SimpleITK: image analysis via a simplified interface to the insight segmentation and registration toolkit
Friday, September 16, 2016 — Poster Session IV
- B Lowekamp
- D Chen
- Z Yaniv
- T Yoo
The Insight Segmentation and Registration Toolkit (ITK), an initiative of the National Library of Medicine, is a C++ open source toolkit for image analysis. It has been actively developed over the past 16 years and is widely used by experienced research teams in biomedical image analysis due to its robust engineering and extensive testing framework. We have developed SimpleITK, a simplified multi-language interface to ITK, enabling us to expand the toolkit’s audience to less experienced programmers. Experienced developers can also benefit from this simplified interface as it enables rapid prototyping of image segmentation and registration frameworks and facilitates evaluation of the effects algorithmic parameter settings have on results with minimal programming effort. Our development process follows best software engineering practices including code reviews and continuous integration testing, with results displayed online allowing everyone to gauge the “health” of the current code and any code that is under consideration for incorporation into the toolkit. User support is available through a dedicated mailing list and the project’s Wiki. In addition, we have developed educational material to support learning and teaching of SimpleITK. This material consists of Jupyter notebooks written in the Python programming language and spanning the gamut from simple tasks such as image input and output to complex tasks such as multi-modal image registration. SimpleITK is available for the following programing languages: Python, R, Java, C#, C++, Lua, Ruby, and TCL. Binary versions of the toolkit are available for the Linux, OS X, and Windows operating systems.
Category: Computational Biology