SimpleITK Image-Analysis Notebooks: a Collaborative Environment for Education and Reproducible Research

Ziv Yaniv, Bradley C. Lowekamp, Hans J. Johnson, Richard Beare

Research output: Contribution to journalArticleResearchpeer-review

48 Citations (Scopus)

Abstract

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: github.com/InsightSoftwareConsortium/SimpleITK-Notebooks.

Original languageEnglish
Pages (from-to)290-303
Number of pages14
JournalJournal of Digital Imaging
Volume31
Issue number3
DOIs
Publication statusPublished - 1 Jun 2018

Keywords

  • Image analysis
  • Open-source software
  • Python
  • R
  • Registration
  • Segmentation

Cite this