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Journal Abstract Search

262 related items for PubMed ID: 26501687

  • 1. A Bayesian hierarchical framework for modeling brain connectivity for neuroimaging data.
    Chen S, Bowman FD, Mayberg HS.
    Biometrics; 2016 Jun; 72(2):596-605. PubMed ID: 26501687
    [Abstract] [Full Text] [Related]

  • 2. A hierarchical model for integrating unsupervised generative embedding and empirical Bayes.
    Raman S, Deserno L, Schlagenhauf F, Stephan KE.
    J Neurosci Methods; 2016 Aug 30; 269():6-20. PubMed ID: 27141854
    [Abstract] [Full Text] [Related]

  • 3. Predicting individual brain functional connectivity using a Bayesian hierarchical model.
    Dai T, Guo Y, Alzheimer's Disease Neuroimaging InitiativeDepartment of Biostatistics and Bioinformatics, The Rollins School of Public Health, Emory University, Atlanta, GA, United States..
    Neuroimage; 2017 Feb 15; 147():772-787. PubMed ID: 27915121
    [Abstract] [Full Text] [Related]

  • 4. Modeling inter-subject variability in FMRI activation location: a Bayesian hierarchical spatial model.
    Xu L, Johnson TD, Nichols TE, Nee DE.
    Biometrics; 2009 Dec 15; 65(4):1041-51. PubMed ID: 19210732
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  • 5. A Bayesian hierarchical framework for spatial modeling of fMRI data.
    DuBois Bowman F, Caffo B, Bassett SS, Kilts C.
    Neuroimage; 2008 Jan 01; 39(1):146-56. PubMed ID: 17936016
    [Abstract] [Full Text] [Related]

  • 6. Probabilistic framework for brain connectivity from functional MR images.
    Rajapakse JC, Wang Y, Zheng X, Zhou J.
    IEEE Trans Med Imaging; 2008 Jun 01; 27(6):825-33. PubMed ID: 18541489
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  • 8. Fast Bayesian whole-brain fMRI analysis with spatial 3D priors.
    Sidén P, Eklund A, Bolin D, Villani M.
    Neuroimage; 2017 Feb 01; 146():211-225. PubMed ID: 27876654
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  • 11. Group-representative functional network estimation from multi-subject fMRI data via MRF-based image segmentation.
    Tang B, Iyer A, Rao V, Kong N.
    Comput Methods Programs Biomed; 2019 Oct 01; 179():104976. PubMed ID: 31443856
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  • 12. A novel method for sparse dynamic functional connectivity analysis from resting-state fMRI.
    Wang H, Chen J, Yuan Z, Huang Y, Lin F.
    J Neurosci Methods; 2024 Nov 01; 411():110275. PubMed ID: 39241968
    [Abstract] [Full Text] [Related]

  • 13. A unified Bayesian hierarchical model for MRI tissue classification.
    Feng D, Liang D, Tierney L.
    Stat Med; 2014 Apr 15; 33(8):1349-68. PubMed ID: 24738112
    [Abstract] [Full Text] [Related]

  • 14. Variational Bayesian inversion for hierarchical unsupervised generative embedding (HUGE).
    Yao Y, Raman SS, Schiek M, Leff A, Frässle S, Stephan KE.
    Neuroimage; 2018 Oct 01; 179():604-619. PubMed ID: 29964187
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  • 16. Comparing variational Bayes with Markov chain Monte Carlo for Bayesian computation in neuroimaging.
    Nathoo FS, Lesperance ML, Lawson AB, Dean CB.
    Stat Methods Med Res; 2013 Aug 01; 22(4):398-423. PubMed ID: 22642986
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  • 17. A functional network estimation method of resting-state fMRI using a hierarchical Markov random field.
    Liu W, Awate SP, Anderson JS, Fletcher PT.
    Neuroimage; 2014 Oct 15; 100():520-34. PubMed ID: 24954282
    [Abstract] [Full Text] [Related]

  • 18. Bayesian vector autoregressive model for multi-subject effective connectivity inference using multi-modal neuroimaging data.
    Chiang S, Guindani M, Yeh HJ, Haneef Z, Stern JM, Vannucci M.
    Hum Brain Mapp; 2017 Mar 15; 38(3):1311-1332. PubMed ID: 27862625
    [Abstract] [Full Text] [Related]

  • 19. A fully Bayesian approach to the parcel-based detection-estimation of brain activity in fMRI.
    Makni S, Idier J, Vincent T, Thirion B, Dehaene-Lambertz G, Ciuciu P.
    Neuroimage; 2008 Jul 01; 41(3):941-69. PubMed ID: 18439839
    [Abstract] [Full Text] [Related]

  • 20. Bayesian connective field modeling using a Markov Chain Monte Carlo approach.
    Invernizzi A, Haak KV, Carvalho JC, Renken RJ, Cornelissen FW.
    Neuroimage; 2022 Dec 01; 264():119688. PubMed ID: 36280097
    [Abstract] [Full Text] [Related]

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