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

Area of Science:

• Computational biology
• Scientific computing
• Bioinformatics

Background:

• Modern scientific research relies heavily on complex computational workflows.
• Effective collaboration and interpretation of these workflows are crucial for scientific advancement.
• Scientists often face challenges with varying software development skills.

Purpose of the Study:

• To describe an image-analysis environment supporting reproducible research.
• To enable scientists with diverse programming skills to utilize computational tools.
• To facilitate flexible, well-documented, and reproducible scientific workflows.

Main Methods:

• Utilized the Jupyter notebook web application as the foundation for the environment.
• Integrated the SimpleITK toolkit, a simplified interface to the Insight Segmentation and Registration Toolkit, for accessible image analysis.
• Incorporated features for user-friendly data sharing via online repositories and a testing framework for code maintenance.

Main Results:

• Developed an environment enabling reproducible research through literate programming.
• Made image-analysis software development accessible to scientists with varying programming experience.
• Facilitated flexible and well-documented computational workflows.

Conclusions:

• The described environment enhances collaborative scientific endeavors in computational image analysis.
• SimpleITK and Jupyter notebooks provide a powerful combination for reproducible and accessible research.
• The environment supports scientists in constructing and interpreting complex computational workflows effectively.