We are happy to announce the Insight Toolkit (ITK) 5.3 Release Candidate 4 is available for testing! :tada: ITK is an open-source, cross-platform toolkit for N-dimensional scientific image processing, segmentation, and registration.

ITK 5.3 is a feature release that accelerates performance, provides new segmentation and shape analysis algorithms, improves documentation, adds distributed computing support, among many more improvements. For more information about performance improvements, see the 5.3 RC 1 Release Notes. For more information about new segmentation and shape analysis algorithms, see the 5.3 RC 2 Release Notes. For more information about documentation improvements, see the 5.3 RC 3 Release Notes.

ITK 5.3 RC 4 highlights distributed computing support with Dask. Dask is a Python library that makes scaling analysis easy through simple programming on a laptop that can then be deployed to HPC or cloud computing resources. In ITK 5.3 RC 4, Dask support applied in medical imaging, bioimaging, and material science, is robust (caveat: import itk should be called in Dask worker functions). Furthermore, support was expanded from NumPy array views on itk.Image‘s to full metadata-perserving distributed computing with itk.Image, itk.Mesh, itk.PointSet, and itk.Transform. With ITK’s Dask support, batch processing a cohort of thousands of medical images or processing biomicroscopy, histopathology, or geospatial images with trillions of pixels is now a matter of minutes instead of weeks.

ITK 5.3 RC 4 also includes advancements in Python interface file (.pyi) support and new remote modules to build WebAssembly processing pipelines to native executables and support ITK WebAssembly file formats, perform multimaterial tetrahedral meshing from segmentations, and read meshes from SWC files, a format for representing neuron morphology.

Knee MRI mapping of cartilage thickness in osteoarthritis that leverages ITK’s Dask support for distributed processing of large patient cohorts over the preprocessing, segmentation, registration, and post-processing steps of the analysis pipeline.


Python Packages

Install ITK Python packages with:

pip install --upgrade --pre itk

Guide and Textbook

Library Sources

Testing Data

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




  • Python packages now include oneTBB support for improved performance
  • Following CPython’s deprecation schedule Python 3.6 is no longer supported
  • Python packages added for Python 3.10
  • Initial Python wrapping is available for the Video modules
  • TransformToDisplacementField is now available in Python
  • Pythonic IO functions itk.imread understands pathlib.Path‘s
  • New repr for itk.Matrix
  • np.asarray works on itk.Matrix
  • DCMTKImageIO wrapping addressed
  • GradientDifferenceImageToImageMetric wrapped
  • SynImageRegistrationMethod, BSplineSynImageRegistrationMethod wrapped
  • ConjugateGradientLineSearchOptimizerv4 wrapped
  • Wrap ImageRegistrationMethodv4 for itk.Mesh
  • Wrap PointSetToPointSetMetric, PointSetToPointSetRegistrationMethod
  • Wrap ANTSNeighborhoodCorrelationImageToImageMetricv4
  • Nearly all registration v4 classes are now wrapped
  • VectorImage input for DisplacementFieldTransform
  • Python wrapping for spatial orientation functionality
  • PyImageFilter wrapped for additional types, supports pipeline functionality
  • NumPy array interfaces for itk.PointSet, itk.Mesh
  • manylinux_2_28 and manylinux2014 wheels are provided
  • Dask support for itk.Image, itk.PointSet, itk.Mesh, itk.Transform


  • C++14 is now required
  • The minimum CMake version required is now 3.16.3
  • New functions: MakePoint, MakeVector, MakeIndex, MakeSize.
  • Targets in Visual Studio and other IDE’s are now organize hierachically by ITK Group and Module
  • Most of itk::mpl meta-programming functions replaced by C++14 equivalents
  • Performance accelerations for b-spline interpolation, Mattes mutual information metric computation
  • Improved modern C++ adoption, e.g. additional adoption of constexpr, auto
  • itk::ReadMesh, itk::WriteMesh simple reader functions available, similar to itk::ReadImage, itk::WriteImage
  • FFT backends are now registered through the object factory mechanism
  • cbegin() and cend() member functions to Index, Offset, Size
  • Add itk::MakeFilled<TContainer>(value)
  • itk::ConvertNumberToString<TValue>(val) convenience function
  • itk::bit_cast<TDestination>(source) function
  • itk::PolyLineCell
  • InputSpaceName and OutputSpaceName support for itk::Transform
  • qfac, qt_xyz added to Nifti metadata
  • LZW compression support
  • Support requested output region in FFT filters
  • Many code coverage improvements

New filters

  • itk::TransformGeometryImageFilter: applies a rigid transform to an Image‘s metadata.
  • 1D FFT classes
    • Interface classes for forward, inverse transformations
    • Vnl implementations
    • FFTW implementations
  • itk::TriangleMeshCurvatureCalculator – Gaussian curvature calculator for itk::Mesh
  • FFTDiscreteGaussianImageFilter — discrete gaussian filters via FFTs

Remote module updates

New remote modules:

  • HASI: High-Throughput Applications for Skeletal Imaging
  • ITKGrowCut: segments a 3D image from user-provided foreground and background seeds
  • ITKMeshToPolyData: Convert an ITK Mesh to a simple data structure compatible with vtkPolyData
  • ITKCudaCommon: Framework for processing images with CUDA
  • itk-wasm WebAssemblyInterface: Build WebAssembly processing pipelines to native executables and support ITK WebAssembly file formats
  • ITKCleaver: Multimaterial tetrahedral meshing.
  • ITKIOMeshSWC: Read meshes from SWC files, a format for representing neuron morphology.

Updated modules: AdaptiveDenoising, AnisotropicDiffusionLBR, BSplineGradient, BoneEnhancement, BoneMorphometry, Cuberille, GrowCut, HASI, HigherOrderAccurateGradient, IOFDF, IOScanco, IsotropicWavelets, MinimalPathExtraction, Montage, MorphologicalContourInterpolation, RTK, SimpleITKFilters, SkullStrip, SplitComponents, Strain, TextureFeatures, Thickness3D, TotalVariation, TubeTK, and Ultrasound.

Third party library updates

  • dcmtk
  • eigen
  • expat
  • fftw
  • gdcm
  • googletest
  • hdf5
  • kwsys
  • kwiml
  • minc
  • metaio
  • niftilib
  • vxl
  • zlib migrated to zlib-ng

Detailed Changelog

Find a detailed changelog in the full release notes.


Congratulations and thank you to everyone who contributed to this release.

Of the 76 authors who contributed since v5.2.0, we would like to specially recognize the new contributors:

Michael Kuczynski, Tim Evain, Tomoyuki SADAKANE, Mario Emmenlauer, Andreas Gravgaard Andersen, Ebrahim Ebrahim, josempozo, Wenqi Li, Genevieve Buckley, Oleksandr Zavalistyi, Jose Tascon, Pranjal Sahu, ambrozicc1, Vagrant Ca scadian, MrTzschr, Philip Cook, Tihomir Heidelberg, Jason Rudy, Kian Weimer, z0gSh1u, Darren Thompson, Darren, Jose M Pozo, Paul Elliott, Gabriele Belotti, Rafael Palomar, Fernando Hueso-González, Mark Asselin, mrhardisty, Laryssa Abdala, Roland Bruggmann, Natalie Johnston, and ferdymercury.

What’s Next

This is the last release candidate before the 5.3.0 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.

Enjoy ITK!

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