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arxiv: 1406.0581 · v2 · pith:3OTYE75Xnew · submitted 2014-06-03 · 📊 stat.ME · stat.AP

Fiber Direction Estimation, Smoothing and Tracking in Diffusion MRI

classification 📊 stat.ME stat.AP
keywords diffusionmethoddirectiondirectionsestimationsmoothingalzheimerdata
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Diffusion magnetic resonance imaging is an imaging technology designed to probe anatomical architectures of biological samples in an in vivo and non-invasive manner through measuring water diffusion. The contribution of this paper is threefold. First it proposes a new method to identify and estimate multiple diffusion directions within a voxel through a new and identifiable parametrization of the widely used multi-tensor model. Unlike many existing methods, this method focuses on the estimation of diffusion directions rather than the diffusion tensors. Second, this paper proposes a novel direction smoothing method which greatly improves direction estimation in regions with crossing fibers. This smoothing method is shown to have excellent theoretical and empirical properties. Lastly, this paper develops a fiber tracking algorithm that can handle multiple directions within a voxel. The overall methodology is illustrated with simulated data and a data set collected for the study of Alzheimer's disease by the Alzheimer's Disease Neuroimaging Initiative (ADNI).

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