We are happy to announce the Insight Toolkit (ITK) 5.1 Release Candidate 1 is available for testing! ITK is an open-source, cross-platform toolkit for N-dimensional scientific image processing, segmentation, and registration.

ITK 5.1 is a feature release that improves and extends the major ITK 5.0 release. ITK 5.1 includes a NumPy filter interface, clang-format enforced coding style, enhanced modern C++ range support, and much more.


Python Packages

Install ITK pre-release binary Python packages with:

pip install --pre itk

Library Sources

Testing Data

Unpack optional testing data in the same directory where the Library Source is unpacked.



RTK sphere reconstruction

Tomographic sphere reconstruction with the RTK remote module. Reproduce this result by installing the RTK Python packages, pip install itk-rtk, and run the FirstReconstruction.py example.

Pass NumPy Array’s to ITK Image Filters

The Pythonic, functional-like interface to all ITK image-to-image-filters now directly supports operation on NumPy array’s, i.e. numpy.ndarray. If a ndarray is passed as an input, a ndarray is returned as an output.

For example,

smoothed = itk.median_image_filter(array, radius=2)

Previously, explicit conversion to / from an itk.Image was required with itk.array_from_image and itk.image_from_array.

We can now also convert an itk.Image to a numpy.ndarray with the standard np.asarray call.

import numpy as np
import itk

image = itk.imread('/path/to/image.tif')
array = np.asarray(image)

Python 3 Only

ITK 5.1 will be the first Python 3-only release. Consistent with most scientific Python packages and CPython’s 2020 drop in support, Python 2 support and binaries are no longer be available.

Python Package 64-bit Float Support

In addition to the many other pixel types supported, the itk binary Python packages now include support for the double pixel type, i.e. 64-bit IEEE floating-point pixels. This improves compatibility with scikit-image, which uses this pixel type as a default.

clang-format Enforced C++ Coding Style

ITK has adopted a .clang-format coding style configuration file so a consistent coding style can automatically be applied to C++ code with the clang-format binary. A consistent coding style is critical for readability and collaborative development.

clang-format has been applied to the entire codebase. The Whitesmiths style of brace indentation, previously part of the ITK Coding Style Guidelines, is not supported by clang-format, so it has been replaced by a brace style consistent with VTK’s current style.

A Git commit hook will automatically apply clang-format to changed C++ code.

Enhanced Modern C++ Range Support

In addition to the ImageBufferRange, ShapedImageNeighborhoodRange, and IndexRange classes introduced in ITK 5.0, ITK 5.1 adds an ImageRegionRange. These range classes conform to the Standard C++ Iterator requirements so they can be used in range-based for loop’s and passed to Standard C++ algorithms. Range-based for loops provide an elegant syntax for iteration. Moreover, they are often more performant than other iteration classes available.

For example, to add 42 to every pixel:

ImageBufferRange<ImageType> range{ *image };

for (auto&& pixel : range)
  pixel = pixel + 42;

In ITK 5.1, adoption of the range classes was extended across the toolkit, which demonstrates their use and improves toolkit performance.

Point Set Registration Parallelism

ITK provides a powerful registration framework for point-set registration, offering information-theoretic similarity metrics, labeled point-set metrics, and spatial transformation models that range from affine to b-spline to dense displacement fields. ITK 5.1 features enhanced parallelism in point-set metric computation, leveraging the native thread-pool and Threading Building Blocks (TBB) enhancements in ITK 5.

SpatialObject’s and Strongly-Typed enum’s

Improvements and refinements were made to the ITK 5 itk::SpatialObject refactoring, and modern C++ interface. In particular, ITK 5.1 transitions enumerations to strongly-typed enumerations, which is flagged by modern compilers due to improved scoping and implicit conversions to int. Enum names are now follow a consistent <Description>Enum naming conversion, which results in a Python interface:


DICOM Support

ITK’s broadly adopted medical image support is hardened thanks to 20 years of testing and support from major open source DICOM libarary maintainers. In this release, many members of the community collaborated to further enhance ITK’s DICOM support for corner cases related to modality, pixel types, and vendor variations.

Remote Module Updates

Many remote modules were updated: AnalyzeObjectMapIO, AnisotropicDiffusionLBR, BSplineGradient, BioCell, BoneEnhancement, BoneMorphometry, Cuberille, FixedPointInverseDisplacementField, GenericLabelInterpolator, HigherOrderAccurateGradient, IOMeshSTL, IOOpenSlide, IOScanco, IOTransformDCMTK, IsotropicWavelets, LabelErodeDilate, LesionSizingToolkit, MinimalPathExtraction, Montage, MorphologicalContourInterpolation, ParabolicMorphology, PhaseSymmetry, RLEImage, RTK, SCIFIO, SimpleITKFilters, SkullStrip, SplitComponents, Strain, SubdivisionQuadEdgeMeshFilter, TextureFeatures, Thickness3D, TotalVariation, and TwoProjectionRegistration. Their updates are included in the detailed changelog below.


Congratulations and thank you to everyone who contributed to this release. Of the 50 authors, we would like to specially recognize the 20 new contributors: Mathew J. Seng, Zahil Shanis, yjcchen0913, PA Rodesch, Aurélien Coussat, yinkaola, Bryce Besler, Pierre Chatelier, Rinat Mukhometzianov, Ramraj Chandradevan, Hina Shah, Gordian Kabelitz, Genevieve Buckley, Aaron Bray, nslay, Antoine Robert, James Butler, Matthew Rocklin, Gina Helfrich, and Neslisah Torosdagli.

What’s Next

As we work towards the next release candidate, we will improve strongly typed enum adoption in the toolkit, consistent with the soft commitment to backwards compatibility to address any potential API or architectual issues until the 5.1.0 release. Please try out the current release candidate, and discuss your experiences at discourse.itk.org. Contribute with pull requests, code reviews, and issue discussions in our GitHub Organization.

A detailed changelog can be found in the Discourse release announcement.

Enjoy ITK!

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