Chapter 1

Welcome to the Insight Segmentation and Registration Toolkit (ITK) Software Guide. This book has been updated for ITK 5.0.0 and later versions of the Insight Toolkit software.

ITK is an open-source, object-oriented software system for image processing, segmentation, and registration. Although it is large and complex, ITK is designed to be easy to use once you learn about its basic object-oriented and implementation methodology. The purpose of this Software Guide is to help you learn just this, plus to familiarize you with the important algorithms and data representations found throughout the toolkit.

ITK is a large system. As a result, it is not possible to completely document all ITK objects and their methods in this text. Instead, this guide will introduce you to important system concepts and lead you up the learning curve as fast and efficiently as possible. Once you master the basics, take advantage of the many resources available 1 , including example materials, which provide cookbook recipes that concisely demonstrate how to achieve a given task, the Doxygen pages, which document the specific algorithm parameters, and the knowledge of the many ITK community members (see Section 1.4 on page 12.)

The Insight Toolkit is an open-source software system. This means that the community surrounding ITK has a great impact on the evolution of the software. The community can make significant contributions to ITK by providing code reviews, bug patches, feature patches, new classes, documentation, and discussions. Please feel free to contribute your ideas through the ITK community discussion.

The Insight Toolkit is built on the principle that patents are undesirable in an open-source software. Thus, the community strives to keep the Insight Toolkit free from any patented code, algorithm or method.

1.1 Organization

This software guide is divided into three parts. Part I is a general introduction to ITK, with a description of how to install the Insight Toolkit on your computer. This includes how to build the library from its source code. Part II introduces basic system concepts such as an overview of the system architecture, and how to build applications in the C++ and Python programming languages. Part II also describes the design of data structures and application of analysis methods within the system. Part III is for the ITK contributor and explains how to create your own classes, extend the system, and be an active participant in the project.

1.2 How to Learn ITK

The key to learning how to use ITK is to become familiar with its palette of objects and the ways to combine them. There are three categories of documentation to help with the learning process: high level guidance material (the Software Guide), ”cookbook” demonstrations on how to achieve concrete objectives (the examples), and detailed descriptions of the application programming interface (the Doxygen2 documentation). These resources are combined in the three recommended stages for learning ITK.

In the first stage, thoroughly read this introduction, which provides an overview of some of the key concepts of the system. It also provides guidance on how to build and install the software. After running your first ”hello world” program, you are well on your way to advanced computational image analysis!

The next stage is to execute a few examples and gain familiarity with the available documentation. By running the examples, one can gain confidence in achieving results and is introduced the mechanics of the software system. There are three example resources,

  1. the Examples directory of the ITK source code repository 3.
  2. the Examples pages on the ITK Wiki 4
  3. the Sphinx documented ITK Examples 5

To gain familiarity with the available documentation, browse the sections available in Part II and Part III of this guide. Also, browse the Doxygen application programming interface (API) documentation for the classes applied in the examples.

Finally, mastery of ITK involves integration of information from multiple sources. the second companion book is a reference to algorithms available, and Part III introduces how to extend them to your needs and participate in the community. Individual examples are a detailed starting point to achieve certain tasks. In practice, the Doxygen documentation becomes a frequent reference as an index of the classes available, their descriptions, and the syntax and descriptions of their methods. When examples and Doxygen documentation are insufficient, the software unit tests thoroughly demonstrate how the code is utilized. Last, but not least, the source code itself is an extremely valuable resource. The code is the most detailed, up-to-date, and definitive description of the software. A great deal of attention and effort is directed to the code’s readability, and its value cannot be understated.

The following sections describe how to obtain the software, summarize the software functionality in each directory, and how to locate data.

1.3 Software Organization

To begin your ITK odyssey, you will first need to know something about ITK’s software organization and directory structure. It is helpful to know enough to navigate through the code base to find examples, code, and documentation.

ITK resources are organized into multiple Git repositories. The ITK library source code are in the ITK6 Git repository. The Sphinx Examples are in the ITKExamples7 repository. The sources for this guide are in the ITKSoftwareGuide8 repository.

The ITK repository contains the following subdirectories:

The source code directory structure—found in ITK/Modules—is the most important to understand.

The Doxygen documentation is an essential resource when working with ITK, but it is not contained in a separate repository. Each ITK class is implemented with a .h and .cxx/.hxx file (.hxx file for templated classes). All methods found in the .h header files are documented and provide a quick way to find documentation for a particular method. Doxygen uses this header documentation to produce its HTML output.

The extensive Doxygen web pages describe in detail every class and method in the system. It also contains inheritance and collaboration diagrams, listing of event invocations, and data members. heavily hyper-linked to other classes and to the source code. The nightly generated Doxygen documentation is online at Archived versions for each feature release are also available online; for example, the documentation for the 4.4.0 release are available at

1.4 The Insight Community and Support

Joining the community discussion is strongly recommended. This is one of the primary resources for guidance and help regarding the use of the toolkit. You can subscribe to the community list online at

ITK transitioned to Discourse on September 2017. Discourse is a next generation, open source discussion platform that functions as a mailing list, discussion forum, and long-form chat room. Discourse is a simple, modern, and fun platform that facilitates civilized discussions.

ITK maintainers developed a Getting Started Guide to help people joining the discussion, subscribing to updates, or setting their preferences.

The previous mailing list resources can be reached at

ITK was created from its inception as a collaborative, community effort. Research, teaching, and commercial uses of the toolkit are expected. If you would like to participate in the community, there are a number of possibilities. For details on participation, see Part III of this book.

1.5 A Brief History of ITK

In 1999 the US National Library of Medicine of the National Institutes of Health awarded six three-year contracts to develop an open-source registration and segmentation toolkit, that eventually came to be known as the Insight Toolkit (ITK) and formed the basis of the Insight Software Consortium. ITK’s NIH/NLM Project Manager was Dr. Terry Yoo, who coordinated the six prime contractors composing the Insight consortium. These consortium members included three commercial partners—GE Corporate R&D, Kitware, Inc., and MathSoft (the company name is now Insightful)—and three academic partners—University of North Carolina (UNC), University of Tennessee (UT) (Ross Whitaker subsequently moved to University of Utah), 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 Ibáñez at UNC (Luis is now at Google), Ross Whitaker with Josh Cates at UT (both now at Utah), and Dimitri Metaxas at UPenn (now at Rutgers). 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 Stetten at the University of Pittsburgh.

In 2002 the first official public release of ITK was made available. In addition, the National Library of Medicine awarded thirteen contracts to several organizations to extend ITK’s capabilities. The NLM has funded maintenance of the toolkit over the years, and a major funding effort was started in July 2010 that culminated with the release of ITK 4.0.0 in December 2011. If you are interested in potential funding opportunities, we suggest that you contact Dr. Terry Yoo at the National Library of Medicine for more information.