Difference between revisions of "2013 Summer Project Week:Ultrasound Calibration"

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Image:PW-MIT2013.png|[[2013_Summer_Project_Week#Projects|Projects List]]
 
Image:PW-MIT2013.png|[[2013_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:ICS-postResection.gif|[[400px|Trackerless Ultrasound Correspondence]]
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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:Slicer_img.png|[[400px|Slicer 3D US Plane Localization]]
 
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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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The goal of this project is to develop 2D ultrasound technology for image-guided procedures.
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Specifically, we focus on ultrasound image processing techniques that can operate in a complementary fashion with external probe tracking systems. For instance, to achieve 3D reconstruction and online visualization in the context of image-guided neurosurgery, where calibrated or tracked ultrasound may not be available.
  
 
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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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* Develop code (C++) for trackerless ultrasound feature matching and associated applications
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** 3D reconstruction
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Our plan for the project week is to first try out <bar>,...
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** Online visualization / navigation
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* Port to a Slicer module
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* Testing algorithms on US data provided by PLUS, Tamas.
  
 
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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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* External build of nlopt library for Slicer (Thank you jc)
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* Developed algorithm and c++ code for trackerless US plane localization
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* Developed slicer module for trackerless US plane localization
 
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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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* Code and slicer module
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* A writeup of developments/results for future publications.
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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)
 
  
 
==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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* 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 13:49, 21 June 2013

Home < 2013 Summer Project Week:Ultrasound Calibration

Key Investigators

  • BWH: Matthew Toews, Daniel Kostro, William Wells, Isaiah Norton
  • Queen's University: Tamas Ungi
  • Kitware: Stephen Aylward

Objective

The goal of this project is to develop 2D ultrasound technology for image-guided procedures.

Specifically, we focus on ultrasound image processing techniques that can operate in a complementary fashion with external probe tracking systems. For instance, to achieve 3D reconstruction and online visualization in the context of image-guided neurosurgery, where calibrated or tracked ultrasound may not be available.

Approach, Plan

  • Develop code (C++) for trackerless ultrasound feature matching and associated applications
    • 3D reconstruction
    • Online visualization / navigation
  • Port to a Slicer module
  • Testing algorithms on US data provided by PLUS, Tamas.

Progress

  • External build of nlopt library for Slicer (Thank you jc)
  • Developed algorithm and c++ code for trackerless US plane localization
  • Developed slicer module for trackerless US plane localization

Delivery Mechanism

  • Code and slicer module
  • A writeup of developments/results for future publications.

References

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