Two-tensor tractography in Slicer using Python and Teem

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Key Investigators

  • BWH: Madeleine Seeland
  • BWH: Carl-Fredrik Westin
  • BWH: Gordon Kindlmann


Objective

Our objective is to finalize the integration of Two-Tensor Tractography into Slicer and to test it on diverse DWI datasets. Furthermore the optimal parameter settings to run the algorithm needs to be investigated.


Approach, Plan

We are integrating the Two-Tensor Streamline Tractography into Slicer. The complete details on the method are summarized in [1]. Our approach for this project week will focus on the following:

The implementation of our project is carried out in Python. The Two-Tensor Tractography calls are already implemented in the Teem library and can be accessed using the Python wrappings for the Teem.

Progress



References

[1] Qazi AA, Radmanesh A, O'Donnell L, Kindlmann G, Peled S, Whalen S, Westin CF, Golby AJ. Resolving crossings in the corticospinal tract by two-tensor streamline tractography: method and clinical assessment using fMRI. Neuroimage 2008

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