Difference between revisions of "BSpline Registration in Slicer3"

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Image:PW2009-v3.png|[[2009_Summer_Project_Week|Project Week Main Page]]
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Image:PW2009-v3.png|[[2009_Summer_Project_Week#Projects|Projects List]]
Image:genuFAp.jpg|Scatter plot of the original FA data through the genu of the corpus callosum of a normal brain.
 
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 Project/<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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* GE: Jim Miller
* Utah: Tom Fletcher, Ross Whitaker
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* Utah: Ross Whitaker, Samuel Gerber
  
 
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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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BSpline image registration module for Slicer3
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<h3>Progress</h3>
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* Standalone Bspline registration is working.
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* Registration in physical coordinates
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* Identified a set of test cases
 
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<h3>Further task</h3>
<h3>Approach, Plan</h3>
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* Smarter regularization - Less user interaction
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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* Compare to elastic registration.
 
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* Simple registration module - either bspline or elastic
Our plan for the project week is to first try out <bar>,...
 
 
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<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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* [[Projects:DBP2:Harvard:Registration_Documentation |Harvard DBP Experience with registration]]
* 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.
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* [http://slicer.spl.harvard.edu/slicerWiki/index.php/Stanford_Simbios_group Stanford Simbios Data and Results]
* 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.
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*[http://www.cs.utah.edu/~sgerber/tmp/bspline.tar.gz Standalone bspline code and examples]
* 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 .
 

Latest revision as of 02:08, 26 June 2009

Home < BSpline Registration in Slicer3


Key Investigators

  • GE: Jim Miller
  • Utah: Ross Whitaker, Samuel Gerber

Objective

BSpline image registration module for Slicer3

Progress

  • Standalone Bspline registration is working.
  • Registration in physical coordinates
  • Identified a set of test cases

Further task

  • Smarter regularization - Less user interaction
  • Compare to elastic registration.
  • Simple registration module - either bspline or elastic

References