View source for 2012 Winter Project Week:GeometricMetamorphosis

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Image:PW-SLC2012.png|[[2012_Winter_Project_Week#Projects|Projects List]]
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==Estimating the infiltration / recession of pathologies independent of background deformations ==


==Key Investigators==
* Kitware: Danielle Pace, Stephen Aylward
* UNC: Marc Niethammer

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<h3>Objective</h3>
* 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.
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<h3>Approach, Plan</h3>
* Develop and implement voxel-wise estimates of infiltrating versus displacing pathology growth/contraction.



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<h3>Progress</h3>


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==Delivery Mechanism==

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

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