Difference between revisions of "2012 Summer Project Week:Intraoperative Tract Detection"

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Image:genuFA.jpg|Regression of FA data; solid line represents the mean and dotted lines the standard deviation.
 
Image:genuFA.jpg|Regression of FA data; solid line represents the mean and dotted lines the standard deviation.
 
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==Instructions for Use of this Template==
 
#Please create a new wiki page with an appropriate title for your project using the convention 2012_Winter_Project_Week:<Project Name>
 
#Copy the entire text of this page into the page created above
 
#Link the created page into the list of projects for the project event
 
#Delete this section from the created page
 
#Send an email to tkapur at bwh.harvard.edu if you are stuck
 
  
 
==Key Investigators==
 
==Key Investigators==
* UNC: Isabelle Corouge, Casey Goodlett, Guido Gerig
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* BWH: Lauren O'Donnell, Isaiah Norton, Alex Golby
* Utah: Tom Fletcher, Ross Whitaker
 
  
 
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<h3>Objective</h3>
 
<h3>Objective</h3>
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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We are developing methods for intraoperative tract detection based on a preoperative plan.
 
 
 
 
 
 
 
 
 
 
  
 
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<h3>Approach, Plan</h3>
 
<h3>Approach, Plan</h3>
  
Our approach for analyzing diffusion tensors is summarized in the IPMI 2007 reference below. The main challenge to this approach is <foo>.
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Our approach for tract detection is to compare new tracts to the prior information (preoperative plan).
 
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Our plan for the project week is to integrate Python code into a slicer module <bar>,...
Our plan for the project week is to first try out <bar>,...
 
  
 
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<h3>Progress</h3>
 
<h3>Progress</h3>
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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==References==
 
==References==
*Fletcher P, Tao R, Jeong W, Whitaker R. [http://www.na-mic.org/publications/item/view/634 A volumetric approach to quantifying region-to-region white matter connectivity in diffusion tensor MRI.] Inf Process Med Imaging. 2007;20:346-358. PMID: 17633712.
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* Corouge I, Fletcher P, Joshi S, Gouttard S, Gerig G. [http://www.na-mic.org/publications/item/view/292 Fiber tract-oriented statistics for quantitative diffusion tensor MRI analysis.] Med Image Anal. 2006 Oct;10(5):786-98. PMID: 16926104.
 
* Corouge I, Fletcher P, Joshi S, Gilmore J, Gerig G. [http://www.na-mic.org/publications/item/view/1122 Fiber tract-oriented statistics for quantitative diffusion tensor MRI analysis.] Int Conf Med Image Comput Comput Assist Interv. 2005;8(Pt 1):131-9. PMID: 16685838.
 
* Goodlett C, Corouge I, Jomier M, Gerig G, 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 .
 

Revision as of 16:31, 15 June 2012

Home < 2012 Summer Project Week:Intraoperative Tract Detection

Key Investigators

  • BWH: Lauren O'Donnell, Isaiah Norton, Alex Golby

Objective

We are developing methods for intraoperative tract detection based on a preoperative plan.

Approach, Plan

Our approach for tract detection is to compare new tracts to the prior information (preoperative plan). Our plan for the project week is to integrate Python code into a slicer module <bar>,...

Progress


Delivery Mechanism

This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)

  1. ITK Module
  2. Slicer Module
    1. Built-in
    2. Extension -- commandline
    3. Extension -- loadable
  3. Other (Please specify)

References