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A Unified Variational Approach to Denoising and Bias Correction in MR.

, , , , , , , и . IPMI, том 2732 из Lecture Notes in Computer Science, стр. 148-159. Springer, (2003)

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Alan S Castleman

Safwat Alani

Maia Alandjiyska

Yilmaz Alan

Viola Alanku

 

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Multiscale methods for the segmentation of images., , , и . ICASSP, стр. 2247-2250. IEEE Computer Society, (1996)A Recursive Estimation Approach to the Segmentation of MR Imagery., , , и . ICIP (2), стр. 506-509. IEEE Computer Society, (1997)Inference with Minimal Communication: a Decision-Theoretic Variational Approach., и . NIPS, стр. 675-682. (2005)Learning Gaussian Graphical Models with Observed or Latent FVSs., и . NIPS, стр. 1833-1841. (2013)Efficient Multiscale Sampling from Products of Gaussian Mixtures., , , и . NIPS, стр. 1-8. MIT Press, (2003)Scaling laws for learning high-dimensional Markov forest distributions., , и . Allerton, стр. 712-718. IEEE, (2010)Latent variable graphical model selection via convex optimization., , и . Allerton, стр. 1610-1613. IEEE, (2010)A large-deviation analysis for the maximum likelihood learning of tree structures., , , и . ISIT, стр. 1140-1144. IEEE, (2009)Nonparametric belief propagation for self-localization of sensor networks., , , и . IEEE J. Sel. Areas Commun., 23 (4): 809-819 (2005)imge segmentation and edge enhancement with stabilized inverse diffusion equations, , и . IEEE transactions on image processing, (2000)