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.