Difference between revisions of "2010 Winter Project Week MultiscaleLupusAnalyses"

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Image:PW-SLC2010.png|[[2010_Winter_Project_Week#Projects|Projects List]]
 
Image:PW-SLC2010.png|[[2010_Winter_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.
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Image:LupusLesionTractsFar.png|DTI Tracts passing near or through lesions
Image:genuFA.jpg|Regression of FA data; solid line represents the mean and dotted lines the standard deviation.
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Image:LesionTractsNear.png|Zoomed in on a lesion (red volume)
 
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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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* MRN: Mark Scully, Jeremy Bockholt
* Utah: Tom Fletcher, Ross Whitaker
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* BWH: Steve Pieper
  
 
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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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To combine the multiple types of available neuroimaging data in to a multiscale analysis of a lupus patient.
 
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Perform a multiscale analysis using sMR, DWI, ASL, and an fMR rest task on a lupus patient
  
  
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<h3>Approach, Plan</h3>
 
<h3>Approach, Plan</h3>
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Use various existing NAMIC analysis pipelines to process each type of neuroimaging data and then combine all resulting features into a single statistical analysis.
  
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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Implement any functionality that doesn't currently exist in the NAMIC kit.
 
 
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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'''1.''' Experimented with multiple DWI pipelines and started processing data using GTRACT
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'''2.''' Implemented a module to perform cross-correlation of the signals created by averaging all voxels within an anatomical region per TR using a rest task during fMRI.  
  
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'''3.''' Applied Cortical Thickness and Stochastic Tractography modules to our test data.
  
 
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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.
 
* 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 .
 
  
 
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Latest revision as of 16:59, 8 January 2010

Home < 2010 Winter Project Week MultiscaleLupusAnalyses

Key Investigators

  • MRN: Mark Scully, Jeremy Bockholt
  • BWH: Steve Pieper

Objective

To combine the multiple types of available neuroimaging data in to a multiscale analysis of a lupus patient. Perform a multiscale analysis using sMR, DWI, ASL, and an fMR rest task on a lupus patient



Approach, Plan

Use various existing NAMIC analysis pipelines to process each type of neuroimaging data and then combine all resulting features into a single statistical analysis.

Implement any functionality that doesn't currently exist in the NAMIC kit.

Progress

1. Experimented with multiple DWI pipelines and started processing data using GTRACT

2. Implemented a module to perform cross-correlation of the signals created by averaging all voxels within an anatomical region per TR using a rest task during fMRI.

3. Applied Cortical Thickness and Stochastic Tractography modules to our test data.

References