Clinical DT-MRI Estimation, Smoothing, and Fiber Tracking With Log-Euclidean Metrics

@article{Fillard2006ClinicalDE,
  title={Clinical DT-MRI Estimation, Smoothing, and Fiber Tracking With Log-Euclidean Metrics},
  author={Pierre Fillard and Vincent Arsigny and Xavier Pennec and Nicholas Ayache},
  journal={IEEE Transactions on Medical Imaging},
  year={2006},
  volume={26},
  pages={1472-1482}
}
Diffusion tensor magnetic resonance imaging (DT-MRI or DTI) is an imaging modality that is gaining importance in clinical applications. However, in a clinical environment, data have to be acquired rapidly, often at the expense of the image quality. This often results in DTI datasets that are not suitable for complex postprocessing like fiber tracking. We propose a new variational framework to improve the estimation of DT-MRI in this clinical context. Most of the existing estimation methods rely… CONTINUE READING

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