About this project

Published

July 25, 2025

Who

This guide was developed by the Imaging Applications and Machine Learning team in Research IT at The Jackson Laboratory:

  • Fernando Cervantes
  • Kiya Govek
  • Erick Ratamero
  • Peter Sobolewski
It is open to contributions from anyone!

If something in the guide is unclear or you have suggestions for improvement—or maybe a task or tool to add!—please do not hesitate to reach out! You can use the GitHub links to open issues or edit the content and submit a pull request.

What

  • The goal of this guide is to provide a quick reference for selecting the right open-source tool for a given bioimage analysis task.
  • It is intended to help with getting started with a project, particularly for newcomers to (bio)image analysis.
  • It is organized by common tasks, such as manual annotation, segmentation, tracking, colocalization, etc., and for each task, a list of commonly used tools is provided. Finally, the guide includes brief overview descriptions of the tools.
  • Where possible we have linked to tutorials or documentation to help you get started.
Please note that the guide is not exhaustive!

At present, the focus is on tools that offer a graphical user interface (GUI) for ease of use, but in the future, we may expand to include command-line tools and libraries. Likewise, the focus is on tools or plugins that are well-supported, have a large user base, and are actively maintained, such that it is easy to find help if needed.