ITK is an open-source toolkit for multidimensional image analysis

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for jcfr from gravatar.com jcfr Avatar for phcerdan from gravatar.com phcerdan Avatar for tbirdso from gravatar.com tbirdso Avatar for thewtex from gravatar.com thewtex

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: Apache Software License (Apache)
  • Author: Insight Software Consortium
  • Tags ITK, InsightToolkit, segmentation, registration, image, imaging
Classifiers

Project description

itk-segmentation

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.

This package addresses the segmentation problem: partition the image into classified regions (labels). This is a high level package that makes use of many lower level packages.

ITK - The Insight Toolkit

ITK: The Insight Toolkit

GitHub release PyPI Wheels License DOI Powered by NumFOCUS

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

Links

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

DOI

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

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for jcfr from gravatar.com jcfr Avatar for phcerdan from gravatar.com phcerdan Avatar for tbirdso from gravatar.com tbirdso Avatar for thewtex from gravatar.com thewtex

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: Apache Software License (Apache)
  • Author: Insight Software Consortium
  • Tags ITK, InsightToolkit, segmentation, registration, image, imaging
Classifiers

Release history Release notifications | RSS feed

5.4.0

5.4rc4 pre-release

5.4rc3 pre-release

5.4rc2 pre-release

5.4rc1 pre-release

5.3.0

5.3rc4.post4 pre-release

5.3rc4.post3 pre-release

5.3rc4.post2 pre-release

5.3rc4.post1 pre-release

5.3rc4 pre-release

5.3rc3 pre-release

5.3rc2.post1 pre-release

5.3rc2 pre-release

5.3rc1 pre-release

5.2.1.post1

5.2.1

5.2.0.post3

This version

5.2.0.post2

5.2.0.post1

5.2.0

5.2rc3 pre-release

5.2rc2 pre-release

5.2rc1 pre-release

5.1.2

5.1.1.post1

5.1.1

5.1.0.post3

5.1.0.post2

5.1.0.post1

5.1.0

5.1rc3 pre-release

5.1rc2 pre-release

5.1rc1.post1 pre-release

5.1rc1 pre-release

5.1b1 pre-release

5.0.1

5.0.0.post1

5.0.0

5.0rc2 pre-release

5.0rc1 pre-release

5.0b3 pre-release

5.0b1 pre-release

5.0a2 pre-release

5.0a1 pre-release

4.13.2.post1

4.13.2

4.13.1.post1

4.13.0

4.12.0.post1

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-5.2.0.post2-cp39-cp39-win_amd64.whl (5.2 MB view details)

Uploaded CPython 3.9 Windows x86-64

itk_segmentation-5.2.0.post2-cp39-cp39-manylinux2014_x86_64.whl (16.6 MB view details)

Uploaded CPython 3.9

itk_segmentation-5.2.0.post2-cp39-cp39-manylinux2014_aarch64.whl (15.3 MB view details)

Uploaded CPython 3.9

itk_segmentation-5.2.0.post2-cp39-cp39-macosx_11_0_arm64.whl (12.4 MB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

itk_segmentation-5.2.0.post2-cp39-cp39-macosx_10_9_x86_64.whl (16.1 MB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

itk_segmentation-5.2.0.post2-cp38-cp38-win_amd64.whl (5.2 MB view details)

Uploaded CPython 3.8 Windows x86-64

itk_segmentation-5.2.0.post2-cp38-cp38-manylinux2014_x86_64.whl (16.6 MB view details)

Uploaded CPython 3.8

itk_segmentation-5.2.0.post2-cp38-cp38-manylinux2014_aarch64.whl (15.3 MB view details)

Uploaded CPython 3.8

itk_segmentation-5.2.0.post2-cp38-cp38-macosx_10_9_x86_64.whl (16.1 MB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

itk_segmentation-5.2.0.post2-cp37-cp37m-win_amd64.whl (5.1 MB view details)

Uploaded CPython 3.7m Windows x86-64

itk_segmentation-5.2.0.post2-cp37-cp37m-manylinux2014_x86_64.whl (16.6 MB view details)

Uploaded CPython 3.7m

itk_segmentation-5.2.0.post2-cp37-cp37m-manylinux2014_aarch64.whl (15.3 MB view details)

Uploaded CPython 3.7m

itk_segmentation-5.2.0.post2-cp37-cp37m-macosx_10_9_x86_64.whl (16.1 MB view details)

Uploaded CPython 3.7m macOS 10.9+ x86-64

itk_segmentation-5.2.0.post2-cp36-cp36m-win_amd64.whl (5.1 MB view details)

Uploaded CPython 3.6m Windows x86-64

itk_segmentation-5.2.0.post2-cp36-cp36m-manylinux2014_x86_64.whl (16.6 MB view details)

Uploaded CPython 3.6m

itk_segmentation-5.2.0.post2-cp36-cp36m-manylinux2014_aarch64.whl (15.3 MB view details)

Uploaded CPython 3.6m

itk_segmentation-5.2.0.post2-cp36-cp36m-macosx_10_9_x86_64.whl (16.1 MB view details)

Uploaded CPython 3.6m macOS 10.9+ x86-64

File details

Details for the file itk_segmentation-5.2.0.post2-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: itk_segmentation-5.2.0.post2-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 5.2 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.2 requests-toolbelt/0.9.1 tqdm/4.40.1 CPython/3.7.3

File hashes

Hashes for itk_segmentation-5.2.0.post2-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 bd19315d42f697fa4b695461c85a411e0c366d37c85162c507b12fe23e8978c2
MD5 2182aa9a7c3ec85f9fd7815680d74153
BLAKE2b-256 789efd0dcbff32a8a6031d17f5666ec656b5868bec32ca7ff4b7fa56d8486d4c

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.0.post2-cp39-cp39-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.2.0.post2-cp39-cp39-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 37a86a170e8ceadc36dd8eeba01e6b163f08e7f872af571c2fd16c97cd5d59c9
MD5 51c0266f447ef5b6722b949fcd31fe21
BLAKE2b-256 69154950628ef31c0b261d08e1d6fd05bce5edbc12548e38ae1d3bf2e75c7b4c

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.0.post2-cp39-cp39-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.2.0.post2-cp39-cp39-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 1ac03f008ff16046398bb91b333e41105c355c4ad154cadc975d259cbeddc7ba
MD5 db1d6c64b1e3192808cf58c717c81132
BLAKE2b-256 2cb8c74224985b3e34a5955928ea7a403e63f65461feca14e5e432517c2b3c07

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.0.post2-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

  • Download URL: itk_segmentation-5.2.0.post2-cp39-cp39-macosx_11_0_arm64.whl
  • Upload date:
  • Size: 12.4 MB
  • Tags: CPython 3.9, macOS 11.0+ ARM64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.2 requests-toolbelt/0.9.1 tqdm/4.40.1 CPython/3.7.3

File hashes

Hashes for itk_segmentation-5.2.0.post2-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 63ecb17ad766f4d9060ed6d979b42364607bdc0442bd09a9ed126d8ee4992daa
MD5 3dd5502206aac7d5a7868174c91e2b4d
BLAKE2b-256 011ef6494d932b4fe260919dab2f282f3be2d96abb407b34f39d1fc0554d1ca1

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.0.post2-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: itk_segmentation-5.2.0.post2-cp39-cp39-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 16.1 MB
  • Tags: CPython 3.9, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.2 requests-toolbelt/0.9.1 tqdm/4.40.1 CPython/3.7.3

File hashes

Hashes for itk_segmentation-5.2.0.post2-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 daa5c3d0e5ed42f9b51896ffdbe90245ac24d405e6a6bd2ced565072f1225efa
MD5 c69a0ab67f1ed2481e52f29f2b2c6d42
BLAKE2b-256 8d351d208294899e395c42da4a8227e07dabf4d9481716ffa44fbd8f0d07d8fb

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.0.post2-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: itk_segmentation-5.2.0.post2-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 5.2 MB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.2 requests-toolbelt/0.9.1 tqdm/4.40.1 CPython/3.7.3

File hashes

Hashes for itk_segmentation-5.2.0.post2-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 980715298a2bd67d7e29c6db6cae356d77b6626b871b1c4675dd3f2b2f7b516c
MD5 88d0858f189e7f71f28a1d5a892d2321
BLAKE2b-256 5277a1269391872f31deb9b85102668869db00f7542e8f17685041c1744ae00a

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.0.post2-cp38-cp38-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.2.0.post2-cp38-cp38-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 c8fe6b64ad71f341a08147e7ceeac479d767e244a9904eef73f84202ec64b52d
MD5 cb0b2ec195380c42ffcab61e62a15bed
BLAKE2b-256 73fdc0c5849b56bfe35153e4e1c53743fdfcd139b26193ed28cb512f27eeb816

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.0.post2-cp38-cp38-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.2.0.post2-cp38-cp38-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 322f91377a9daba31beb8586ebebb3409e0610c2e2fd8d135f21e4b0f584636b
MD5 f49ac9d3d5c0a9e94fe3c2ae2994c8bb
BLAKE2b-256 1bdef815b9d3c006eb971528e16ba9bd251a39916b890bf048eabf34eee505b8

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.0.post2-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: itk_segmentation-5.2.0.post2-cp38-cp38-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 16.1 MB
  • Tags: CPython 3.8, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.2 requests-toolbelt/0.9.1 tqdm/4.40.1 CPython/3.7.3

File hashes

Hashes for itk_segmentation-5.2.0.post2-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 0bd3f5d2f250bf6beb1c9aef94c93c9faf12c17c8a84d36ac75311762785a46d
MD5 fb4f8a64ce29b74f41aee63697fbb14d
BLAKE2b-256 2e8134d95608c7928c1988771f05b8f1d1937f3c23c9d4a4e7a5f84bab6a3669

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.0.post2-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: itk_segmentation-5.2.0.post2-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 5.1 MB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.2 requests-toolbelt/0.9.1 tqdm/4.40.1 CPython/3.7.3

File hashes

Hashes for itk_segmentation-5.2.0.post2-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 274b770460a3c94b9741b2da1bc58050721a3af701a3b9a917a876f88717d814
MD5 88e9b4b6a4e69a2c8ad2dd66f710712c
BLAKE2b-256 5924d60a383d5aaaf0840b3155c487f13b8027f71d0592ce97ec0b8d61c607df

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.0.post2-cp37-cp37m-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.2.0.post2-cp37-cp37m-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 903daf0c3efb7b9acc6bf48839ed7c5874e4c7bff63c6d8887ac04ae9b0ed558
MD5 fcac28ca67af0c79a9519291a7aa1ffb
BLAKE2b-256 cfb006645d30065492e013dcaacd4b7f3a63f9621bd7ac4b6cb811c5a6dfc590

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.0.post2-cp37-cp37m-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.2.0.post2-cp37-cp37m-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 33eb6effc9d56dfecbf8c5a49118ee02764484ffe9444e07932a4af2ab2d4e24
MD5 230e6fa911a435b7a8494dacbbe34f52
BLAKE2b-256 39eafc0f4488af26fcd72d58d2d3cb56d1958cf2640e286dc69f2d2401610e81

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.0.post2-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: itk_segmentation-5.2.0.post2-cp37-cp37m-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 16.1 MB
  • Tags: CPython 3.7m, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.2 requests-toolbelt/0.9.1 tqdm/4.40.1 CPython/3.7.3

File hashes

Hashes for itk_segmentation-5.2.0.post2-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 28a2486ac893b0dee661372b7d750bb3fe796cc8919d7084b3f5b1bf3f1b9cbd
MD5 64f00a9b580952e36f0dfa42b63d509b
BLAKE2b-256 c3aa60c6b7f61af8fc2bab71f0ca67af480ffff12bf4951a70dadf6840a56d82

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.0.post2-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: itk_segmentation-5.2.0.post2-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 5.1 MB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.2 requests-toolbelt/0.9.1 tqdm/4.40.1 CPython/3.7.3

File hashes

Hashes for itk_segmentation-5.2.0.post2-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 3e12afd037a2f6e8d774b0b68222caec2fdc12a1b35e1a2c452c8ef95e42864f
MD5 a231dfca98333f1e24e8f94a2d19fe07
BLAKE2b-256 41f967d9aa27644e2a73380b4a1caa193d8328f330845fe6cb0b92bd41ff0265

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.0.post2-cp36-cp36m-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.2.0.post2-cp36-cp36m-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 9ecc0434b229b0d8bf3f74f95216c2ff41df58d510e7c5bfcba294216061f1dc
MD5 46f4a598754a84fe66c8355bfbbfaef7
BLAKE2b-256 066f166b552869f704f7921d71815250c676d81e074d362a9af76920f3bdd56b

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.0.post2-cp36-cp36m-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.2.0.post2-cp36-cp36m-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 25e19fdce2f8a91d099bacd69099545f02c966ec8f4b66074292b4712694bb32
MD5 add0e5903b7735f697d9dd868d51a09b
BLAKE2b-256 2bef18e9ab6adafd1a78ce84dc2121a4a9c311211cfe0f8f7faf7a92413a3682

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.0.post2-cp36-cp36m-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: itk_segmentation-5.2.0.post2-cp36-cp36m-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 16.1 MB
  • Tags: CPython 3.6m, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.2 requests-toolbelt/0.9.1 tqdm/4.40.1 CPython/3.7.3

File hashes

Hashes for itk_segmentation-5.2.0.post2-cp36-cp36m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 7cc796d931bfba605f6fd758b826db65b80a242465fc4d2bf452a7572e5c5931
MD5 c513e3299a361102fc24c448d13d6bde
BLAKE2b-256 f9150b748ce3a6a86933906b9776476ec61c7b9cb3879507a5c0830692f11552

See more details on using hashes here.

Supported by

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