Algorithm:UNC:DTI:Population Analysis - Revision history

Gcasey: Added figures and improved description

2007-04-03T16:13:26Z

Added figures and improved description

Gcasey: added feature images

2007-04-02T20:37:43Z

added feature images

Gcasey at 19:58, 2 April 2007

2007-04-02T19:58:25Z

Gcasey at 19:58, 2 April 2007

2007-04-02T19:58:06Z

Gcasey at 16:38, 2 April 2007

2007-04-02T16:38:46Z

Gcasey at 16:33, 2 April 2007

2007-04-02T16:33:51Z

Gcasey at 16:31, 2 April 2007

2007-04-02T16:31:53Z

Andy: Update from Wiki

2006-12-18T13:34:39Z

Update from Wiki

New page

= Description =

= Publications =

= Software =

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 [[Image:goodlett_dti_atlas_flowchart.png]]
-Our registration procedure is based on a scalar feature image which is sensitive to sheet like structures.  We have observed that the major fiber bundles of interest occur as sheet or tube like manifolds in the FA image of the brain.  As a feature image we use the maximum eigenvalue of the hessian of the FA image.
+[[Image:cbg-dtiatlas-tensors.png|thumb|right|320px|Tensors in Splenium]]
-{| border="1"
+Our registration procedure is based on a scalar feature image which is sensitive to sheet like structures.  We have observed that the major fiber bundles of interest occur as sheet or tube like manifolds in the FA image of the brain.  As a feature image we use the maximum eigenvalue of the hessian of the FA image.  Images are initially aligned using an affine registration and then deformed to a common coordinate system using the unbiased atlas-building procedure of Joshi et al. [http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=15501084&dopt=Citation].  The deformation fields produced by the registration process are applied to the tensors fields using appropriate methods for reorienting and interpolating tensors.  The transformed images are averaged in the atlas space to produce a DTI atlas.
-|+'''Scalar feature image'''
-|-
+An initial test was performed by using the procedure on a set of images of healthy subject at age one year.  The results of the tensor averaging are shown on the right.  Tractography was also performed on the mean atlas image as shown.
 = Publications =

@@ Line 1: / Line 1: @@
 = 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-
+atlas, which is unbiased with respect to the choice of a template image, 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-
+tensors use the Riemannian symmetric space framework. The anatomically significant correspondence provides a basis for comparison of tensor
 features and fiber tract geometry in clinical studies.
 = Publications =

@@ Line 8: / Line 8: @@
 cally significant correspondence provides a basis for comparison of tensor
 features and fiber tract geometry in clinical studies.
 = Publications =

@@ Line 2: / Line 2: @@
 = Publications =
-* Fiber Tract-Oriented Statistics for Quantitative Diffusion Tensor MRI Analysis, Isabelle Corouge, P.Thomas Fletcher, Sarang Joshi, Sylvain Gouttard, Guido Gerig, Medical Image Analysis 10 (2006), 786 - 798 [http://www.cs.unc.edu/~gerig/publications/Corouge-DTI-Original-MedIA-2006.pdf|PDF]
+* Fiber Tract-Oriented Statistics for Quantitative Diffusion Tensor MRI Analysis, Isabelle Corouge, P.Thomas Fletcher, Sarang Joshi, Sylvain Gouttard, Guido Gerig, Medical Image Analysis 10 (2006), 786 - 798 [http://www.cs.unc.edu/~gerig/publications/Corouge-DTI-Original-MedIA-2006.pdf| PDF]
 * C. Goodlett, I. Corouge, M. Jomier, and G. Gerig, A Quantitative DTI Fiber Tract Analysis Suite, The Insight Journal, vol. ISC/NAMIC/ MICCAI Workshop on Open-Source Software, 2005, Online publication
 * Corouge, I., Fletcher, T., Joshi, S., Gilmore J.H., and Gerig, G., Fiber Tract-Oriented Statistics for Quantitative Diffusion Tensor MRI Analysis, Lecture Notes in Computer Science LNCS, James S. Duncan and Guido Gerig, editors, Springer Verlag, Vol. 3749, Oct. 2005, pp. 131 -- 138
 = Software =

← Older revision		Revision as of 16:31, 2 April 2007
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	= Publications =		= Publications =
		+	* Fiber Tract-Oriented Statistics for Quantitative Diffusion Tensor MRI Analysis, Isabelle Corouge, P.Thomas Fletcher, Sarang Joshi, Sylvain Gouttard, Guido Gerig, Medical Image Analysis 10 (2006), 786 - 798 [http://www.cs.unc.edu/~gerig/publications/Corouge-DTI-Original-MedIA-2006.pdf\|PDF]
		+	* C. Goodlett, I. Corouge, M. Jomier, and G. Gerig, A Quantitative DTI Fiber Tract Analysis Suite, The Insight Journal, vol. ISC/NAMIC/ MICCAI Workshop on Open-Source Software, 2005, Online publication
		+	* Corouge, I., Fletcher, T., Joshi, S., Gilmore J.H., and Gerig, G., Fiber Tract-Oriented Statistics for Quantitative Diffusion Tensor MRI Analysis, Lecture Notes in Computer Science LNCS, James S. Duncan and Guido Gerig, editors, Springer Verlag, Vol. 3749, Oct. 2005, pp. 131 -- 138

	= Software =		= Software =