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.\" Hey, EMACS: -*- nroff -*-
.TH INSIGHTTOOLKIT 3 "Oct 11, 2005"
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.SH NAME
insighttoolkit \- imaging toolkit for segmentation and registration
.SH DESCRIPTION
This manual page briefly documents the
.B Insight Toolkit
(ITK).
.PP
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.
.PP
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.
.PP
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.
.SH HISTORY
In 1999 the US
.B 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
.B 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.
.SH LICENSE
ITK is released under a BSD-style license. See
/usr/share/doc/libinsighttoolkitX.Y/copyright for the full text.
.SH API REFERENCE
The API documentation is available in HTML generated by Doxygen, in the
insighttoolkit-doc package.
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.\" .SH SEE ALSO
.\" .BR bar (1),
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.SH MAILING LIST
Join the community by subscribing to the ITK mailing lists at
http://www.itk.org/HTML/MailingLists.htm.
.SH AUTHORS
.PP
The
.B Insight Segmentation and Registration Toolkit
is developed by the
.B Insight Software Consortium
and the ITK community.
.SH SEE ALSO
See the project homepage
.B http://www.itk.org/
for more information.
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