Skip to main content

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.

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

If you're not sure about the file name format, learn more about wheel file names.

itk_io-5.4.7-cp311-abi3-win_amd64.whl (8.7 MB view details)

Uploaded CPython 3.11+Windows x86-64

itk_io-5.4.7-cp311-abi3-manylinux_2_28_x86_64.whl (28.0 MB view details)

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

itk_io-5.4.7-cp311-abi3-manylinux_2_28_aarch64.whl (25.6 MB view details)

Uploaded CPython 3.11+manylinux: glibc 2.28+ ARM64

itk_io-5.4.7-cp311-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (27.7 MB view details)

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

itk_io-5.4.7-cp311-abi3-macosx_11_0_arm64.whl (17.8 MB view details)

Uploaded CPython 3.11+macOS 11.0+ ARM64

itk_io-5.4.7-cp311-abi3-macosx_10_9_x86_64.whl (22.4 MB view details)

Uploaded CPython 3.11+macOS 10.9+ x86-64

itk_io-5.4.7-cp310-cp310-win_amd64.whl (8.7 MB view details)

Uploaded CPython 3.10Windows x86-64

itk_io-5.4.7-cp310-cp310-manylinux_2_28_x86_64.whl (28.0 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.28+ x86-64

itk_io-5.4.7-cp310-cp310-manylinux_2_28_aarch64.whl (25.6 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.28+ ARM64

itk_io-5.4.7-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (27.7 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.17+ x86-64

itk_io-5.4.7-cp310-cp310-macosx_11_0_arm64.whl (17.8 MB view details)

Uploaded CPython 3.10macOS 11.0+ ARM64

itk_io-5.4.7-cp310-cp310-macosx_10_9_x86_64.whl (22.3 MB view details)

Uploaded CPython 3.10macOS 10.9+ x86-64

itk_io-5.4.7-cp39-cp39-win_amd64.whl (8.7 MB view details)

Uploaded CPython 3.9Windows x86-64

itk_io-5.4.7-cp39-cp39-manylinux_2_28_x86_64.whl (28.0 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.28+ x86-64

itk_io-5.4.7-cp39-cp39-manylinux_2_28_aarch64.whl (25.6 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.28+ ARM64

itk_io-5.4.7-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (27.7 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.17+ x86-64

itk_io-5.4.7-cp39-cp39-macosx_11_0_arm64.whl (17.8 MB view details)

Uploaded CPython 3.9macOS 11.0+ ARM64

itk_io-5.4.7-cp39-cp39-macosx_10_9_x86_64.whl (22.3 MB view details)

Uploaded CPython 3.9macOS 10.9+ x86-64

File details

Details for the file itk_io-5.4.7-cp311-abi3-win_amd64.whl.

File metadata

  • Download URL: itk_io-5.4.7-cp311-abi3-win_amd64.whl
  • Upload date:
  • Size: 8.7 MB
  • Tags: CPython 3.11+, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.3

File hashes

Hashes for itk_io-5.4.7-cp311-abi3-win_amd64.whl
Algorithm Hash digest
SHA256 8c7e6a7842137fd360d80e80d9c26618df9662114d6c98f12b24be9be769da43
MD5 61184927dc9ffca0bdfd1cd3eaad25c6
BLAKE2b-256 0507e42792e040812ec2030b8971f4f06919f6055e651facdeecb9d2fdac6659

See more details on using hashes here.

File details

Details for the file itk_io-5.4.7-cp311-abi3-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for itk_io-5.4.7-cp311-abi3-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 a2af543cc0e2dea6549fca6af0fd08ed84cd92b34c3f25bda5e01b4000ec7d2f
MD5 4b3ec25f43e83c246b754e6b24d96034
BLAKE2b-256 ee3c335d93a3137e1ff1c1468ff760f862a5d43c9778e1441e6d177e4495d8ad

See more details on using hashes here.

File details

Details for the file itk_io-5.4.7-cp311-abi3-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for itk_io-5.4.7-cp311-abi3-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 a1b67764abd71a0dd5b9827ad400db2eae6a9a777a185b51681d61961c5bde2a
MD5 3f9b3b7ddb0c95ad7a7fd4f13d7ebe3b
BLAKE2b-256 e27768b94a420cb6faaceb6d9880fe3001da7ebe60288b306adb914d314a0acb

See more details on using hashes here.

File details

Details for the file itk_io-5.4.7-cp311-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.

File metadata

File hashes

Hashes for itk_io-5.4.7-cp311-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
Algorithm Hash digest
SHA256 b5242e7cf3b7dd4a01478844a5421e637c9b860ad5c7620ef4019398d96efdc0
MD5 469d81d2651cfd4300242d116a162703
BLAKE2b-256 3f57a4fb7ad91765efb8fe76084a0cadacf6846206430f4d9968379a3306f845

See more details on using hashes here.

File details

Details for the file itk_io-5.4.7-cp311-abi3-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for itk_io-5.4.7-cp311-abi3-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 d158bb1cd9746238a11717ec63a05006b5dfd14c4699a0edc2ab42c02c492532
MD5 22811ea3621f2738e7d035fb02bd68c4
BLAKE2b-256 eba910e4bb2d9e9cfb558de75a71e9f634f109de4e078086d8622eda61d9e5cc

See more details on using hashes here.

File details

Details for the file itk_io-5.4.7-cp311-abi3-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for itk_io-5.4.7-cp311-abi3-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 3de7b45085dbd25281a590ebf9c6b1dafbaeff080eceabc8eb0d7fb3c5394876
MD5 e0c7309f949f4c04b99e2204b34560b1
BLAKE2b-256 e2befe6d74ee8c778df437b60e6ca2ef436db46b3356ecb59a4608a33a67b18e

See more details on using hashes here.

File details

Details for the file itk_io-5.4.7-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: itk_io-5.4.7-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 8.7 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.3

File hashes

Hashes for itk_io-5.4.7-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 db4219a73977d499ce03dd148c73a8f2d4cc9010d1430b259ab8c2c60aac821e
MD5 2b86bb489dcebadfa93ac847623488ca
BLAKE2b-256 0de512376622c833a9b1f11705be0257bb2b2c89fcac4cbc8aa0148857a23c3b

See more details on using hashes here.

File details

Details for the file itk_io-5.4.7-cp310-cp310-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for itk_io-5.4.7-cp310-cp310-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 228ca76d5a1b238a0d88a88dae1f0ba147beeb5e4109d3c681b2dc5fd00ae9f7
MD5 cd8fdf34e885835d5c9f488a5a1705fb
BLAKE2b-256 97c539095b0a25761477f228432eec128b1849970c00f49599a5635d1a52c86f

See more details on using hashes here.

File details

Details for the file itk_io-5.4.7-cp310-cp310-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for itk_io-5.4.7-cp310-cp310-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 0f6423bc79ae84ccf93db9c36ad963eac2fc01eb3731a6d333fe7f3931d4f3cd
MD5 fdb0e69c7178c30b78f85dce23bc64dc
BLAKE2b-256 eb3aceb5053bfd7e8f528da928289432e4df24813d6468fd9bdca377a1218ec3

See more details on using hashes here.

File details

Details for the file itk_io-5.4.7-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.

File metadata

File hashes

Hashes for itk_io-5.4.7-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
Algorithm Hash digest
SHA256 6dd6b1b8362fabb517f9a4de1a2fe99b4a92f0dc983beb32836307041a9b2921
MD5 1140036eb8eaed77cd36e1dfa59a9459
BLAKE2b-256 47fa2c53034425887fe69af5fe30234f6ccb976b384d3cc3b1452a0a89c3b11e

See more details on using hashes here.

File details

Details for the file itk_io-5.4.7-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for itk_io-5.4.7-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 c6565c1942fd7cd0e0dce95e6682c0e45a9a75fd0d2bfc3dbba64d5e1f397db8
MD5 3c824b6be7f079c0072ce155788912b0
BLAKE2b-256 5beaac237bcaa93c63e5af19457c9d9be054f1fd2385f20ed074440170744708

See more details on using hashes here.

File details

Details for the file itk_io-5.4.7-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for itk_io-5.4.7-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 74411ac9aed856a2133f2447ee747c38fb8e347e48b4537e2e8b49ad70e4020d
MD5 48179ec346a454c082685d5d1f470144
BLAKE2b-256 bdb1e39eff0bb5e5c23a3de97d24af0c10c65485eb6fab2285030245335a0b15

See more details on using hashes here.

File details

Details for the file itk_io-5.4.7-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: itk_io-5.4.7-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 8.7 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.3

File hashes

Hashes for itk_io-5.4.7-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 1a223e965ef3d37c9ab3eb419406b2618496608b82044196f5e0612665be6b87
MD5 8b34913a22f0820a2c8c865b56e9cad6
BLAKE2b-256 a45e58b85bb491be68937d000999e61e43de196b04d2d4cd653971a42ad47610

See more details on using hashes here.

File details

Details for the file itk_io-5.4.7-cp39-cp39-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for itk_io-5.4.7-cp39-cp39-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 cbc655fbf3428613bf6bfc142f58fba8b52bd8f67c831dbe0f268e4f060ac84b
MD5 61c646a27dc430f022258a43f34a3cde
BLAKE2b-256 40f9cb63d4426cd662e57fd3a82624ea959a1b557c177dc1966e9a34cf9377e2

See more details on using hashes here.

File details

Details for the file itk_io-5.4.7-cp39-cp39-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for itk_io-5.4.7-cp39-cp39-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 f750bb8056152c1b47bad643269f4c877182d2fbcac85441f4c9db523c61f2d5
MD5 a4b7f7425ddb905881d810e44b70fcb5
BLAKE2b-256 1204628d7906a022c1251ed064ccb26088e5f1ded3d9b92834ddf7db3e3988a3

See more details on using hashes here.

File details

Details for the file itk_io-5.4.7-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.

File metadata

File hashes

Hashes for itk_io-5.4.7-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
Algorithm Hash digest
SHA256 b358cadd8fa6283223535f23fb362f4fec8142119dd04dcbae5d85b6f9cab0bd
MD5 835ee087f5a6b428c0bde5e51395f410
BLAKE2b-256 11b0b54b62eeb42eea1e0589622cb3afaa0f55c785371890f750e3271a900a1f

See more details on using hashes here.

File details

Details for the file itk_io-5.4.7-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for itk_io-5.4.7-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 0c9562c06b8be544611173fa5f9ec7798dcf33a55d93b540649f4197ea1cb170
MD5 4ae1ff79b9c1b32bba358606a39cf9b8
BLAKE2b-256 dfb8073853eabbe171f8d633ce91c2dbd31d1c0323899fdb5c325be3e2da6251

See more details on using hashes here.

File details

Details for the file itk_io-5.4.7-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for itk_io-5.4.7-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 fe73b849087db7afe4c42030e1364fed0cd478f52b4d16229c1d9a6af0cebd31
MD5 878ed6c3186d10322bf6ad99ba8e8d25
BLAKE2b-256 063e38de870a870bd442a29d21be2f7ac67d655f78fe0762a04700b2b1c05530

See more details on using hashes here.

Supported by

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