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Name
TurtleSeg
Byline
MIAL, Simon Fraser University and BiSICL, University of British Columbia
Description

TurtleSeg is an interactive segmentation tool originally designed for 3D medical images. TurtleSeg is developed at the Medical Image Analysis Lab at Simon Fraser University and the Biomedical Signal and Image Computing Laboratory at the University of British Columbia.

Accurate and automatic 3D medical image segmentation remains an elusive goal and manual intervention is often unavoidable. TurtleSeg implements techniques that allow the user to provide intuitive yet minimal interaction for guiding the 3D segmentation process.

A typical workflow involves having the user load a 3D image and then use 2D Livewire to manually contour a sparse number of different slices. The full 3D segmentation can then be built automatically using the user-provided information. TurtleSeg is named after the Turtlemap 3D Livewire algorithm [1] implemented in TurtleSeg for constructing the 3D segmentation. The algorithm employs the concept of a "Turtlemap" in order to automatically produce a dense set of parallel segmentation contours from a sparse set of user provided contours.

NIfTI-1 support
The NIfTI file format is supported by TurtleSeg in a limited fashion. We use ITK 3.16.0's NIfTI file IO functionality.
Creator
Andrew Top, Ghassan Hamarneh and Rafeef Abugharbieh
Contact
feedback@turtleseg.org
WWW
http://www.turtleseg.org/
Availability
Free, 1-year license
How to get
Download information is at www.turtleseg.org.
Current version
1.2.0.1614
Current version release date
December 12th, 2011
Open source
No
License
1-year free usage, LGPL and BSD.
Available free of charge
Yes
Requirements
Technical publications

  1. Andrew Top, Ghassan Hamarneh, and Rafeef Abugharbieh. Active Learning for Interactive 3D Image Segmentation In Medical Image Computing and Computer-Assisted Intervention (MICCAI), volume 6893, pages 603-610, 2011.
  2. Andrew Top, Ghassan Hamarneh, and Rafeef Abugharbieh. Spotlight: Automated Confidence-based User Guidance for Increasing Efficiency in Interactive 3D Image Segmentation. In Medical Image Computing and Computer-Assisted Intervention Workshop on Medical Computer Vision (MICCAI MCV), pages 204-213, 2010.
  3. Miranda Poon, Ghassan Hamarneh, and Rafeef Abugharbieh. Efficient Interactive 3D Livewire Segmentation of Objects with Arbitrarily Topologies. Computerized Medical Imaging and Graphics, volume 32, pages 639-650, 2008.
  4. Miranda Poon, Ghassan Hamarneh, and Rafeef Abugharbieh. Segmentation of Complex Objects with Non-Spherical Topologies from Volumetric Medical Images using 3D Livewire. In SPIE Medical Imaging, volume 6512, pages 1-10, 2007.
  5. Ghassan Hamarneh, Johnson Yang, Chris McIntosh, and Morgan Langille. 3D live-wire-based semi-automatic segmentation of medical images. In SPIE Medical Imaging, volume 5747, pages 1597-1603, 2005.

Applications publications
Other information
Keywords
NIfTI-1 support, segmentation, visualization, volume
Platforms
Windows
IATR listing last updated
12 Dec 2011