SimpleITK 2.0 Release Candidate 1


Announcing the SimpleITK 2.0 Release Candidate 1!

NOTE: SimpleITK neither supports Python 2.7 nor provides 32-bit binaries as of version 2.0.

Installing SimpleITK

Complete instructions on getting started with SimpleITK including downloading binaries or building SimpleITK can be found on the SimpleITK Read the Docs web page.

Python Binary Downloads

  • Including Python 3.8 support!
  • Python binary wheels are available for download. It is important to have the latest version of pip for correct wheel compatibility and installation. To install the latest SimpleITK package from GitHub releases:
python -m pip install --upgrade pip
python -m pip install --pre SimpleITK --find-links

Anaconda Binary Downloads

Conda packages are available from Anaconda Cloud on the SimpleITK channel with the dev label. These can be installed with:

conda install -c simpleitk/label/dev simpleitk

Release Notes

New Features

  • Update ITK version to 5.1rc2.
  • Disable ITK 4 legacy behaviors.
  • For ImageViewer add user’s Application folder to search path.
  • Add SignedDanielssonDistanceMapImageFilter::GetVoronoiMap method.
  • Add wrapping for CannySegmentationLevelSetImageFilter.
  • Update levelset segmentation filters to support named inputs.
  • Add 4D support toSliceImageFilter and to the Python slice indexing.
  • Add complex pixel support to Image::GetBufferAs... methods.
  • Add Python support for complex pixels to GetArrayFromImage, GetImageFromArray and GetArrayViewFromImage methods.
  • Add wrapping for BinaryPruningImageFilter.
  • Add per label measurements to LabelOverlapMeasuresImageFilter.
  • Add Python deepcopy support to Image class, this ensure the copy is unique with lazy copying implementation.
  • Add Python pickling support for Image and Transform classes.
  • ResampleImageFilter add option to use nearest neighbor extrapolation.
  • Add ReturnBinMidPoint parameter to OtsuThresholdImageFilter. Defaults to false which may change results.
  • Add ImageFileWriter and ImageSeriesWriter support to specify compression level and compression algorithm.
  • BSplineTransform Python support construction and SetCoefficientImage with list-like series of Images.
  • MeanImageFilter directly filters vector images, improving performance.
  • Add C# constant image buffer access methods of the form GetConstBufferAs....
  • Add to LabelShapeStatisticsImageFilter per label method GetIndexes and GetRLEIndexes.

Bug Fixes

  • Update StatisticsImageFilter input convention for ITKv5.
  • Remove WarpImageFilter matching image size requirement.
  • The results of the LiThresholdImageFilter changes with ITK, baseline test results were updated. ( See ITK commit e3ce37 for details. )
  • Add additional baseline images for registration results, due to change in ImageRegistration’s smoothing algorithm. ( See ITK commit 569a47 for details. )
  • Correct LabelShapeStatistics baseline for OrientedBoundingBoxVertices results. ( See ITK commit 50c695 for details. )
  • Fix potential double memory free of pixel container in results from internal image to vector image conversions.
  • Fix RelabelComponentImageFilter incorrect object size computation with sorting enabled. ( See ITK commit 162101 for details. )
  • Fix potential ITK pipeline execution error when a filter execute on a vector image by per component.
  • Add C++11 move semantics support to the Image class.
  • Add direct support for C++11 lambda command to the ProcessObject class.
  • Add GetBufferAsVoid method to the Image class.
  • Add Decay parameter to the MirrorPadImageFilter.


  • Update copyright to NumFOCUS.
  • Add casting to N4BiasFieldCorrection example.
  • Typo fixes.
  • Create Docker images for generating Doxygen.
  • Add C# ConnectedThresholdSegmentation example.
  • Remove references to next branch in documentation.
  • Update R installation instructions.
  • Add C# ImageReistrationMethod2 example.
  • Add multi-lingual examples for FastMarchingSegmentationImageFilter.
  • Uset stopping time parameter in FastMarchingSegmentation examples.
  • Add C# CannySegmentationLevelSetImageFilter example.
  • Improve documentation to GetImageFromArray about isVector parameter.
  • Update referenced tutorials.
  • Add acknowledgment section to readme.
  • Update Java and CSharp installation instructions.
  • Move Doxygen pages to Sphinx documents, remove other out dated pages.
  • Move Sphinx documentation to docs directory.


  • Require C++11 standard for compilation.
  • Replace C++ tr1 usage with standard C++11 classes.
  • Replace compiler depended defines with C+11 keywords.
  • Prefer using C++11 lambda over std::bind when std::placeholders are not needed.
  • Improve support on OSX for isysroot flag and CMAKE_OSX_SYSROOT variable.
  • Support additional CMAKE_GENERATOR_*, CMAKE_VS_PLATFORM_TOOLSET_* variables is superbuild.
  • Added AWS S3 buckets for data mirroring.
  • Use SHA512 hash files as index for downloaded source code.
  • Use CMake for creating zip archives.
  • Improve finding of Lua interpreter.
  • Update Lua superbuild version to 5.3.5, require Lua version 5.2 or 5.3 for code generation.
  • Update PCRE superbuild version to 8.43.
  • Add USE_CCACHE cmake option to automatically use ccache as launcher if available.
  • Enable GNU gold linker by default if available.
  • Update GTest vesrion to 1.10.0 in superbuild.
  • Fix incorrect version of virtualenv detected.


  • Continuing updates and improvements to the testing, build and packaging infrastructure.
  • Add tolerance for testing BSpline domains.
  • Update setup for development scripts to support github workflows.
  • Add Insight Software Consortium Code of Conduct.
  • Archive SHA512 in distributed data archive.
  • Disable ITK’s automatic advanced architecture compilation settings in packaging builds.

With the update to ITK 5.1, are there plans to support the xarray interface?

Great work and congrats to the SimpleITK team.

Just a query - is there a way we can setup that the releases tally with simpleitk channel in Anaconda - just had to get the python 3.8 release from the github release – would be a nice to have… let me know if I can help

The pre release are available in the dev channel on Anaconda Clound. Did you try the dev channel:

conda install -c simpleitk/label/dev simpleitk
1 Like

of course! thanks - I used the standard simpleitk channel oops