Two-Tensor Tractography Using a Constrained Filter

@article{Malcolm2009TwoTensorTU,
  title={Two-Tensor Tractography Using a Constrained Filter},
  author={James G. Malcolm and Martha Elizabeth Shenton and Yogesh Rathi},
  journal={Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention},
  year={2009},
  volume={12 Pt 1},
  pages={
          894-902
        }
}
  • James G. Malcolm, Martha Elizabeth Shenton, Yogesh Rathi
  • Published in MICCAI 2009
  • Computer Science, Medicine
  • Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
  • We describe a technique to simultaneously estimate a weighted, positive-definite multi-tensor fiber model and perform tractography. Existing techniques estimate the local fiber orientation at each voxel independently so there is no running knowledge of confidence in the estimated fiber model. We formulate fiber tracking as recursive estimation: at each step of tracing the fiber, the current estimate is guided by the previous. To do this we model the signal as a weighted mixture of Gaussian… CONTINUE READING

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    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 24 REFERENCES

    Estimating Crossing Fibers: A Tensor Decomposition Approach

    VIEW 5 EXCERPTS
    HIGHLY INFLUENTIAL

    High angular resolution diffusion imaging reveals intravoxel white matter fiber heterogeneity.

    VIEW 5 EXCERPTS
    HIGHLY INFLUENTIAL

    Spectral decomposition of a 4 th - order covariance tensor : Applications to diffusion tensor MRI

    • P. Basser, S. Pajevic
    • Signal Processing
    • 2007