ITK 4.8 Released to Further Medical Computing Research and Development

New Python wrapping and cross-compilation features enhance support for ITK’s active community.

On behalf of the Insight Segmentation and Registration Toolkit (ITK) community, Kitware is pleased to announce the release of ITK 4.8.0. This is a major release that offers substantial benefits to the medical computing community by making the toolkit more accessible to non-C++ programmers and by providing greater availability on mobile, high-performance computing (HPC), and web-browser platforms. The release includes several improvements to ITK in regards to Python wrapping, infrastructure, filtering, registration, and documentation. It also includes new remote modules, third-party library updates, advanced compiler support, and enhanced code coverage.

A key highlight of the release is the introduction of a Python-wrapping infrastructure based on C-family Abstract Syntax Tree XML Output (CastXML). This infrastructure works with the latest Microsoft Visual C++ (MSVC), Clang, and GNU Compiler Collection (GCC) compilers. Also introduced in the release is itk::FFTPadImageFilter, which automatically pads images for the greatest prime factor supported by the fast Fourier transform (FFT) implementation.

ITK 4.8 presents new remote modules including BridgeNumPy, LabelErodeDilate, ParabolicMorphology, and MinimalPathExtraction; and more modules can be built as shared libraries. The 4.8 release also features enhanced point set registration capabilities, along with experimental cross-compilation support for Windows (MinGW-w64), ARMv6 (Raspberry Pi), ARMv7 (Android), ppc64le (POWER8), and JavaScript (Emscripten).

ITK is an open-source, cross-platform system that provides developers from around the world with an extensive suite of software tools for image analysis. Since development through extreme programming methodologies began in 1999, ITK has delivered leading-edge algorithms for processing multidimensional MRI, CT, ultrasound, PET, fluoroscopy, and microscopy data.

For more information on ITK 4.8, please visit the Kitware blog. To download the software, go to

This material is based upon work funded in whole by a $781,998 award from the National Library of Medicine.

Image courtesy of Dan Mueller, Queensland University of Technology (

Questions or comments are always welcome!