Difference between revisions of "2011 Winter Project Week:TubeTK VascularImageSegmentationAndAnalysis"

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__NOTOC__
 
__NOTOC__
 
<gallery>
 
<gallery>
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Image:TubeTK-VessTortuosity.jpg|Tortuosity for benign/malignant (Image from Dr. Bullitt, UNC)
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Image:TubeTK-USVess.png|Ultrasound to vessel registration
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Image:TubeTK-VessGraphs.jpg|Spatial graphs of vasculature capture inter-population variations
 
Image:PW-SLC2011.png|[[2011_Winter_Project_Week#Projects|Projects List]]
 
Image:PW-SLC2011.png|[[2011_Winter_Project_Week#Projects|Projects List]]
 
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* Kitware: Stephen Aylward, Danielle Pace
 
* Kitware: Stephen Aylward, Danielle Pace
 
* SPL: Steve Pieper
 
* SPL: Steve Pieper
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* Luca Antiga, Daniel Haehn
  
 
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<h3>Objective</h3>
 
<h3>Objective</h3>
[http://public.kitware.com/Wiki/TubeTK TubeTK] is a new open-source toolkit that hosts algorithms for applications involving images of tubes. By focusing on the geometry of tubes we can accomplish many of the grand challenges in medical image analysis for a wide range significant cases, e.g., disease detection, diagnosis, treatment guidance, and monitoring using vascular features.
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[http://public.kitware.com/Wiki/TubeTK TubeTK] is a new open-source toolkit that hosts algorithms for applications involving images of tubes.
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 +
Two driving applications:
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* Surgical guidance: registering pre-operative vascular models with intra-operative images (e.g., ultrasound)
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* Characterizing vascular patters: using graph theory to distinguish clinical populations based on vascular patterns (e.g., benign -vs- malignant tumors via tortuosity)
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History
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* June 2001, UNC released the patent on vessel extraction method from [Aylward, Bullitt 1996...]
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* TubeTK released under Apache 2.0 license: includes rights to patents
  
 
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<h3>Approach, Plan</h3>
 
<h3>Approach, Plan</h3>
TODO
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* Python module in Slicer 4 for centerline and radius estimation of vasculature in brain MRA
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** Workflow: brain envelop segmentation, seeding, extraction
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* Integration with VMTK
  
 
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<h3>Progress</h3>
 
<h3>Progress</h3>
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* Skype meeting with VMTK team to learn design pattern to follow
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* Extended TubeTK to include LDA methods for multi-echo MR segmentation
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** SWAN (susceptibility weighted angiography), T1, T2 data from U of Mississippi
  
 
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==Delivery Mechanism==
 
==Delivery Mechanism==
All software written during the project week will be contributed to TubeTK for release to the community.
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This work will be delivered to the NA-MIC Kit as follows:
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* All software written during the project week will be contributed to TubeTK, and algorithms will be incorporated into 3D Slicer as CLI applications.
  
 
</div>
 
</div>

Latest revision as of 17:32, 14 January 2011

Home < 2011 Winter Project Week:TubeTK VascularImageSegmentationAndAnalysis

Key Investigators

  • Kitware: Stephen Aylward, Danielle Pace
  • SPL: Steve Pieper
  • Luca Antiga, Daniel Haehn

Objective

TubeTK is a new open-source toolkit that hosts algorithms for applications involving images of tubes.

Two driving applications:

  • Surgical guidance: registering pre-operative vascular models with intra-operative images (e.g., ultrasound)
  • Characterizing vascular patters: using graph theory to distinguish clinical populations based on vascular patterns (e.g., benign -vs- malignant tumors via tortuosity)

History

  • June 2001, UNC released the patent on vessel extraction method from [Aylward, Bullitt 1996...]
  • TubeTK released under Apache 2.0 license: includes rights to patents

Approach, Plan

  • Python module in Slicer 4 for centerline and radius estimation of vasculature in brain MRA
    • Workflow: brain envelop segmentation, seeding, extraction
  • Integration with VMTK

Progress

  • Skype meeting with VMTK team to learn design pattern to follow
  • Extended TubeTK to include LDA methods for multi-echo MR segmentation
    • SWAN (susceptibility weighted angiography), T1, T2 data from U of Mississippi

Delivery Mechanism

This work will be delivered to the NA-MIC Kit as follows:

  • All software written during the project week will be contributed to TubeTK, and algorithms will be incorporated into 3D Slicer as CLI applications.