geman, S., and Geman, D.: 'Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images', IEEE Trans. PRMI, 1984, 6, pp. 721-741
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  • 4
    • 0034745001 scopus 로고    scopus 로고
    • Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm
    • Zhang, Y., Brady, M., and Smith, S.: 'Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm', IEEE Trans. Med. Imaging, 2001, 20, (1), pp. 45-57
    • (2001) IEEE Trans. Med. Imaging , vol.20 , Issue.1 , pp. 45-57
    • Zhang, Y.1    Brady, M.2    Smith, S.3
  • 5
    • 0026938712 scopus 로고
    • The mean field theory in EM procedures for Markov random fields
    • Zhang, J.: 'The mean field theory in EM procedures for Markov random fields', IEEE Trans. Signal Process., 1992, 40, (3), pp. 2570-2583
    • (1992) IEEE Trans. Signal Process , vol.40 , Issue.3 , pp. 2570-2583
    • Zhang, J.1
  • 6
    • 0037209490 scopus 로고    scopus 로고
    • EM procedures using mean field-like approximations for Markov model-based image segmentation
    • Celeux, G., Forbes, F., and Peyrard, N.: 'EM procedures using mean field-like approximations for Markov model-based image segmentation', Pattern Recognit., 2003, 36, pp. 131-144
    • (2003) Pattern Recognit. , vol.36 , pp. 131-144
    • Celeux, G.1    Forbes, F.2    Peyrard, N.3
  • 8
    • 0032630688 scopus 로고    scopus 로고
    • Estimating Gaussian Markov random field parameters in a nonstationary framework: Application to remote sensing image
    • Descombes, X., Sigelle, M., and Preteux, F.: 'Estimating Gaussian Markov random field parameters in a nonstationary framework: application to remote sensing image', IEEE Trans. Image Process., 1999, 8, pp. 490-503
    • (1999) IEEE Trans. Image Process , vol.8 , pp. 490-503
    • Descombes, X.1    Sigelle, M.2    Preteux, F.3
  • 9
    • 10044260784 scopus 로고    scopus 로고
    • Modelling of inhomogeneous Markov random fields with applications to cloud screening
    • University of California
    • Cadez, I., and Smyth, P.: 'Modelling of inhomogeneous Markov random fields with applications to cloud screening'. University of California, Technical Report UCI-ICS 98-21, 1998
    • (1998) Technical Report , vol.UCI-ICS 98-21
    • Cadez, I.1    Smyth, P.2
  • 10
    • 0033623981 scopus 로고    scopus 로고
    • Parametric estimate of intensity inhomogeneities applied to MRI
    • Styner, M., Brechbuhler, C., and Szekely, G.: 'Parametric estimate of intensity inhomogeneities applied to MRI', IEEE Trans. Med. Imaging, 2000, 19, (3), pp. 153-165
    • (2000) IEEE Trans. Med. Imaging , vol.19 , Issue.3 , pp. 153-165
    • Styner, M.1    Brechbuhler, C.2    Szekely, G.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.