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

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==Delivery Mechanism==
 
==Delivery Mechanism==
  
This work will be delivered to the NA-MIC Kit as a:
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This work will be delivered to the NA-MIC Kit as follows:
  
#ITK Module
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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.
#Slicer Module
 
##Built-in
 
##Extension -- commandline YES
 
##Extension -- loadable
 
#Other YES
 
 
 
All software written during the project week will be contributed to TubeTK, and algorithms will be incorporated into 3D Slicer as CLI applications.
 
  
 
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Revision as of 16:49, 6 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)

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

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.