Diffusion Tensor Field Registration in the Presence of Uncertainty

  title={Diffusion Tensor Field Registration in the Presence of Uncertainty},
  author={M. Okan Irfanoglu and Cheng Guan Koay and Sinisa Pajevic and Raghu Machiraju and Peter J. Basser},
  journal={Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention},
  volume={12 Pt 1},
  • M. Irfanoglu, C. Koay, P. Basser
  • Published 2 October 2009
  • Mathematics
  • Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
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… 
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