SIRF-Exercises

This material is intended to get you going with SIRF, an open source framework for PET, SPECT and MR Image Reconstruction, including synergistic aspects.

This repository also contains basic information on CIL functionality to show similarities with SIRF and how use CIL's optimisation algorithms.

This software is distributed under an open source license, see LICENSE.txt for details.

Links to documentation

Full instructions on getting started are in our documentation for participants (or use this link to GitHub for nice formatting, but do check which version of the exercises you are using). Despite the name, this documentation is also appropriate if you are trying these exercises on your own.
Gentle request: If you are attending a course, please read this before the course.

Instructors should check our documentation for instructors.

Installation instructions when you do not use our cloud resources are in INSTALL.md, but read the above links first.

You can run the SIRF-Exercises in GitHub Codespaces, see the section in the documentation, including information on which kernel to select (and more!).

Authors

• Kris Thielemans (this document and PET exercises)
• Christoph Kolbitsch (MR exercises and Introductory exercises)
• Johannes Mayer (MR exercises)
• David Atkinson (MR and geometry exercises)
• Evgueni Ovtchinnikov (PET and MR exercises)
• Edoardo Pasca (overall check and clean-up)
• Richard Brown (PET and registration exercises)
• Daniel Deidda and Palak Wadhwa (HKEM exercise)
• Ashley Gillman (overall check, scripts and clean-up)
• Imraj Singh (Deep Learning for PET exercise)
• Daniel Deidda and Sam Porter (Synergistic SPECT/PET Reconstruction Exercises)