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 *

149 related articles for article (PubMed ID: 18276274)

  • 1. Inversion of large-support ill-posed linear operators using a piecewise Gaussian MRF.
    Nikolova M; Idier J; Mohammad-Djafari A
    IEEE Trans Image Process; 1998; 7(4):571-85. PubMed ID: 18276274
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Markovian reconstruction using a GNC approach.
    Nikolova M
    IEEE Trans Image Process; 1999; 8(9):1204-20. PubMed ID: 18267538
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Posterior-mean super-resolution with a causal Gaussian Markov random field prior.
    Katsuki T; Torii A; Inoue M
    IEEE Trans Image Process; 2012 Jul; 21(7):3182-93. PubMed ID: 22389146
    [TBL] [Abstract][Full Text] [Related]  

  • 4. 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]  

  • 5. 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]  

  • 6. Bayesian image reconstruction in SPECT using higher order mechanical models as priors.
    Lee SJ; Rangarajan A; Gindi G
    IEEE Trans Med Imaging; 1995; 14(4):669-80. PubMed ID: 18215871
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Application of the split-gradient method to 3D image deconvolution in fluorescence microscopy.
    Vicidomini G; Boccacci P; Diaspro A; Bertero M
    J Microsc; 2009 Apr; 234(1):47-61. PubMed ID: 19335456
    [TBL] [Abstract][Full Text] [Related]  

  • 8. The application of mean field theory to image motion estimation.
    Zhang J; Hanauer GG
    IEEE Trans Image Process; 1995; 4(1):19-33. PubMed ID: 18289956
    [TBL] [Abstract][Full Text] [Related]  

  • 9. The ZpiM algorithm: a method for interferometric image reconstruction in SAR/SAS.
    Dias JM; Leitao JM
    IEEE Trans Image Process; 2002; 11(4):408-22. PubMed ID: 18244643
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. Mean field annealing: a formalism for constructing GNC-like algorithms.
    Bilbro GL; Snyder WE; Garnier SJ; Gault JW
    IEEE Trans Neural Netw; 1992; 3(1):131-8. PubMed ID: 18276414
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 13. A comparative study of energy minimization methods for Markov random fields with smoothness-based priors.
    Szeliski R; Zabih R; Scharstein D; Veksler O; Kolmogorov V; Agarwala A; Tappen M; Rother C
    IEEE Trans Pattern Anal Mach Intell; 2008 Jun; 30(6):1068-80. PubMed ID: 18421111
    [TBL] [Abstract][Full Text] [Related]  

  • 14. 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]  

  • 15. Hierarchical Bayesian sparse image reconstruction with application to MRFM.
    Dobigeon N; Hero AO; Tourneret JY
    IEEE Trans Image Process; 2009 Sep; 18(9):2059-70. PubMed ID: 19493849
    [TBL] [Abstract][Full Text] [Related]  

  • 16. 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]  

  • 17. An augmented Lagrangian approach to the constrained optimization formulation of imaging inverse problems.
    Afonso MV; Bioucas-Dias JM; Figueiredo MA
    IEEE Trans Image Process; 2011 Mar; 20(3):681-95. PubMed ID: 20840899
    [TBL] [Abstract][Full Text] [Related]  

  • 18. 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]  

  • 19. On the computational aspects of Gibbs-Markov random field modeling of missing-data in image sequences.
    Krishnan D; Chong MN; Kalra S
    IEEE Trans Image Process; 1999; 8(8):1139-42. PubMed ID: 18267530
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Shape-based multi-spectral optical image reconstruction through genetic algorithm based optimization.
    Wang S; Dhawan AP
    Comput Med Imaging Graph; 2008 Sep; 32(6):429-41. PubMed ID: 18585895
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.