2011 Winter Project Week:TubeTK VascularImageSegmentationAndAnalysis

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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.