Summer2009:VCFS

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Home < Summer2009:VCFS

Key Investigators

  • BWH: Julien de Siebenthal, Sylvain Bouix, Marek Kubicki

Objective

To create an end-to-end analysis pipeline to study white matter anomalies using a stochastic tractography algorithm in VCFS population.

See our Roadmap for more details.

Approach, Plan

Our approach involves the implementation of a stochastic tractography algorithm in python that can be used both within and outside of the slicer framework.

Our plan for the project week is to integrate diffusion weighted imaging preprocessing steps to the pipeline in particular:

  • Rician Noise Removal
  • EPI distortion correction
  • Eddy current correction

We will also be testing pipeline on VCFS population, now that we have enough subjects to start a study and some encouraging gray matter segmentation results.

Progress

  • Achieved ITK integration through WrapITK into the python pipeline
    • cmake were adapted to reduce the so called 'combinatorial explosion' to a reasonable compilation cycle (<1h on my laptop)
    • alternative under discussion for the Slicer side: weave seems to be a better candidate
  • Tested numpy conversion to/from VTK/ITK
  • Ongoing : EPI distortion correction under test
    • Rician & EPI are cmake ready for python wrapping
  • Even if not perfect, WrapITK allows:
    • to build efficient VTK/ITK pipeline - with the python benefits
    • to integrate easily a C++ class developed in ITK/VTK: it is just up to write a small cmake configuration file
    • >90% of ITK and VTK classes are usable at once
    • quite cumbersome to understand why people argue against it ;-)

References