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Variational Bayesian Inference for a Nonlinear Forward Model

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      Probabilistic diffusion tractography with multiple fibre orientations: What can we gain?

      We present a direct extension of probabilistic diffusion tractography to the case of multiple fibre orientations. Using automatic relevance determination, we are able to perform online selection of the number of fibre orientations supported by the data at each voxel, simplifying the problem of tracking in a multi-orientation field. We then apply the identical probabilistic algorithm to tractography in the multi- and single-fibre cases in a number of example systems which have previously been tracked successfully or unsuccessfully with single-fibre tractography. We show that multi-fibre tractography offers significant advantages in sensitivity when tracking non-dominant fibre populations, but does not dramatically change tractography results for the dominant pathways.
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        Bayes Factors

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          Dynamic causal modelling

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            Author and article information

            Journal
            IEEE Transactions on Signal Processing
            IEEE Trans. Signal Process.
            Institute of Electrical and Electronics Engineers (IEEE)
            1053-587X
            1941-0476
            January 2009
            January 2009
            : 57
            : 1
            : 223-236
            10.1109/TSP.2008.2005752
            © 2009
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