Skip to main content

ITK is an open-source toolkit for multidimensional image analysis

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


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-5.2.1.post1-cp39-cp39-win_amd64.whl (5.2 MB view details)

Uploaded CPython 3.9 Windows x86-64

itk_segmentation-5.2.1.post1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (16.6 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

itk_segmentation-5.2.1.post1-cp39-cp39-macosx_11_0_arm64.whl (12.3 MB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

itk_segmentation-5.2.1.post1-cp39-cp39-macosx_10_9_x86_64.whl (16.1 MB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

itk_segmentation-5.2.1.post1-cp38-cp38-win_amd64.whl (5.2 MB view details)

Uploaded CPython 3.8 Windows x86-64

itk_segmentation-5.2.1.post1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (16.6 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

itk_segmentation-5.2.1.post1-cp38-cp38-macosx_10_9_x86_64.whl (16.1 MB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

itk_segmentation-5.2.1.post1-cp37-cp37m-win_amd64.whl (5.1 MB view details)

Uploaded CPython 3.7m Windows x86-64

itk_segmentation-5.2.1.post1-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (16.6 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ x86-64

itk_segmentation-5.2.1.post1-cp37-cp37m-macosx_10_9_x86_64.whl (16.1 MB view details)

Uploaded CPython 3.7m macOS 10.9+ x86-64

itk_segmentation-5.2.1.post1-cp36-cp36m-win_amd64.whl (5.1 MB view details)

Uploaded CPython 3.6m Windows x86-64

itk_segmentation-5.2.1.post1-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (16.6 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ x86-64

itk_segmentation-5.2.1.post1-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-5.2.1.post1-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: itk_segmentation-5.2.1.post1-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-5.2.1.post1-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 136b995ee4f65096792c8be41c696d1dd384364f89cc84a0d8fb003f12ab6b9e
MD5 98dc372d687f4338bbb6d021a0d65b4b
BLAKE2b-256 92fcf1fdd828bd4cb82e854a074f1833524bfc23d153d994a11de6cc5502109e

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.1.post1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.2.1.post1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 a2e7d4953bd4e2b2d36539944c8bef33e50266398249e8af3c4a5b31a291f72b
MD5 67be9210d7912ed88454aa4b573fc10d
BLAKE2b-256 4ca15940c53af27147643df4f20e8cd5e0e3856caa7ec6953b4022029dcec582

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.1.post1-cp39-cp39-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.2.1.post1-cp39-cp39-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 79536634927dddf2e7589543ad89ff46761886339ad3c2f201f686f752a7db69
MD5 074ff6a6d08582d423a7a21b65a2aaa5
BLAKE2b-256 229f0ef94b4650d741b6eed2be7a9591844dac94d999c5e2f990f5b55b004e6a

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.1.post1-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

  • Download URL: itk_segmentation-5.2.1.post1-cp39-cp39-macosx_11_0_arm64.whl
  • Upload date:
  • Size: 12.3 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-5.2.1.post1-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 3b95e009b231ed72577fba0c659eeb777fc226e88f9fa7768b53fc21d7d889be
MD5 2893a23c89b023412f83cece63c91283
BLAKE2b-256 90bd6a38175b888ff8a25e2c394b1565a8042d1b49071651b41a19e24fb1261a

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.1.post1-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: itk_segmentation-5.2.1.post1-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-5.2.1.post1-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 e3ac06a6e6db5951e1ef1741030b232936d519691cb7e030f0a09980cbd3d7a6
MD5 ffb98760f7756993c7975deaa74eb688
BLAKE2b-256 c5d5465354f3f36b9ef64832d75bc48de3888e1d0ddc4817d433da3efa043f41

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.1.post1-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: itk_segmentation-5.2.1.post1-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-5.2.1.post1-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 ba5c39d9fe7c9bd6cc0dbada82da86ea154ee9c56bf90557c0c91b25261c8c6f
MD5 ff6dd49bfd6d7a038db102562a2dd98e
BLAKE2b-256 ed72b3be7b5ab0ed62c2a012dbfe06fcbe46b9f4c7c0f7047734a87011d38997

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.1.post1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.2.1.post1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 ba57eabcd353099176c89b5bf348429b74823f7127cac650cb17031c9d284498
MD5 9a6dcad4165df85c9c11ee2c3cb0449b
BLAKE2b-256 05f0cd9b96446acd9ed29a167e946dc4a286d18f21d1b590dd772095652ff76f

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.1.post1-cp38-cp38-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.2.1.post1-cp38-cp38-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 cf4844b7b16e9dcdae5f47c100b754f6460fe00881818b36f32a5c29f09b35d1
MD5 f237bf680468ab1fb5fe099108882ce4
BLAKE2b-256 23f09a31aa4a097de51e6d3d78250acf317b78f05bbbf5562c4f9705c6c6e149

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.1.post1-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: itk_segmentation-5.2.1.post1-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-5.2.1.post1-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 1d835a80f7a79938d39f3334ac3fee0867576d6f778461e44a1fe6eca51c49c4
MD5 d4a7143647467505c48058c1ef457e71
BLAKE2b-256 a2fe848eeaeaab437dff5a3007b4aa9a613afa757b288ccc02ec39e8a97e8b4e

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.1.post1-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: itk_segmentation-5.2.1.post1-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-5.2.1.post1-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 3f69066ef49304928e3690a6321236526df0c3efd933af8884cd9e1f6e72dd76
MD5 1abcbc4e6342b38d49c91623e21bac22
BLAKE2b-256 fa780ef394234aa20701de67d77069ec625b0930db61956a0faadb601a39f981

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.1.post1-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.2.1.post1-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 a8020796164463ba0df5ede33a10ae3907df9c69e9723c41afd950c2d36ea3d4
MD5 ef0d2eb161099641e688a4e8b1fdc470
BLAKE2b-256 c8d3d741da307667579a646af097da803659b442f1b3cb5cfc0901db9953f7ee

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.1.post1-cp37-cp37m-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.2.1.post1-cp37-cp37m-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 2fa12e2f0160c9038f9cc5cde9184b17f5e8f0a147cac3cb9ff2622be2bb9afa
MD5 47dd3e9a6a7780621dae8b6b5d025d61
BLAKE2b-256 fc6d9ec5648010794c4b1968d856d67670a3de8a51a3b90f31f240db4ccac457

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.1.post1-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: itk_segmentation-5.2.1.post1-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-5.2.1.post1-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 bd2e08cbe29f7be4ef2963e31711a392a0ea0787493294bda075e1586e95fa67
MD5 a1ddc76f78cb10bb00a3336043e48d9b
BLAKE2b-256 3b73713fb071d38f67d04c7781346c4ec1975dddfef859cd2409db9db1cdedcd

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.1.post1-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: itk_segmentation-5.2.1.post1-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-5.2.1.post1-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 93b7a447a18e6c79d67c31a55c761fe49bd8d45895dfaa1e9a01b0a94b39afbc
MD5 f21182bceca66dfcde545324b833756d
BLAKE2b-256 554c4445fa3e681a136d05ce369720a99d13b889c152dc70ba4f74011de0d8db

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.1.post1-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.2.1.post1-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 4d361fb1d13cbe7a380ff509375b8f98c641c5f2922841e4214f9a755bc7277c
MD5 386c11794cad8f64b86b8387eba1079b
BLAKE2b-256 69760856cd2d412d4d4bf93523fca52df541c98f50fe6acac706345e297c746e

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.1.post1-cp36-cp36m-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for itk_segmentation-5.2.1.post1-cp36-cp36m-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 8ed06a271576b65c96dd8efce76108ab4a7a30387ef17dafe4166eaf7122c8da
MD5 626d557dbb8ad5a35afe3ef953d83b79
BLAKE2b-256 e1d17fcf4f94ecc5a9e212117951b48b7c4eaba8e27628a77935ba1934cd8803

See more details on using hashes here.

File details

Details for the file itk_segmentation-5.2.1.post1-cp36-cp36m-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: itk_segmentation-5.2.1.post1-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-5.2.1.post1-cp36-cp36m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 72d541bf2f343def6d021f9f8f5fea8896f4b328f3696b366661e7296b2361cb
MD5 2583bd3f2f77a96f289e890d6c4ff55b
BLAKE2b-256 3786ba7153ec742caaa3e8c89315ddbd9b1a744de96213e4300f1372613a76f6

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