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 Analysis

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

  • 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

Software