Difference between revisions of "2012 Summer Project Week:Nipype Integration"

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Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
 
Image:PW-MIT2012.png|[[2012_Summer_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:BAW.png
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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 2012_Winter_Project_Week:<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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* UIowa: Hans Johnson
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* Utah: Tom Fletcher, Ross Whitaker
 
  
 
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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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Nipype is a flexible, uniform interface to existing neuroimaging software that allows interaction between these packages within a single workflow. Our objective is to improve on Nipype's interaction with Slicer, with the goal of being able to pass scripts to Slicer's python interface that allow pipeline development within Slicer.
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<h3>Approach, Plan</h3>
 
<h3>Approach, Plan</h3>
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# Meet with Satra
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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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# Discuss python environment with JC and Steve and others
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# Determine how python modules can be more easily incorporated with Slicer
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Our plan for the project week is to first try out <bar>,...
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# Investigate updates to Numpy and Scipy
  
 
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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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SlicerCLI  modules created and wrapped with nipype outside of Slicer
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==Delivery Mechanism==
 
==Delivery Mechanism==
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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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* Nipype: http://nipy.sourceforge.net/nipype/ [http://nipy.sourceforge.net/nipype/]
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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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* Consider merging the [https://github.com/pieper/Slicer/tree/syspy system python] changes as a way to give easy access.
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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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* Consider bundling python executable with slicer to simplify installation of python packages.
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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 .
 
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Latest revision as of 16:48, 18 June 2012

Home < 2012 Summer Project Week:Nipype Integration

Key Investigators

  • UIowa: Hans Johnson

Objective

Nipype is a flexible, uniform interface to existing neuroimaging software that allows interaction between these packages within a single workflow. Our objective is to improve on Nipype's interaction with Slicer, with the goal of being able to pass scripts to Slicer's python interface that allow pipeline development within Slicer.

Approach, Plan

  1. Meet with Satra
  2. Discuss python environment with JC and Steve and others
  3. Determine how python modules can be more easily incorporated with Slicer
  4. Investigate updates to Numpy and Scipy

Progress

SlicerCLI modules created and wrapped with nipype outside of Slicer

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

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