Bump itk-numerics from 5.4rc3 to 5.4.0 in /envs

[dependabot]

Bumps itk-numerics from 5.4rc3 to 5.4.0.

Release notes

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ITK 5.4 Release Candidate 4: ALL THE DICOMs

We are happy to announce the Insight Toolkit (ITK) 5.4 Release Candidate 4 is available for testing! 🎉 ITK is an open-source, cross-platform toolkit for N-dimensional scientific image processing, segmentation, and registration.

🔦 Highlights

The Insight Toolkit (ITK) has further enhanced its DICOM capabilities in the latest release, building on over 25 years of extensive clinical usage and application. DICOM (Digital Imaging and Communications in Medicine) is a valuable standard handling, storing, printing, and transmitting information in medical imaging. It includes a wide range of medical data types and allows for various imaging modalities and workflow information, posing significant challenges due to its extensive support for diverse medical content and variations in vendor implementations and adherence to the standard.

This release introduces expanded support for additional modality features and crucial spatial metadata for Secondary Capture images. ITK significantly improves the way medical imaging data is processed and interpreted and ensures robust support for diverse DICOM applications.

The impact of spatial metadata handling on the NLM Visible Human cryomacrotome anatomic secondary capture images, available in the NIH Imaging Data Commons, when visualized in 3D Slicer. Left: before ITK v5.4rc04, Right: after. Screenshots courtesy Steve Pieper.

The development of ITK’s DICOM support is a testament to a robust community-driven effort involving ITK developers, maintainers from DICOM library projects such as GDCM and DCMTK, and curators of the DICOM standard. This release includes collaborative contributions from notable community members including Mikhail Isakov, Jon Haitz Legarreta Gorroño, Sean McBride, Martin Hoßbach, Mathieu Malaterre, Michael Onken, Steve Pieper, Andras Lasso, David Clunie, and Andrey Fedorov.

This release candidate also expands on our support for elegant, performant, modern C++. For example, specializations of std::tuple_size and std::tuple_element for itk::ImageRegion in order to support C++17 structured bindings enable compile-time optimized statements to provide a multidimensional region's index and size:

auto [index, size] = image.GetRequestedRegion();

For more information on ITK 5.4's modern C++ support, see the Release Candidate 1 release notes.

Moreover, this release candidate extends the toolkit's sustainability and Python support through Stable ABI Python wheels. This is made possible by upgrades to SWIG and scikit-build-core, the modern Python packaging standard evolution of scikit-build classic. Python 3.11 wheels will be recognized by pip and work with Python 3.11, 3.12, 3.13, 3.14, etc. While we also provide cross-platform wheels for Python 3.8-3.10, we can only use the Stable ABI with Python 3.11 because it is required for itk's NumPy support.

ITK Remote Modules now also have GitHub Action-driven mac ARM / Apple Silicon Python wheel generation support. While a Remote Module setup.py file is still supported in ITK 5.4, migration to a scikit-build-core pyproject.toml file is encouraged. One important advantage is the generation of Stable ABI wheels for Python 3.11+. To migrate to scikit-build-core, use this pyproject.toml template and remove the setup.py file.

ITK 5.4 contains many additional improvements; highlights can be found below along with a more detailed changelog. For a summary of changes that continue our sustainability evolution with Web3 testing data, see the 5.4 Release Candidate 2 release notes.

💾 Download

Python Packages

Install ITK Python packages with:

pip install --upgrade --pre itk

Guide and Textbook

• InsightSoftwareGuide-Book1-5.4rc04.pdf
• InsightSoftwareGuide-Book2-5.4rc04.pdf

Library Sources

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