The Insight Toolkit (ITK) is an open-source, cross-platform toolkit for N-dimensional scientific image processing, segmentation, and registration. Documentation for the toolkit ranges from the ITK Software Guide textbook, to Doxygen API reference material, to C++ and Python examples. Slicer makes use of ITK filters for many image processing operations.
The ITK Examples hackathon aims to bring together ITK developers and new users to expand documentation and learn to use ITK tools for scientific image processing.
We will focus on expanding and adding new examples to https://examples.itk.org/index.html.
More information may be found at https://hackmd.io/WL6AxKj6Sy2O9GKtgj0LYA?view.
- Learn: Want to learn to use ITK, but not sure where to get started? Join the discussion and take your first steps with the ITK Python library!
- Contribute: Have you found a great way to apply ITK in your image processing work? Create an example to share your process with other community members!
- Meet: Want to interact with the ITK and scientific image processing community? Come meet the developers behind the curtain!
- Date: May 20th, 2022
- Time: 9am - 5pm EST
- Where: Google Meet
- Who: Anyone interested in contributing to the ITK community!
- Visit the ITK and ITKSphinxExamples Github repositories
- Create a Github account and fork the ITKSphinxExamples repository
- Add your ideas and suggestions for examples at ITKSphinxExamples/issues
- Install the most recent ITK Python packages for Python development
python -m pip install --pre itk
Run, tweak, and understand existing examples to learn about using ITK
Check out good first issues
Develop short C++ or Python scripts demonstrating a particular ITK filter or other mechanism
Develop Jupyter notebook in Python demonstrating an ITK pipeline
Chat with other attendees to learn about ITK and share perspectives
(Recommended) Have fun!