Are you a researcher looking for a programming environment where you can quickly evaluate various segmentation and registration approaches while collaborating with colleagues at other institutions?
Are you an educator teaching an image-analysis course and want to use a free modern development environment which is accessible to students proficient in Python or R?
If you answered yes to either of these questions, then read on.
We are proud to officially introduce the SimpleITK Jupyter notebooks environment:
For those interested in a detailed description of the environment and the rational for creating it, you can read our paper: “SimpleITK Image-Analysis Notebooks: a Collaborative Environment for Education and Reproducible Research”, freely available here.
Modern scientific endeavors increasingly require team collaborations to construct and interpret complex computational workflows. This work describes an image-analysis environment that supports the use of computational tools that facilitate reproducible research and support scientists with varying levels of software development skills. The Jupyter notebook web application is the basis of an environment that enables flexible, well-documented, and reproducible workflows via literate programming. Image-analysis software development is made accessible to scientists with varying levels of programming experience via the use of the SimpleITK toolkit, a simplified interface to the Insight Segmentation and Registration Toolkit. Additional features of the development environment include user friendly data sharing using online data repositories and a testing framework that facilitates code maintenance. SimpleITK provides a large number of examples illustrating educational and research-oriented image analysis workflows for free download from GitHub under an Apache 2.0 license.
posted on behalf of the SimpleITK development team