2012 Winter Project Week:GeometricMetamorphosis

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Estimating the infiltration / recession of pathologies independent of background deformations

Key Investigators

  • Kitware: Danielle Pace, Stephen Aylward
  • UNC: Marc Niethammer

Objective

  • Image registration of longitudinal neuroimaging data of traumatic brain injury (TBI), with the aim of predicting long term outcome and designing treatment plans.
  • The geometric metamorphosis registration algorithm jointly estimates global background deformations and local pathology changes. This allows injury changes to be analysed without the impact of background motion.
  • Quantification of "infiltrative" versus "displacing" pathology changes may be a clinically-significant biomarker, and is enabled by geometric metamorphosis's separation of total deformation into background and pathology deformations.

Approach, Plan

  • Develop and implement voxel-wise estimates of infiltrating versus displacing pathology growth/contraction.


Progress


Delivery Mechanism

This work will be delivered to the NA-MIC Kit as a Slicer extension.

References

Marc Niethammer, Gabriel L. Hart, Danielle F. Pace, Paul M. Vespa, Andrei Irimia, John D. Van Horn, and Stephen R. Aylward, Geometric Metamorphosis, MICCAI 2011.

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