Difference between revisions of "Projects/Diffusion/2007 Project Week DTI Population Analysis"

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http://www.na-mic.org/Wiki/index.php/NA-MIC/Projects/Theme/Template - Please cut and paste the template from this page and use it hereThis will be the replacement for the 4-block.
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[[Image:ProjectWeek-2007.png|thumb|320px|Return to [[2007_Programming/Project_Week_MIT|Project Week Main Page]] ]]
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__NOTOC__
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===Key Investigators===
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* UNC: Casey Goodlett, Guido Gerig
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* Harvard: Marek Kubicki
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<div style="margin: 20px;">
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<div style="width: 27%; float: left; padding-right: 3%;">
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<h1>Objective</h1>
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We are developing methods for building atlases of DTI data to provide a reference coordinate system for statistical analysis.
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</div>
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<div style="width: 27%; float: left; padding-right: 3%;">
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<h1>Approaches and Challenges </h1>
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Our approach for building a DTI atlas is based on non-rigid registration of tensor images using a shape measure for the tensor images to drive the registration processOur goal is to separate the shape variability from the diffusion variability through the registration process.
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</div>
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<div style="width: 40%; float: left;">
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<h1>Progress</h1>
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====June 2007 Project Week====
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Our goal for the project week is to perform statistical analysis on the data provided by the PNL, which has already been registered using the procedure described in the links below.
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</div>
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<br style="clear: both;" />
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</div>
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==Additional Information==
 
==Additional Information==
  
Link to Additional Information about this project here.
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*[[Algorithm:UNC:DTI#Population_Analysis| Description of atlas procedure]]
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* Goodlett C, Davis B, Jean R, Gilmore J, Gerig G. Improved Correspondence for DTI Population Studies via Unbiased Atlas Building. MICCAI, 2006.  [[Media:Goodlett-miccai06.pdf|PDF]]

Revision as of 23:41, 25 May 2007

Home < Projects < Diffusion < 2007 Project Week DTI Population Analysis


Key Investigators

  • UNC: Casey Goodlett, Guido Gerig
  • Harvard: Marek Kubicki


Objective

We are developing methods for building atlases of DTI data to provide a reference coordinate system for statistical analysis.


Approaches and Challenges

Our approach for building a DTI atlas is based on non-rigid registration of tensor images using a shape measure for the tensor images to drive the registration process. Our goal is to separate the shape variability from the diffusion variability through the registration process.

Progress


June 2007 Project Week

Our goal for the project week is to perform statistical analysis on the data provided by the PNL, which has already been registered using the procedure described in the links below.




Additional Information

  • Description of atlas procedure
  • Goodlett C, Davis B, Jean R, Gilmore J, Gerig G. Improved Correspondence for DTI Population Studies via Unbiased Atlas Building. MICCAI, 2006. PDF