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Joint Fractional Segmentation and Multi-tensor Estimation in Diffusion MRI
Xiang Hao and P. Thomas Fletcher
Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, USAAbstract. In this paper we present a novel Bayesian approach for fractional segmentation of white matter tracts and simultaneous estimation of a multi-tensor diffusion model. Our model consists of several white matter tracts, each with a corresponding weight and tensor compartment in each voxel. By incorporating a prior that assumes the tensor fields inside each tract are spatially correlated, we are able to reliably estimate multiple tensor compartments in fiber crossing regions, even with low angular diffusion-weighted imaging (DWI). Our model distinguishes the diffusion compartment associated with each tract, which reduces the effects of partial voluming and achieves more reliable statistics of diffusion measurements. We test our method on synthetic data with known ground truth and show that we can recover the correct volume fractions and tensor compartments. We also demonstrate that the proposed method results in improved segmentation and diffusion measurement statistics on real data in the presence of crossing tracts and partial voluming.
LNCS 7917, p. 340 ff.
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© Springer-Verlag Berlin Heidelberg 2013