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simpleitk

SimpleITK is a simplified interface to the Insight Toolkit (ITK) for image registration and segmentation

simpleitk v2.5.6 824.1K downloads/30d#4,964 on PyPI1,082
Permissive license Apache Active released

What it is and what it does

SimpleITK is a C++ image analysis library wrapped for Python that simplifies access to the Insight Toolkit (ITK). It supports filtering, segmentation, and registration workflows on 2D, 3D, and 4D images, with voxels that can be n-dimensional vectors. The package is built on ITK but provides a more approachable API than the underlying C++ toolkit, making it suitable for research, education, and clinical applications.

The library is distributed as precompiled wheels for multiple platforms and Python versions, eliminating the need to build from source in most cases. It has no declared runtime dependencies, making it lightweight to install once the binary is available. Development is active, with the project maintained by the Insight Software Consortium and NumFOCUS.

Use it for:

  • Segment anatomical structures in medical images (CT, MRI, ultrasound) for clinical analysis or surgical planning.
  • Register multiple images to a common coordinate system for longitudinal studies or multi-modal fusion.
  • Apply standard image filters (Gaussian, median, morphological) to preprocess images before analysis.
  • Extract and analyze image statistics and features for quantitative biomarker research.
  • Prototype image analysis algorithms in Jupyter notebooks for reproducible research and education.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

SimpleITK provides a simplified Python interface to the Insight Toolkit (ITK) for performing image segmentation, registration, and general filtering operations on 2D, 3D, and 4D images.

Yes. SimpleITK is a stable, actively maintained toolkit with no known vulnerabilities, permissive licensing, and broad platform support. It fills a clear niche for Python developers working with medical or scientific images who need segmentation and registration without the complexity of raw ITK. Medium install friction is typical for compiled libraries and is not a barrier given the availability of prebuilt wheels.

Install

simpleitk on PyPI

pip

pip install simpleitk

uv

uv add simpleitk

poetry

poetry add simpleitk

Installing simpleitk

Before you install

Medium install friction due to compiled C++ bindings; prebuilt wheels are available for common platforms (macOS x86_64/arm64, Linux x86_64/aarch64, Windows x86_64) across Python 3.9–3.14. Last release was 15 days ago and the repository remains actively maintained.

License in practice

Licensed under Apache 2.0 (permissive), allowing commercial and private use with minimal restrictions. Copyright held by NumFOCUS under the Insight Software Consortium.

Quickstart

import simpleitk as sitk
image = sitk.ReadImage('image.dcm')
filtered = sitk.MedianImageFilter().Execute(image)

Requires a compatible Python version and a platform with prebuilt wheel support (macOS, Linux, Windows).

Verify before relying

  • Specific minimum Python version requirement (requires_python is unspecified in metadata).
  • Whether numpy or other array libraries are required at runtime despite zero declared runtime dependencies.
  • Performance characteristics and memory footprint for large 3D/4D image datasets.

Package facts

License Apache (permissive)
Python support not specified
Install friction medium — platform-specific wheel
Runtime dependencies none
Maintenance actively maintained — 15 days since the last release
Last repo commit
First released
Downloads 824,116/month — #4,964 on PyPI (30-day window, as of 2026-08-14)
Known vulnerabilities none known (OSV.dev, checked 2026-08-14)

Evidence: simpleitk-2.5.6-cp310-cp310-macosx_10_9_x86_64.whl; simpleitk-2.5.6-cp310-cp310-macosx_11_0_arm64.whl; simpleitk-2.5.6-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.whl; simpleitk-2.5.6-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl; simpleitk-2.5.6-cp310-cp310-win_amd64.whl; simpleitk-2.5.6-cp311-abi3-macosx_10_9_x86_64.whl; simpleitk-2.5.6-cp311-abi3-macosx_11_0_arm64.whl; simpleitk-2.5.6-cp311-abi3-manylinux2014_aarch64.manylinux_2_17_aarch64.whl; simpleitk-2.5.6-cp311-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl; simpleitk-2.5.6-cp311-abi3-win_amd64.whl; simpleitk-2.5.6-cp314-cp314t-macosx_10_9_x86_64.whl; simpleitk-2.5.6-cp314-cp314t-macosx_11_0_arm64.whl; simpleitk-2.5.6-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.whl; simpleitk-2.5.6-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.whl; simpleitk-2.5.6-cp314-cp314t-win_amd64.whl; simpleitk-2.5.6-cp39-cp39-macosx_10_9_x86_64.whl; simpleitk-2.5.6-cp39-cp39-macosx_11_0_arm64.whl; simpleitk-2.5.6-cp39-cp39-manylinux2014_aarch64.manylinux_2_17_aarch64.whl; simpleitk-2.5.6-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.whl; simpleitk-2.5.6-cp39-cp39-win_amd64.whl

Keywords: SimpleITK, ITK, InsightToolkit, segmentation, registration

Development Status :: 5 - Production/StableIntended Audience :: EducationIntended Audience :: Healthcare IndustryIntended Audience :: Science/ResearchLicense :: OSI Approved :: Apache Software LicenseOperating System :: MacOSOperating System :: Microsoft :: WindowsOperating System :: POSIXOperating System :: UnixProgramming Language :: C++Programming Language :: PythonTopic :: Scientific/EngineeringTopic :: Scientific/Engineering :: Information AnalysisTopic :: Scientific/Engineering :: Medical Science Apps.Topic :: Software Development :: Libraries

Tags

image segmentation registrationmedical image analysisitk python wrapperimage filtering toolkitbiomedical image processing
medical-imagingimage-processingsegmentation-registration

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