Difference between revisions of "Projects:DTIQuantitativeTractAnalysis"
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This project proposes a framework for quantitative analysis of DTI data. The framework uses the full tensor information for statistical analysis using the affine-invariant Riemannian metric for defining operations such as interpolation and averaging on tensors. Furtheremore, the results of tractography are used to provide a reference coordinate system the respresents the underlying structure of fiber bundles. The tract modeling framework includes a model both of the geometry of the fiber bundle and of the diffusion properties along the bundle. A new anisotropy measure called geodesic anisotropy (GA) is also included in the framework. | This project proposes a framework for quantitative analysis of DTI data. The framework uses the full tensor information for statistical analysis using the affine-invariant Riemannian metric for defining operations such as interpolation and averaging on tensors. Furtheremore, the results of tractography are used to provide a reference coordinate system the respresents the underlying structure of fiber bundles. The tract modeling framework includes a model both of the geometry of the fiber bundle and of the diffusion properties along the bundle. A new anisotropy measure called geodesic anisotropy (GA) is also included in the framework. | ||
Revision as of 16:33, 12 December 2007
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DTI Quantitative Tract Analysis
This project proposes a framework for quantitative analysis of DTI data. The framework uses the full tensor information for statistical analysis using the affine-invariant Riemannian metric for defining operations such as interpolation and averaging on tensors. Furtheremore, the results of tractography are used to provide a reference coordinate system the respresents the underlying structure of fiber bundles. The tract modeling framework includes a model both of the geometry of the fiber bundle and of the diffusion properties along the bundle. A new anisotropy measure called geodesic anisotropy (GA) is also included in the framework.
Description
Publications
Key Investigators
- UNC: Isabelle Corouge, Casey Goodlett, Guido Gerig
Links
Project Week Results: Jun 2005
