Difference between revisions of "Projects:FiberTractStatistics"

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'''Objective:''' We are developing methods for analyzing diffusion tensor data along fiber tracts. The goal is to be able to make statistical group comparisons with fiber tracts as a common reference frame for comparison.
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Back to [[NA-MIC_Collaborations|NA-MIC_Collaborations]], [[Algorithm:UNC|UNC Algorithms]], [[Algorithm:Utah|Utah Algorithms]]
  
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'''Progress:''' Software for the fiber tracking and statistical analysis along the tracts has been implemented. The statistical methods for diffusion tensors are implemented as ITK code as part of the [[NA-MIC/Projects/Diffusion_Image_Analysis/DTI_Software_and_Algorithm_Infrastructure|DTI Software Infrastructure]] project. The methods have been validated on a repeated scan of a healthy individual. This work has been published as a conference paper (MICCAI 2005) and a journal version (MEDIA 2006). Our recent IPMI 2007 paper includes a nonparametric regression method for analyzing data along a fiber tract.
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= Fiber Tract Statistics =
  
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''References:''
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We are developing methods for analyzing diffusion tensor data along fiber tracts. The goal is to be able to make statistical group comparisons with fiber tracts as a common reference frame for comparison.
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* Fletcher, P.T., Tao, R., Jeong, W.-K., Whitaker, R.T., "A Volumetric Approach to Quantifying Region-to-Region White Matter Connectivity in Diffusion Tensor MRI," to appear Information Processing in Medical Imaging (IPMI) 2007.
 
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* Corouge, I., Fletcher, P.T., Joshi, S., Gilmore, J.H., and Gerig, G., "Fiber Tract-Oriented Statistics for Quantitative Diffusion Tensor MRI Analysis," Medical Image Analysis 10 (2006), 786--798.
 
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* Corouge, I., Fletcher, P.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
 
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* 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: http://hdl.handle.net/1926/39 .
 
  
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'''Key Investigators:'''
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= Description =
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Software for the fiber tracking and statistical analysis along the tracts has been implemented. The statistical methods for diffusion tensors are implemented as ITK code as part of the [[Projects:DTISoftwareAndAlgorithmInfrastructure|DTI Software Infrastructure]] project. The methods have been validated on a repeated scan of a healthy individual. This work has been published as a conference paper (MICCAI 2005) and a journal version (MEDIA 2006). Our recent IPMI 2007 paper includes a nonparametric regression method for analyzing data along a fiber tract. The AJNR-07 paper demonstrates the use of the NAMIC quantitative DTI analysis on a population of 55 neonate MR-DTI scans as part of a pre-clinical UNC study.
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{|
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|[[Image:genuFAp.jpg|thumb|320px|Scatter plot of the original FA data through the genu of the corpus callosum of a normal brain.]]
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|[[Image:genuFA.jpg|thumb|320px|Regression of FA data; solid line represents the mean and dotted lines the standard deviation.]]
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|}
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= Publications =
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''In Print''
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[http://www.na-mic.org/Special:Publications?text=Projects%3AFiberTractStatistics&submit=Search&words=all&title=checked&keywords=checked&authors=checked&abstract=checked&sponsors=checked&searchbytag=checked| NA-MIC Publications Database]
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= Key Investigators =
  
 
* UNC: Isabelle Corouge, Casey Goodlett, Guido Gerig
 
* UNC: Isabelle Corouge, Casey Goodlett, Guido Gerig
 
* Utah: Tom Fletcher, Ross Whitaker
 
* Utah: Tom Fletcher, Ross Whitaker
  
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'''Links:'''
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= Links =
  
 
* [[Progress_Report:Diffusion_Tensor_Statistics|Diffusion Tensor Statistics Progress Report]]
 
* [[Progress_Report:Diffusion_Tensor_Statistics|Diffusion Tensor Statistics Progress Report]]
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{|
 
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|[[Image:genuFAp.jpg|thumb|320px|Scatter plot of the original FA data through the genu of the corpus callosum of a normal brain.]]
 
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|[[Image:genuFA.jpg|thumb|320px|Regression of FA data; solid line represents the mean and dotted lines the standard deviation.]]
 
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|}
 

Latest revision as of 02:44, 27 November 2007

Home < Projects:FiberTractStatistics
Back to NA-MIC_Collaborations, UNC Algorithms, Utah Algorithms

Fiber Tract Statistics

We are developing methods for analyzing diffusion tensor data along fiber tracts. The goal is to be able to make statistical group comparisons with fiber tracts as a common reference frame for comparison.

Description

Software for the fiber tracking and statistical analysis along the tracts has been implemented. The statistical methods for diffusion tensors are implemented as ITK code as part of the DTI Software Infrastructure project. The methods have been validated on a repeated scan of a healthy individual. This work has been published as a conference paper (MICCAI 2005) and a journal version (MEDIA 2006). Our recent IPMI 2007 paper includes a nonparametric regression method for analyzing data along a fiber tract. The AJNR-07 paper demonstrates the use of the NAMIC quantitative DTI analysis on a population of 55 neonate MR-DTI scans as part of a pre-clinical UNC study.

Scatter plot of the original FA data through the genu of the corpus callosum of a normal brain.
Regression of FA data; solid line represents the mean and dotted lines the standard deviation.

Publications

In Print

NA-MIC Publications Database


Key Investigators

  • UNC: Isabelle Corouge, Casey Goodlett, Guido Gerig
  • Utah: Tom Fletcher, Ross Whitaker


Links

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