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 some exercises using CIL, including basic functionality to show similarities with SIRF and how to use CIL's optimisation algorithms for synergistic reconstruction.
This software is distributed under an open source license, see LICENSE.txt for details.
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!).
- Kris Thielemans (this document and PET and synergistic exercises, overall QA)
- Christoph Kolbitsch (MR exercises and Introductory exercises)
- David Atkinson (MR and geometry exercises, overall QA)
- Evgueni Ovtchinnikov (PET and MR exercises)
- Johannes Mayer (MR exercises)
- Richard Brown (PET and registration exercises)
- Nicole Jurjew (updating, answers and checks of PET exercises)
- Daniel Deidda and Palak Wadhwa (HKEM exercise)
- Daniel Deidda and Sam Porter (Synergistic SPECT/PET Reconstruction Exercises)
- Margaret Duff and Sam Porter (Synergistic deconvolution exercise)
- Georg Schramm (Deep Learning for listmode PET exercise)
- Imraj Singh (Deep Learning for PET (projection data) exercise)
- Nikolaos Efthymiou (Long Axial FOV exercise)
- Ashley Gillman (overall checks, scripts and clean-up)
- Casper da Costa-Luis (overall checks, devcontainer and clean-up)
- Edoardo Pasca (overall checks and clean-up)