Difference between revisions of "NA"

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'''Objective:''' We are developing new denoising methods for diffusion tensor MRI. These methods are based on physical noise models in DT-MRI.
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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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'''Progress:''' We have implemented several filtering methods for DT-MRI, including our new method and also several methods from the literature. One goal is to determine whether it is best to filter the estimated tensor fields or the original diffusion weighted images. The method that we developed filters the original diffusion weighted images and takes into account the physical properties of the imaging noise. We are comparing this method with others in the literature, including methods that filter the estimated tensor fields. Our preliminary findings are that it is advantageous to filter the DWIs and to include a physical model of the noise.
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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 has been submitted.
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''References:''
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* 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
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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 .
  
 
'''Key Investigators:'''
 
'''Key Investigators:'''
  
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* Utah: Saurav Basu, Tom Fletcher, Ross Whitaker
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* UNC: Isabelle Corouge, Casey Goodlett, Guido Gerig
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* Harvard PNL: Sylvain Bouix, Doug Marchant, Adam Cohen, Marc Niethammer, Marek Kubicki, Mark Dreusicke, Martha Shenton
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* Utah: Tom Fletcher, Ross Whitaker
  
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'''Links'''
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'''Links:'''
  
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* [[AHM_2006:ProjectsRiemmanianDTIFilters|Programming Event Project Page (January 2006)]]
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* [[Progress_Report:Diffusion_Tensor_Statistics|Diffusion Tensor Statistics Progress Report]]

Revision as of 13:28, 18 December 2006

Home < NA

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.

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 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 has been submitted.

References:

  • 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
  • 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 .

Key Investigators:

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

Links:

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