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| General Section People Events Program Details |
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Predoctoral Trainee
Diffusion Tensor MRI is an important modality for the characterization of the local organization of brain tissue microstructure. This captures information about structures that represent brain connectivity networks. We propose an algorithm where a global parametric model and a local non-parametric support vector regression co-inform each other. This enables us to construct improved models that characterize brain network structure. Current techniques primarily rely on strictly local information to propagate streamlines (tracts), along 1D trajectories through a diffusion tensor field making them highly susceptible to noise. The proposed algorithm offers robustness and reproducibility over the current state of the art. (This research is in collaboration with Andrew Alexander, Vikas Singh and Charles Dyer. 2008 CV (.pdf format)
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