insighttoolkit - imaging toolkit for segmentation and registration
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.
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
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.
ITK is released under a BSD-style license. See
/usr/share/doc/libinsighttoolkitX.Y/copyright for the full text.
The API documentation is available in HTML generated by Doxygen, in the
Join the community by subscribing to the ITK mailing lists at
The Insight Segmentation and Registration Toolkit is developed by the
Insight Software Consortium and the ITK community.
See the project homepage http://www.itk.org/ for more information.
Oct 11, 2005