itk-segmentation
ITK is an open-source toolkit for multidimensional image analysis
Decision gist · record as of 2026-08-14
Yes, if you need production-grade medical image segmentation with established academic credibility. The Apache 2.0 license is permissive, maintenance is active, and pre-built wheels eliminate compilation friction. Install if your workflow involves ITK-based medical imaging; otherwise evaluate whether a specialized segmentation library (deep learning–based or domain-specific) better fits your task.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires itk-filtering as a runtime dependency; compiled wheels available for Python 3.8+ on Linux, macOS, Windows.
- Medium install friction due to compiled binary wheels.
- Released 7 days ago with active maintenance (last commit 2026-08-14).
License · maintenance · safety
permissive license (permissive) — Apache License 2.0 permits both non-commercial and commercial use with permissive terms. Derivative works must include attribution and license notices, but no copyleft obligations apply.
last release 2026-08-07 (7 days) · last repo commit 2026-08-14 · 1,643 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 214,316 downloads/mo, #9,419 on PyPI
Alternatives
Verify before relying
pip install itk-segmentation
import itk
# Load image and apply segmentation algorithm
image = itk.imread('scan.mha')
# Segmentation methods available via itk namespace- Whether itk-filtering is a separate install or bundled; exact segmentation algorithm coverage
- Performance characteristics for large 3D/4D medical datasets
- Integration maturity with common medical imaging workflows (DICOM, NIfTI)
What it is and what it does
itk-segmentation is a Python wrapper around the Insight Toolkit's segmentation module, part of ITK's broader ecosystem for medical image analysis. It provides access to segmentation algorithms designed for N-dimensional scientific images, particularly medical scans from CT and MRI instruments. The package depends on itk-filtering for core image processing operations.
Typical use involves loading a medical image, applying segmentation algorithms to identify and classify structures of interest (tumors, organs, tissues), and extracting the resulting labeled regions. The package is maintained by the Insight Software Consortium and NumFOCUS, with active development and broad platform support.
Use it for
- Segment organs or tumors from CT/MRI scans for clinical analysis or surgical planning
- Classify tissue types in volumetric medical images for research studies
- Preprocess medical imaging datasets for machine learning model training
- Align or register segmented structures across multiple patient scans
- Extract quantitative measurements from segmented anatomical regions
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need production-grade medical image segmentation with established academic credibility.
The Apache 2.0 license is permissive, maintenance is active, and pre-built wheels eliminate compilation friction. Install if your workflow involves ITK-based medical imaging; otherwise evaluate whether a specialized segmentation library (deep learning–based or domain-specific) better fits your task.
Install
itk-segmentation on PyPI
Before you install
Medium install friction due to compiled binary wheels. Released 7 days ago with active maintenance (last commit 2026-08-14). Supports Python 3.8+ across Linux, macOS (including Apple Silicon), and Windows with pre-built wheels.
Requires itk-filtering as a runtime dependency; compiled wheels available for Python 3.8+ on Linux, macOS, Windows.
License in practice
Apache License 2.0 permits both non-commercial and commercial use with permissive terms. Derivative works must include attribution and license notices, but no copyleft obligations apply.
Quickstart
pip install itk-segmentation
import itk
# Load image and apply segmentation algorithm
image = itk.imread('scan.mha')
# Segmentation methods available via itk namespaceVerify before relying
- Whether itk-filtering is a separate install or bundled; exact segmentation algorithm coverage
- Performance characteristics for large 3D/4D medical datasets
- Integration maturity with common medical imaging workflows (DICOM, NIfTI)
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.8 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | 1 packageitk-filtering |
| Maintenance | Actively maintained 7 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 214,316 / month, #9,419 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: DevelopersIntended Audience :: EducationIntended Audience :: Healthcare IndustryIntended Audience :: Science/ResearchLicense :: OSI Approved :: Apache Software LicenseOperating System :: AndroidOperating System :: MacOSOperating System :: Microsoft :: WindowsOperating System :: POSIXOperating System :: UnixProgramming Language :: C++Programming Language :: PythonProgramming Language :: Python :: 3Topic :: Scientific/EngineeringTopic :: Scientific/Engineering :: Information AnalysisTopic :: Scientific/Engineering :: Medical Science Apps.Topic :: Software Development :: Libraries |
Evidence: itk_segmentation-5.4.7-cp310-cp310-macosx_10_9_x86_64.whl; itk_segmentation-5.4.7-cp310-cp310-macosx_11_0_arm64.whl; itk_segmentation-5.4.7-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl; itk_segmentation-5.4.7-cp310-cp310-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl; itk_segmentation-5.4.7-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl; itk_segmentation-5.4.7-cp310-cp310-win_amd64.whl; itk_segmentation-5.4.7-cp311-abi3-macosx_10_9_x86_64.whl; itk_segmentation-5.4.7-cp311-abi3-macosx_11_0_arm64.whl; itk_segmentation-5.4.7-cp311-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl; itk_segmentation-5.4.7-cp311-abi3-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl; itk_segmentation-5.4.7-cp311-abi3-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl; itk_segmentation-5.4.7-cp311-abi3-win_amd64.whl; itk_segmentation-5.4.7-cp39-cp39-macosx_10_9_x86_64.whl; itk_segmentation-5.4.7-cp39-cp39-macosx_11_0_arm64.whl; itk_segmentation-5.4.7-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.whl; itk_segmentation-5.4.7-cp39-cp39-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl; itk_segmentation-5.4.7-cp39-cp39-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl; itk_segmentation-5.4.7-cp39-cp39-win_amd64.whl
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See also itk · itk-core · itk-numerics · itk-filtering · simpleitk · itkwasm · itk-io · itk-registration · TotalSegmentator · nnunetv2