INSIGHTTOOLKIT(3)
NAME
insighttoolkit - imaging toolkit for segmentation and registration
DESCRIPTION
This manual page briefly documents the Insight Toolkit (ITK).
ITK is an open-source software toolkit for performing registration and
segmentation. Segmentation is the process of identifying and classifying data found in a digitally sampled representation. Typically the
sampled representation is an image acquired from such medical instrumentation as CT or MRI scanners. Registration is the task of aligning
or developing correspondences between data. For example, in the medical
environment, a CT scan may be aligned with a MRI scan in order to combine the information contained in both.
ITK is implemented in C++. In addition, an automated wrapping process
generates interfaces between C++ and interpreted programming languages
such as Tcl, Java, and Python. This enables developers to create software using a variety of programming languages. ITK's C++ implementation
style is referred to as generic programming. Such C++ templating means
that the code is highly efficient, and that the many software problems
are discovered at compile-time, rather than at run-time during program
execution.
Because ITK is an open-source project, developers from around the world
can use, debug, maintain, and extend the software. ITK uses a model of
software development referred to as Extreme Programming. Extreme Programming collapses the usual software creation methodology into a
simultaneous and iterative process of design-implement-test-release.
The key features of Extreme Programming are communication and testing.
Communication among the members of the ITK community is what helps manage the rapid evolution of the software. Testing is what keeps the
software stable. In ITK, an extensive testing process is in place that
measures the quality on a daily basis.
HISTORY
In 1999 the US National Library of Medicine
[http://www.nlm.nih.gov/nlmhome.html] of the National Institutes of
Health awarded a three-year contract to develop an open-source registration and segmentation toolkit, which eventually came to be known as
the Insight Toolkit (ITK). The primary purpose of the project is to
support the Visible Human Project [http://www.nlm.nih.gov/research/visible/visible_human.html] by providing software tools to process and
work with the project data. ITK's NLM Project Manager was Dr. Terry
Yoo, who coordinated the six prime contractors who made up the Insight
consortium. These consortium members included the three commercial
partners GE Corporate R&D, Kitware, Inc., and MathSoft (the company
name is now Insightful); and the three academic partners University of
North Carolina (UNC), University of Tennessee (UT), and University of
Pennsylvania (UPenn). The Principle Investigators for these partners
were, respectively, Bill Lorensen at GE CRD, Will Schroeder at Kitware,
Vikram Chalana at Insightful, Stephen Aylward with Luis Ibanez at UNC
(Luis is now at Kitware), Ross Whitaker with Josh Cates at UT (both now
at Utah), and Dimitri Metaxas at UPenn. In addition, several subcontractors rounded out the consortium including Peter Raitu at Brigham &
Women's Hospital, Celina Imielinska and Pat Molholt at Columbia University, Jim Gee at UPenn's Grasp Lab, and George Stetton at University of
Pittsburgh.
LICENSE
ITK is released under a BSD-style license. See /usr/share/doc/libinsighttoolkitX.Y/copyright for the full text.
API REFERENCE
The API documentation is available in HTML generated by Doxygen, in the
insighttoolkit-doc package.
MAILING LIST
Join the community by subscribing to the ITK mailing lists at
http://www.itk.org/HTML/MailingLists.htm.
AUTHORS
The Insight Segmentation and Registration Toolkit is developed by the Insight Software Consortium and the ITK community.
SEE ALSO
- See the project homepage http://www.itk.org/ for more information.