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Abstract #1692

Determination of Local Fibre Configuration Using Bayesian Neighbourhood Tract Modeling

Thomas Glyn Close1,2, Jacques-Donald Tournier1,3, Fernando Calamante1,3, Leigh A. Johnston2,4, Iven Mareels2, Alan Connelly1,3

1Brain Research Institute, Florey Neuroscience Institutes (Austin), Melbourne, Victoria, Australia; 2School of Engineering and NICTA VRL, University of Melbourne, Melbourne, Victoria, Australia; 3Department of Medicine, University of Melbourne, Melbourne, Victoria, Australia; 4Howard Florey Insitute, Florey Neuroscience Institutes (Parkville), Melbourne, Victoria, Australia


We present a new method for characterising white matter fibre configurations within local neighbourhoods. Instead of single-voxel based models of fibre orientations represent the complete tract configuration within a local neighbourhood (eg. 3x3x3 voxels) via a rich tract-segment model. By fitting multiple tracts simultaneously, this approach utilizes the probability of surrounding tracts to improve the fit of each tract.

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