TubeTK: Difference between revisions

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* [http://open.cdash.org/index.php?project=TubeTK TubeTK Dashboard]
* [http://open.cdash.org/index.php?project=TubeTK TubeTK Dashboard]
* [https://github.com/TubeTK TubeTK GitHub]
* [https://github.com/KitwareMedical/TubeTK TubeTK GitHub]
* [https://github.com/TubeTK/TubeTK/issues TubeTK GitHub Issues]
* [https://github.com/KitwareMedical/TubeTK/issues TubeTK GitHub Issues]
* [https://github.com/TubeTK/TubeTK TubeTK GitHub Repository]
* [https://github.com/KitwareMedical/TubeTK TubeTK GitHub Repository]
* [http://midas3.kitware.com/midas/community/7 TubeTK Midas Platform Community]
* [http://midas3.kitware.com/midas/community/7 TubeTK Midas Platform Community]
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Revision as of 12:19, 12 August 2014

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TubeTK

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Overview

TubeTK is being developed to host algorithms for applications involving images of tubes (blood vessel in medical images, roads in satellite images, etc.). It also offers methods for handling other geometries (points, surfaces, and densities) in images.

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:

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

At this time TubeTK is targeted for

  1. Software developers who wish to write code to integrate our algorithms into their applications
  2. Researchers who can write bash and other scripts to string together TubeTK's command-line tools

We are working to provide modules, based on TubeTK, that allow TubeTK's methods to be called from within Slicer, Osirix, and ImageJ.

If you have questions regarding or suggestions for improving TubeTK, please do not hesitate to contact the development team.

Features

  • Centerline vascular segmentation
  • Vascular atlas formation
  • Vascular network to image registration
  • Organ segmentation
  • Vascular-ness measures
  • Multi-modality support

Driving Applications

Technical Focus

  • Vascular pattern analysis is the characterization and comparison of individuals and populations based on "spatial graphs" as representations of vascular networks.
  • Sliding organ registration are methods for registering images of multiple organs in which the organs may have shifted, expanded, or compressed independently.
  • Intra-operative ultrasound registration is the grand challenge of real-time transcription of pre-operative surgical plans into intra-operative ultrasound images.

Acknowledgement

If you find TubeTK useful for your work and publications, please include a reference to this website and to

  • S. R. Aylward and E. Bullitt, “Initialization, noise, singularities, and scale in height ridge traversal for tubular object centerline extraction,” Medical Imaging, IEEE Transactions on, vol. 21, no. 2, pp. 61–75, 2002.

Thank you!

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