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| title | chunk | source | category | tags | date_saved | instance |
|---|---|---|---|---|---|---|
| Insight Segmentation and Registration Toolkit | 1/2 | https://en.wikipedia.org/wiki/Insight_Segmentation_and_Registration_Toolkit | reference | science, encyclopedia | 2026-05-05T10:11:55.021887+00:00 | kb-cron |
ITK is a cross-platform, open-source application development framework widely used for the development of image segmentation and image registration programs. 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 an MRI scan in order to combine the information contained in both. ITK was developed with funding from the National Library of Medicine (U.S.) as an open resource of algorithms for analyzing the images of the Visible Human Project. ITK stands for The Insight Segmentation and Registration Toolkit. The toolkit provides leading-edge segmentation and registration algorithms in two, three, and more dimensions. ITK uses the CMake build environment to manage the configuration process. The software is implemented in C++ and it is wrapped for Python. An offshoot of the ITK project providing a simplified interface to ITK in eight programming languages, SimpleITK, is also under active development.
== Introduction ==
=== Origins === In 1999 the US National Library of Medicine 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). ITK's NLM Project Manager was Dr. Terry Yoo, who coordinated the six prime contractors who made up the Insight Software 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 Principal Investigators for these partners were, respectively, Bill Lorensen at GE CRD, Will Schroeder at Kitware, Vikram Chalana at Insightful, Stephen Aylward with Luis Ibáñez at UNC (both of whom subsequently moved to Kitware), Ross Whitaker with Josh Cates at UT (both now at Utah), and Dimitris Metaxas at UPenn (Dimitris Metaxas is now at Rutgers University). In addition, several subcontractors rounded out the consortium including Peter Ratiu at Brigham & Women's Hospital, Celina Imielinska and Pat Molholt at Columbia University, Jim Gee at UPenn's Grasp Lab, and George Stetten at University of Pittsburgh.
=== Technical details === 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 an MRI scan in order to combine the information contained in both. ITK is implemented in C++. ITK is cross-platform, using the CMake build environment to manage the compilation process. In addition, an automated wrapping process generates interfaces between C++ and other programming languages such as Java and Python. This enables developers to create software using a variety of programming languages. ITK's implementation employs the technique of generic programming through the use of C++ templates. 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 (using CDash) is in place that measures the quality on a daily basis. The ITK Testing Dashboard is posted continuously, reflecting the quality of the software.
=== Developers and contributors === The Insight Toolkit was initially developed by six principal organizations
Kitware GE Corporate R&D Insightful University of North Carolina at Chapel Hill University of Utah University of Pennsylvania and three subcontractors
Harvard Brigham & Women's Hospital University of Pittsburgh Columbia University After its inception the software continued growing with contributions from other institutions including
University of Iowa Georgetown University Stanford University King's College London Creatis INSA
=== Funding === The funding for the project is from the National Library of Medicine at the National Institutes of Health. NLM in turn was supported by member institutions of NIH (see sponsors). The goals for the project include the following:
Support the Visible Human Project. Establish a foundation for future research. Create a repository of fundamental algorithms. Develop a platform for advanced product development. Support commercial application of the technology. Create conventions for future work. Grow a self-sustaining community of software users and developers. The source code of the Insight Toolkit is distributed under an Apache 2.0 License (as approved by the Open Source Initiative) The philosophy of Open Source of the Insight Toolkit was extended to support open science, in particular by providing open access to publications in the domain of Medical Image Processing. These publications are made freely available through the Insight Journal
=== Community participation === Because ITK is an open-source system, anybody can make contributions to the project. A person interested in contributing to ITK can take the following actions
Read the ITK Software Guide. (This book can be purchased from Kitware's store.) Read the instructions on how to contribute classes and algorithms to the Toolkit via submissions to the Insight Journal Obtain access to GitHub. Follow the Git contribution instructions. Join the ITK Discourse discussion. The community is open to everyone. Anyone can submit a patch, and write access to the repository is not necessary to get a patch merged or retain authorship credit. For more information, see the ITK Bar Camp documentation on how to submit a patch.