Difference between revisions of "2009 Summer Project Week Registration for RT"

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__NOTOC__
 
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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|Project Week Main Page]]
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Image:genuFAp.jpg|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|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==
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#Please create a new wiki page with an appropriate title for your project using the convention Project/<Project Name>
 
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#Copy the entire text of this page into the page created above
 
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#Link the created page into the list of projects for the project event
 
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#Delete this section from the created page
 
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#Send an email to tkapur at bwh.harvard.edu if you are stuck
 
  
 
==Key Investigators==
 
==Key Investigators==
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* UNC: Isabelle Corouge, Casey Goodlett, Guido Gerig
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* BWH: Sandy Wells, Tina Kapur
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* Utah: Tom Fletcher, Ross Whitaker
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* U Michigan: James Balter, Dan McShan
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* MGH: Lilla Zollei, Greg Sharp
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* NVIDIA: Joe Stam
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*Mayo: Dan Blezek
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*Kitware: Sebastien Barre
  
 
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<h3>Objective</h3>
 
<h3>Objective</h3>
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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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We will be taking an inventory of 2d/3d registration algorithms available between our groups, and accelerating at least one using CUDA for NVIDIA hardware.
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<h3>Approach, Plan</h3>
 
<h3>Approach, Plan</h3>
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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 plan for the project week is to first try out <bar>,...
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DRR creation is a compute+memory intensive task of our 2d/3d registration algorithms and we plan to accelerate that using CUDA.
 
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<h3>Progress</h3>
 
<h3>Progress</h3>
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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 [[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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We achieved the following:
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*started cuda acceleration of the drr creation routine from plastimatch (greg sharp)
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*started using cmake for 2d/3d registration code base from mvis (sandy wells)
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*obtained phantom data (CT and projections) from U Michigan
  
 
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==References==
 
==References==
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*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.
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* 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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</div>
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* 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 12:55, 26 June 2009

Home < 2009 Summer Project Week Registration for RT


Key Investigators

  • BWH: Sandy Wells, Tina Kapur
  • U Michigan: James Balter, Dan McShan
  • MGH: Lilla Zollei, Greg Sharp
  • NVIDIA: Joe Stam
  • Mayo: Dan Blezek
  • Kitware: Sebastien Barre

Objective

We will be taking an inventory of 2d/3d registration algorithms available between our groups, and accelerating at least one using CUDA for NVIDIA hardware.




Approach, Plan


DRR creation is a compute+memory intensive task of our 2d/3d registration algorithms and we plan to accelerate that using CUDA.

Progress

We achieved the following:

  • started cuda acceleration of the drr creation routine from plastimatch (greg sharp)
  • started using cmake for 2d/3d registration code base from mvis (sandy wells)
  • obtained phantom data (CT and projections) from U Michigan

References

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