Difference between revisions of "2012 Winter Project Week:GeometricMetamorphosis"
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| − | + | * 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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| − | * | + | * Develop and implement voxel-wise estimates of infiltrating versus displacing pathology growth/contraction. |
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<h3>Progress</h3> | <h3>Progress</h3> | ||
| − | + | * Built CALA-TK: Cross-sectional And Longitudinal Atlas toolkit | |
| + | * Fixed some small bugs to get geometric metamorphosis CLI into Slicer | ||
| + | * Got Slicer change tracker running on my data, with help of Andriy | ||
| + | * Future work is integrating geometric metamorphosis into change tracker | ||
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This work will be delivered to the NA-MIC Kit as a Slicer extension. | This work will be delivered to the NA-MIC Kit as a Slicer extension. | ||
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| + | ==References== | ||
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| + | 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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Latest revision as of 15:12, 13 January 2012
Home < 2012 Winter Project Week:GeometricMetamorphosis
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
- Built CALA-TK: Cross-sectional And Longitudinal Atlas toolkit
- Fixed some small bugs to get geometric metamorphosis CLI into Slicer
- Got Slicer change tracker running on my data, with help of Andriy
- Future work is integrating geometric metamorphosis into change tracker
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.
