Skip to main content

ITK is an open-source toolkit for multidimensional image analysis

Project description

ITK - The Insight Toolkit

ITK: The Insight Toolkit

GitHub release PyPI Wheels License DOI Powered by NumFOCUS

C++ Python
Linux Build Status Build Status
Windows Build Status Build Status
macOS Build Status Build Status
macOS (Apple Silicon) ITK.macOS.Arm64
Linux (Code coverage) Build Status

Links

Note: For questions related to ITK, please use the official Discussion space: the issue tracker is reserved to track different aspects of the software development process, as highlighted by the available templates.

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.

Professional Services

Kitware provides professional services for ITK, including custom solution creation, collaborative research and development, development support, and training.

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

DOI

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

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

itk_segmentation-5.4.4.post1-cp311-abi3-win_amd64.whl (5.0 MB view details)

Uploaded CPython 3.11+Windows x86-64

itk_segmentation-5.4.4.post1-cp311-abi3-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (15.9 MB view details)

Uploaded CPython 3.11+manylinux: glibc 2.27+ x86-64manylinux: glibc 2.28+ x86-64

itk_segmentation-5.4.4.post1-cp311-abi3-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl (14.7 MB view details)

Uploaded CPython 3.11+manylinux: glibc 2.27+ ARM64manylinux: glibc 2.28+ ARM64

itk_segmentation-5.4.4.post1-cp311-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (16.5 MB view details)

Uploaded CPython 3.11+manylinux: glibc 2.17+ x86-64

itk_segmentation-5.4.4.post1-cp311-abi3-macosx_11_0_arm64.whl (11.7 MB view details)

Uploaded CPython 3.11+macOS 11.0+ ARM64

itk_segmentation-5.4.4.post1-cp311-abi3-macosx_10_9_x86_64.whl (14.6 MB view details)

Uploaded CPython 3.11+macOS 10.9+ x86-64

itk_segmentation-5.4.4.post1-cp310-cp310-win_amd64.whl (4.9 MB view details)

Uploaded CPython 3.10Windows x86-64

itk_segmentation-5.4.4.post1-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (15.8 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.27+ x86-64manylinux: glibc 2.28+ x86-64

itk_segmentation-5.4.4.post1-cp310-cp310-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl (14.6 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.27+ ARM64manylinux: glibc 2.28+ ARM64

itk_segmentation-5.4.4.post1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (16.3 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.17+ x86-64

itk_segmentation-5.4.4.post1-cp310-cp310-macosx_11_0_arm64.whl (11.4 MB view details)

Uploaded CPython 3.10macOS 11.0+ ARM64

itk_segmentation-5.4.4.post1-cp310-cp310-macosx_10_9_x86_64.whl (14.1 MB view details)

Uploaded CPython 3.10macOS 10.9+ x86-64

itk_segmentation-5.4.4.post1-cp39-cp39-win_amd64.whl (4.9 MB view details)

Uploaded CPython 3.9Windows x86-64

itk_segmentation-5.4.4.post1-cp39-cp39-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (15.8 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.27+ x86-64manylinux: glibc 2.28+ x86-64

itk_segmentation-5.4.4.post1-cp39-cp39-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl (14.6 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.27+ ARM64manylinux: glibc 2.28+ ARM64

itk_segmentation-5.4.4.post1-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (16.3 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.17+ x86-64

itk_segmentation-5.4.4.post1-cp39-cp39-macosx_11_0_arm64.whl (11.4 MB view details)

Uploaded CPython 3.9macOS 11.0+ ARM64

itk_segmentation-5.4.4.post1-cp39-cp39-macosx_10_9_x86_64.whl (14.1 MB view details)

Uploaded CPython 3.9macOS 10.9+ x86-64

File details

Details for the file itk_segmentation-5.4.4.post1-cp311-abi3-win_amd64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.4.4.post1-cp311-abi3-win_amd64.whl
Algorithm Hash digest
SHA256 5e0751ca0a8deb168ccdb38200251f332add73bedc7dac9c2634e4a1f94ddf70
MD5 b555a509b995086600831402d09da48f
BLAKE2b-256 321d0df3d3736683caf75ce18c7d29d71db27bcf562c928e518a10b46d8db7c3

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.4.4.post1-cp311-abi3-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.4.4.post1-cp311-abi3-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 047cd183fe2a2075bc47ffc3f4c425fe2577e79aa1e76e695c7cfc1620aa50f7
MD5 e9236e2b522f2e6eb61ebafba80f2273
BLAKE2b-256 16fe5e35e6709b705ebb3b767e1a4a975189fc96e1bb1be85c48d29eb4f01a81

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.4.4.post1-cp311-abi3-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.4.4.post1-cp311-abi3-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 4336c21aa35790f218e8bdd4e4c8438d16e2a62a0f9bd0ee76982545aab522b0
MD5 1786bb40e05b2435368ea12bb88399a2
BLAKE2b-256 dfb6bc25a73f843e53b76580b70c490c45c75006f614b73cc24737417b823b4f

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.4.4.post1-cp311-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.4.4.post1-cp311-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
Algorithm Hash digest
SHA256 4d041206b54ad09844ae78a46f1828c7f5670eb3922052b0a663adfe112819fd
MD5 b30588c3aadcef65d8d7be35a847270f
BLAKE2b-256 691ef86e35649bb9932afe6d4d383608c7088b65faba62502f8e2b1b6a910179

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.4.4.post1-cp311-abi3-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.4.4.post1-cp311-abi3-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 d3dec87fe07b4d2c73c036d275257097732e3120a2e882ba141c6300ee7cd0bf
MD5 dbeef27180b8295859b1e891cacc0a64
BLAKE2b-256 5591814d45b673b4ac37c049eb5044a3d9714bbcd5e2c1716ace9531e404ffca

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.4.4.post1-cp311-abi3-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.4.4.post1-cp311-abi3-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 9420152de925df69702e2bfe91b20a9ac4a1e4ee14c444c27c9c36546975a8ce
MD5 752a6e2a8eba403019b3b627243d441e
BLAKE2b-256 ba44124ab9dc4914307338357bf036337b689d18c605981c3252567aa6f4dd35

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.4.4.post1-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.4.4.post1-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 758bc51821947102684f74fcdd8996f8465b5aa95bea74b4439acbc1b4ae3637
MD5 c5d9a13ec536a3cb0d1bbd44faf3b1f5
BLAKE2b-256 5c1cf0b431d0614059437b42e2832acf5957f62682e135a1720f3a03e8d5c171

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.4.4.post1-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.4.4.post1-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 1cd83273c16ad0d05f280ae742dbcd5d1ec3c365a5514dd462bd2701744dd7dc
MD5 75e1b1362e46749d9e8acc4006703f84
BLAKE2b-256 bfb2cbb4aeddebdea47d8200dc66c8832f59f5cf059bce99df89089976cd29fb

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.4.4.post1-cp310-cp310-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.4.4.post1-cp310-cp310-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 aa12c56512878bf46d1e2f851f03d866ad5a431177d45f58e5f6218c62997324
MD5 eebb17ec5d78a435ffca8795e23e8923
BLAKE2b-256 d99e45cc84b0ebacb7306dbd6e160260a5144fb9403fc9d8066ef7b4d08b0457

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.4.4.post1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.4.4.post1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
Algorithm Hash digest
SHA256 78227290d6def18c093e20f7533a1382f8d4e08877282a0a3dfcfd2aede83162
MD5 cdee5bd5ff5d7781497a253f97518007
BLAKE2b-256 3ca39cb0dd470b929febed566333c9694d07b1fb4157666b235a681bcb118f20

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.4.4.post1-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.4.4.post1-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 587e81cea4a2c5825de4f83833ceec5a36e229ad5ef79fa63e90d3b26e0b9550
MD5 f4376b6f93a924fdec615164a41b24d2
BLAKE2b-256 a3e2b2c71c4a788743927bb05bf64eacf03536250978f3d94b2945cd8e2b7932

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.4.4.post1-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.4.4.post1-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 34b5f56017906508c63194898c5edce4788a671ecad96697de5e681bc3f1859c
MD5 615c12abf08c9bb17402a33819804013
BLAKE2b-256 100a3bbc914e83e28ecd1ed98b4de26cacd1a94d760f3ddf24788e22474fd1e9

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.4.4.post1-cp39-cp39-win_amd64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.4.4.post1-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 2473cf4c92f8c8aa374d550e7debc968c450f8fad3895c67a175b6d96337a27d
MD5 81348fe6255e18f64876d3293d5dd9f1
BLAKE2b-256 2d4a217309afbb77862317dbf1ce7ff0e7950dd540c4aae836b690206e76ef6b

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.4.4.post1-cp39-cp39-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.4.4.post1-cp39-cp39-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 2dafab4902ccb8fd79803fb0662e0ba2ba4f1688d50df274e1ae5abf5f3e9422
MD5 a5d5390c160e2f73956ac1e52234ae48
BLAKE2b-256 7254531464185c92fbd68a0fda6fdf634f1b029117ea13d91ae2bf30fa9cb825

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.4.4.post1-cp39-cp39-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.4.4.post1-cp39-cp39-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 7fc0553aef15eefd8b774ef1f2f33fe0f661fca11c6ef2764a117768b0e6281d
MD5 2e74f9a20014fd27bab719b6dbcec501
BLAKE2b-256 8b8e785273d6c01986f6abf901b1db376ed24c91a99a8785a45b650d6edca481

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.4.4.post1-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.4.4.post1-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
Algorithm Hash digest
SHA256 a46a3504b9558021c07bd2ea111805c97d3b93bb4d55c040181310ada82cb02c
MD5 ae04188a15eedcc0a4719e07ca2da178
BLAKE2b-256 99cacc89e2bf76b1ac00c61f32e14a8b4a332d03f98155304bb0fb0fdcba2bc5

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.4.4.post1-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.4.4.post1-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 12eb2240aeb9ebab657f21b39e8c63fe659994ed1409cb9793ac688afcee6b6f
MD5 deae96a79a351d1b859f3a9cfcecab52
BLAKE2b-256 654a1bd7d2b942e942095d675ba2c0c06f2ecb9177bdd8c0345faf439d00d961

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.4.4.post1-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.4.4.post1-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 32700d0816b0ccb8c399eed03396ed9682357ed21df2bd41dc4f8b52918b2d7e
MD5 d88dcd858524b65c3ab9580335465f32
BLAKE2b-256 1eefd7d128f1cb5007a9900038ea3902e5292ca55218d55230f26d244634310e

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page