About SimpleITK

SimpleITK is a simplified programming interface to the algorithms and data structures of the Insight Toolkit (ITK). It supports interfaces for multiple programming languages including C++, Python, R, Java, C#, Lua, Ruby and TCL. These bindings enable scientists to develop image analysis workflows in the programming language they are most familiar with. The toolkit supports more than 15 different image file formats, provides over 280 image analysis filters, and implements a unified interface to the ITK intensity-based registration framework.


The SimpleITK community includes researchers from a variety of domains that require image analysis capabilities without requiring extensive expertise in software development. Originally the community consisted primarily of researchers from the biomedical sciences, though it has since expanded to many other disciplines. In the context of bio-medicine, the toolkit has been used in the analysis of anatomical structures imaged with CT, MR, and PET, and analysis of cellular structures imaged using dual photon microscopy, focused ion beam scanning electron microscopy and focal plane array microscopy.

Outside of bio-medicine the toolkit has been used in a broad range of applications, from identification of microplastics in micro-Fourier transform infrared microscopy, to analysis of fuel cells using X-ray tomography, and for alignment of remote sensing images acquired by unmanned aerial systems. Outside of the research setting, the toolkit is used in medical image analysis courses at multiple academic institutions, allowing students to focus more on the algorithms and less on learning complex software interfaces.


SimpleITK was created as part of a concerted effort to simplify the use of the Insight Toolkit, making it more accessible to a wider audience. The initial funding for the toolkit was provided by the United States National Library of Medicine (NLM) under the American Recovery and Reinvestment Act (ARRA), with the initial version of the toolkit developed as a collaboration between The Mayo Clinic, Kitware Inc, The University of Iowa and NLM's intramural research program. The first major release of the toolkit was announced in April-May 2017.

Between 2013 and 2019, development was supported by the NLM intramural research program with collaborators at The University of Iowa and Monash University. Since 2019, SimpleITK development is supported by the Office of Cyber Infrastructure and Computational Biology at the National Institute of Allergy and Infectious Diseases.


The SimpleITK project is part of the Insight Software Consortium a non-profit educational consortium dedicated to promoting and maintaining open-source, freely available software for medical image analysis. The copyright is held by NumFOCUS. The SimpleITK software is distributed under the Apache License 2.0.


If you found SimpleITK useful in your research, support our efforts by citing the relevant publication(s):

  • R. Beare, B. C. Lowekamp, Z. Yaniv, “Image Segmentation, Registration and Characterization in R with SimpleITK”, J Stat Softw, 86(8), doi: 10.18637/jss.v086.i08, 2018.
  • Z. Yaniv, B. C. Lowekamp, H. J. Johnson, R. Beare, “SimpleITK Image-Analysis Notebooks: a Collaborative Environment for Education and Reproducible Research”, J Digit Imaging., doi: 10.1007/s10278-017-0037-8, 31(3): 290-303, 2018.
  • B. C. Lowekamp, D. T. Chen, L. Ibáñez, D. Blezek, “The Design of SimpleITK”, Front. Neuroinform., 7:45. doi: 10.3389/fninf.2013.00045, 2013.