Difference between revisions of "Algorithm:UNC:DTI:Population Analysis"
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= Description = | = Description = | ||
+ | Our methodology for population analysis of DT-MRI is based on unbiased non-rigid registration of a population to a common coordinate system. The registration jointly produces an average DTI | ||
+ | atlas, which is unbiased with respect to the choice of a template im- | ||
+ | age, along with diffeomorphic correspondence between each image. The | ||
+ | registration image match metric uses a feature detector for thin fiber | ||
+ | structures of white matter, and interpolation and averaging of diffusion | ||
+ | tensors use the Riemannian symmetric space framework. The anatomi- | ||
+ | cally significant correspondence provides a basis for comparison of tensor | ||
+ | features and fiber tract geometry in clinical studies. | ||
+ | |||
= Publications = | = Publications = | ||
− | + | * Casey Goodlett, Brad Davis, Remi Jean, John Gilmore, Guido Gerig. Improved Correspondence for DTI Population Studies via Unbiased Atlas Building. Proc. MICCAI 2006, Springer LNCS v. 4191, pp. 260 - 267.[http://www.cs.unc.edu/~gcasey/research/pdfs/miccai06-dtiatlas.pdf| PDF] | |
= Software = | = Software = |
Revision as of 19:58, 2 April 2007
Home < Algorithm:UNC:DTI:Population AnalysisDescription
Our methodology for population analysis of DT-MRI is based on unbiased non-rigid registration of a population to a common coordinate system. The registration jointly produces an average DTI atlas, which is unbiased with respect to the choice of a template im- age, along with diffeomorphic correspondence between each image. The registration image match metric uses a feature detector for thin fiber structures of white matter, and interpolation and averaging of diffusion tensors use the Riemannian symmetric space framework. The anatomi- cally significant correspondence provides a basis for comparison of tensor features and fiber tract geometry in clinical studies.
Publications
- Casey Goodlett, Brad Davis, Remi Jean, John Gilmore, Guido Gerig. Improved Correspondence for DTI Population Studies via Unbiased Atlas Building. Proc. MICCAI 2006, Springer LNCS v. 4191, pp. 260 - 267.PDF