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MICCAI
2009
Springer

Diffusion Tensor Field Registration in the Presence of Uncertainty

12 years 9 months ago
Diffusion Tensor Field Registration in the Presence of Uncertainty
We propose a novel method for deformable tensor?to?tensor registration of Diffusion Tensor Imaging (DTI) data. Our registration method considers estimated diffusion tensors as normally distributed random variables whose covariance matrices describe uncertainties in the mean estimated tensor due to factors such as noise in diffusion weighted images (DWIs), tissue diffusion properties, and experimental design. The dissimilarity between distributions of tensors in two different voxels is computed using the Kullback-Leibler divergence to drive a deformable registration process, which is not only affected by principal diffusivities and principal directions, but also the underlying DWI properties. We in general do not assume the positive definite nature of the tensor space given the pervasive influence of noise and other factors. Results indicate that the proposed metric weights voxels more heavily whose diffusion tensors are estimated with greater certainty and exhibit anisotropic diffusion...
M. Okan Irfanoglu, Cheng Guan Koay, Sinisa Pajev
Added 06 Nov 2009
Updated 08 Dec 2009
Type Conference
Year 2009
Where MICCAI
Authors M. Okan Irfanoglu, Cheng Guan Koay, Sinisa Pajevic, Raghu Machiraju, Peter J. Basser
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