Shahrum Nedjati-Gilani1, Daniel C. Alexander1
1Centre for Medical Image Computing, University College London, London, UK
We present a new model for fanning and bending white matter structures on a sub-voxel scale, and explore the suitability of the model for estimating the degree of fanning in each voxel of a human brain diffusion MRI acquisition. Preliminary work suggests that we can use the model to reconstruct fanning structures in real brain data and provide quantitative information about the fanning structure. Defining the structure more accurately allows more appropriate action to be taken by tractography algorithms, resulting in fewer false positive and false negative tracts.
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