These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

216 related articles for article (PubMed ID: 18237891)

  • 1. A tree-structured Markov random field model for Bayesian image segmentation.
    D'Elia C; Poggi G; Scarpa G
    IEEE Trans Image Process; 2003; 12(10):1259-73. PubMed ID: 18237891
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Sonar image segmentation using an unsupervised hierarchical MRF model.
    Mignotte M; Collet C; Perez P; Bouthemy P
    IEEE Trans Image Process; 2000; 9(7):1216-31. PubMed ID: 18262959
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Statistical approach to segmentation of single-channel cerebral MR images.
    Rajapakse JC; Giedd JN; Rapoport JL
    IEEE Trans Med Imaging; 1997 Apr; 16(2):176-86. PubMed ID: 9101327
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A Bayesian framework for image segmentation with spatially varying mixtures.
    Nikou C; Likas AC; Galatsanos NP
    IEEE Trans Image Process; 2010 Sep; 19(9):2278-89. PubMed ID: 20378472
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A multiscale random field model for Bayesian image segmentation.
    Bouman CA; Shapiro M
    IEEE Trans Image Process; 1994; 3(2):162-77. PubMed ID: 18291917
    [TBL] [Abstract][Full Text] [Related]  

  • 6. ML parameter estimation for Markov random fields with applications to Bayesian tomography.
    Saquib SS; Bouman CA; Sauer K
    IEEE Trans Image Process; 1998; 7(7):1029-44. PubMed ID: 18276318
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Training an active random field for real-time image denoising.
    Barbu A
    IEEE Trans Image Process; 2009 Nov; 18(11):2451-62. PubMed ID: 19635701
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Hierarchical multiple Markov chain model for unsupervised texture segmentation.
    Scarpa G; Gaetano R; Haindl M; Zerubia J
    IEEE Trans Image Process; 2009 Aug; 18(8):1830-43. PubMed ID: 19447707
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Unsupervised vector image segmentation by a tree structure-ICM algorithm.
    Fwu JK; Djuric PM
    IEEE Trans Med Imaging; 1996; 15(6):871-80. PubMed ID: 18215966
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Automatic segmentation of magnetic resonance images using a decision tree with spatial information.
    Chao WH; Chen YY; Lin SH; Shih YY; Tsang S
    Comput Med Imaging Graph; 2009 Mar; 33(2):111-21. PubMed ID: 19097854
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Pixon-based image segmentation with Markov random fields.
    Yang F; Jiang T
    IEEE Trans Image Process; 2003; 12(12):1552-9. PubMed ID: 18244710
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Self-validated labeling of Markov random fields for image segmentation.
    Feng W; Jia J; Liu ZQ
    IEEE Trans Pattern Anal Mach Intell; 2010 Oct; 32(10):1871-87. PubMed ID: 20724763
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Agentification of Markov model-based segmentation: application to magnetic resonance brain scans.
    Scherrer B; Dojat M; Forbes F; Garbay C
    Artif Intell Med; 2009 May; 46(1):81-95. PubMed ID: 18929472
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Multiscale Bayesian segmentation using a trainable context model.
    Cheng H; Bouman CA
    IEEE Trans Image Process; 2001; 10(4):511-25. PubMed ID: 18249641
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Superresolution with compound Markov random fields via the variational EM algorithm.
    Kanemura A; Maeda S; Ishii S
    Neural Netw; 2009 Sep; 22(7):1025-34. PubMed ID: 19157777
    [TBL] [Abstract][Full Text] [Related]  

  • 16. An adaptive semiparametric and context-based approach to unsupervised change detection in multitemporal remote-sensing images.
    Bruzzone L; Prieto DF
    IEEE Trans Image Process; 2002; 11(4):452-66. PubMed ID: 18244646
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Document ink bleed-through removal with two hidden Markov random fields and a single observation field.
    Wolf C
    IEEE Trans Pattern Anal Mach Intell; 2010 Mar; 32(3):431-47. PubMed ID: 20075470
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Statistical regularization in linearized microwave imaging through MRF-based MAP estimation: hyperparameter estimation and image computation.
    Pascazio V; Ferraiuolo G
    IEEE Trans Image Process; 2003; 12(5):572-82. PubMed ID: 18237933
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Unsupervised statistical segmentation of nonstationary images using triplet Markov fields.
    Benboudjema D; Pieczynski W
    IEEE Trans Pattern Anal Mach Intell; 2007 Aug; 29(8):1367-78. PubMed ID: 17568141
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Estimation of Markov random field prior parameters using Markov chain Monte Carlo maximum likelihood.
    Descombes X; Morris RD; Zerubia J; Berthod M
    IEEE Trans Image Process; 1999; 8(7):954-63. PubMed ID: 18267508
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.