itk-filtering 5.2.1.post1

ITK is an open-source toolkit for multidimensional image analysis

itk-filtering

ITK is an open-source, cross-platform library that provides developers with an extensive suite of software tools for image analysis. Developed through extreme programming methodologies, ITK employs leading-edge algorithms for registering and segmenting multidimensional scientific images.

These packages contains filters that modify data in the ITK pipeline framework. These filters take an input object, such as an Image, and modify it to create an output. Filters can be chained together to create a processing pipeline.

ITK: The Insight Toolkit

	C++	Python
Linux
macOS
Windows
Linux (Code coverage)

Links

• Homepage
• Download
• Discussion
• Software Guide
• Help
• Examples
• Issue tracking
• Submit a patch

About

The Insight Toolkit (ITK) is an open-source, cross-platform toolkit for N-dimensional scientific image processing, segmentation, and registration. 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.

The ITK project uses an open governance model and is fiscally sponsored by NumFOCUS. Consider making a tax-deductible donation to help the project pay for developer time, professional services, travel, workshops, and a variety of other needs.

ITK is distributed in binary Python packages. To install:

pip install itk

or

conda install -c conda-forge itk

The cross-platform, C++ core of the toolkit may be built from source using CMake.

Copyright

NumFOCUS holds the copyright of this software. NumFOCUS is a non-profit entity that promotes the use of open source scientific software for educational and research purposes. NumFOCUS delegates project governance to the Insight Software Consortium Council, an educational consortium dedicated to promoting and maintaining open-source, freely available software for medical image analysis. This includes promoting such software in teaching, research, and commercial applications, and maintaining webpages and user and developer communities. ITK is distributed under a license that enables use for both non-commercial and commercial applications. See LICENSE and NOTICE files for details.

Supporting ITK

ITK is a fiscally sponsored project of NumFOCUS, a non-profit dedicated to supporting the open source scientific computing community. If you want to support ITK's mission to develop and maintain open-source, reproducible scientific image analysis software for education and research, please consider making a donation to support our efforts.

NumFOCUS is 501(c)(3) non-profit charity in the United States; as such, donations to NumFOCUS are tax-deductible as allowed by law. As with any donation, you should consult with your personal tax adviser or the IRS about your particular tax situation.

Citation

To cite ITK, please reference, as appropriate:

The papers

McCormick M, Liu X, Jomier J, Marion C, Ibanez L. ITK: enabling reproducible research and open science. Front Neuroinform. 2014;8:13. Published 2014 Feb 20. doi:10.3389/fninf.2014.00013

Yoo TS, Ackerman MJ, Lorensen WE, Schroeder W, Chalana V, Aylward S, Metaxas D, Whitaker R. Engineering and Algorithm Design for an Image Processing API: A Technical Report on ITK – The Insight Toolkit. In Proc. of Medicine Meets Virtual Reality, J. Westwood, ed., IOS Press Amsterdam pp 586-592 (2002).

The books

Johnson, McCormick, Ibanez. "The ITK Software Guide: Design and Functionality." Fourth Edition. Published by Kitware, Inc. 2015 ISBN: 9781-930934-28-3.

Johnson, McCormick, Ibanez. "The ITK Software Guide: Introduction and Development Guidelines." Fourth Edition. Published by Kitware, Inc. 2015 ISBN: 9781-930934-27-6.

Specific software version

Once your work has been published, please create a pull request to add the publication to the ITKBibliography.bib file.