Difference between revisions of "2012 Winter Project Week:ScriptView"

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<gallery>
 
<gallery>
 
Image:PW-SLC2012.png|[[2012_Winter_Project_Week#Projects|Projects List]]
 
Image:PW-SLC2012.png|[[2012_Winter_Project_Week#Projects|Projects List]]
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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:Subj1_II.png|Subject1.
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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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Image:Subj2_II.png|Subject2.
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Image:Subj3_II.png|Subject3.
 
</gallery>
 
</gallery>
  
 
==Key Investigators==
 
==Key Investigators==
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* UNC: Isabelle Corouge, Casey Goodlett, Guido Gerig
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* GE Research: Albert Montillo  (montillo@ge.com)
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* Utah: Tom Fletcher, Ross Whitaker
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* Isomics: Steve Pieper
  
 
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<div style="margin: 20px;">
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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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Programmatically setup 3D Slicer to view data from different subjects while applying the same consistent view. Save screen image to PNG.
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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 approach is to create a template MRML scene file and reuse it for each subject. MRML scene stores relative paths to items in the scene such as volumes. Python script is passed to Slicer to load the scene per subject and save image.<foo>.
  
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Our plan for the project week is to first try out <bar>,...
 
  
 
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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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The python script has been tested on folder with multiple subject subfolders. All subject folders use same file names for scene elements so that same MRML file works for all subjects. MRML scene need only be setup once, for one subject, then reused for each subject.  
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</div>
 
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==Delivery Mechanism==
 
==Delivery Mechanism==
  
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This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)
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This work will be delivered as a python script.
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#ITK Module
 
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#Slicer Module
 
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##Built-in
 
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##Extension -- commandline
 
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##Extension -- loadable
 
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#Other (Please specify)
 
  
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==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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* 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 .
 
  
 
</div>
 
</div>

Latest revision as of 17:02, 13 January 2012

Home < 2012 Winter Project Week:ScriptView

Key Investigators

  • GE Research: Albert Montillo (montillo@ge.com)
  • Isomics: Steve Pieper

Objective

Programmatically setup 3D Slicer to view data from different subjects while applying the same consistent view. Save screen image to PNG.


Approach, Plan

Our approach is to create a template MRML scene file and reuse it for each subject. MRML scene stores relative paths to items in the scene such as volumes. Python script is passed to Slicer to load the scene per subject and save image.<foo>.


Progress

The python script has been tested on folder with multiple subject subfolders. All subject folders use same file names for scene elements so that same MRML file works for all subjects. MRML scene need only be setup once, for one subject, then reused for each subject.

Delivery Mechanism

This work will be delivered as a python script.



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