All lectures have been recorded and made available on this youtube playlist.
|Principles of PET and SPECT image reconstruction
|TotalBody PET challenges
|Principles of MR image reconstruction
|PyTorch principles for deep-learned iterative PET image reconstruction
- Write your own PET or SPECT reconstruction algorithm
- Synergistic PET and SPECT reconstruction
- Image reconstruction using Deep Learning
The school will cover basic principles of the physics behind the acquisition process and image reconstruction methods used for PET and SPECT, with specific information on the challenges for TotalBody PET. We will also briefly cover MR aspects. The school will include practical sessions with the Open Source software Synergistic Image Reconstruction Framework (SIRF).
The school will consist of a half day of lecture-style presentations followed by project-based work using SIRF (in Python). For maximum benefit, participants will be expected to get basic familiarity with SIRF and Python beforehand. Appropriate training material will be distributed before the school.
Prof. Kris Thielemans (University College London) and Prof. Andrew Reader (King’s College London) with assistance by Prof. Nicola Belcari (University of Pisa) for local arrangements.
Prof. Andrew Reader (King’s College London), Prof. Kris Thielemans (University College London), Dr. Christoph Kolbitsch (PTB, Berlin) and Dr. David Atkinson (University College London). Full list TBC.