Documentation/4.2/Extensions/TubeTK

Introduction and Acknowledgements

Author: Stephen Aylward
Contributors: Stephen Aylward (Kitware), Jean-Christophe Fillion-Robin (Kitware), Christopher Mullins (Kitware), Michael Jeulin-L (Kitware), Matthew McCormick (Kitware)
Contact: Christopher Mullins, <email>christopher.mullins@kitware.com</email>
Website: http://www.tubetk.org/
License: TubeTK License

Extension Description

TubeTK is an open-source toolkit for the segmentation, registration, and analysis of tubes and surfaces in images.

Tubes and surfaces, as generalized 1D and 2D manifolds in N-dimensional images, are essential components in a variety of image analysis tasks. Instances of tubular structures in images include blood vessels in magnetic resonance angiograms and b-mode ultrasound images, wires in microscopy images of integrated circuits, roads in areal photographs, and nerves in confocal microscopy.

Longterm Goals

By focusing on local geometric structure, the algorithms are able to accomplish segmentations, registrations, and other analyses that consider the physicial properties of objects and their variations, while not requiring limiting assumptions on the specific arrangement or general shape of the objects in the images. We are applying these techniques to push image understanding in new directions such as:

• registration of abdominal images even when organs slides against one another
• forming statistical atlases of intra-canrial vessel network topology even when that topology changes between subjects
• segmentation of arbitrary objects in images even when intensity statistics of those objects, and the objects around them, vary from image to image.

Modules

• TubeTK Anisotropic Diffusive Deformable Registration
• TubeTK Coherence-Enhancing Anisotropic Diffusion
• TubeTK Compute Binary Image Similary
• TubeTK Compute Image Similarity
• TubeTK Connected Components
• TubeTK Compute Contrast Image Using Prior
• TubeTK Crop
• TubeTK Deblend Images Using Prior
• TubeTK Edge Enhancing Anisotropic Diffusion
• TubeTK Extract Curves 2D
• TubeTK Ridge Extractor
• TubeTK Extract Vessel Seeds
• TubeTK Hessian Tubeness 2D
• TubeTK Hybrid-Enhancing Anisotropic Diffusion
• TubeTK LDA Generator
• TubeTK Mask To Stats
• TubeTK Match Image With Prior
• TubeTK Merge
• TubeTK NJet Linear Discriminant Analysis
• TubeTK Otsu Threshold Application
• TubeTK PDF Region Growing
• TubeTK Resample Images
• TubeTK Sample CLI Application
• TubeTK Skeletonize

Acknowledgements

The development of TubeTK is being funded, in part, by the following grants

• 1. NIH/NIBIB sponsored "National Alliance of Medical Image Computing" (NA-MIC, PI: Kikinis) project
  • 1U54EB005149-01
  • NA-MIC
• 2. DARPA sponsored "Trust in Integrated Circuits" (EXPOSE, PI: Bajura) program
  • USC/ISI Team
  • DARPA
• 3. NIH/NCI sponsored "Image Registration for Ultrasound-Based Neurosurgical Navigation" (NeuralNav, PI: Aylward, Wells)
  • 1R01CA138419-01
  • NeuralNav