Ferienakademie 2023:
Computational Medical Imaging

Summer school course

• Date: September 17 to 29, 2023
• Location: Sarntal Valley, South Tyrol, Italy

• Instructors:
• PD Dr. Christian Riess (Friedrich-Alexander Universität Erlangen-Nürnberg)
• PD Dr. Tobias Lasser (Technische Universität München)
• Guest lecturers:
• Melia Fleischmann (LMU Klinikum)
• Alessandro Wollek (Technische Universität München)

Course description

In this course we will explore computational imaging techniques in the context of medical imaging. This covers the various image processing tasks such as segmentation, registration, detection and classification, as well as tomographic reconstruction. As in many other fields, deep learning techniques have had a tremendous impact in medical imaging, next to, and in combination with, the more classical variational methods.

The course is organized in two parts. In the first part, each participant will give a 30 minute presentation on a selected topic of computational medical imaging. In the second part, the participants will work together to develop a small-scale application of computational imaging in the context of X-ray imaging. We will be building upon existing open source frameworks, using a Python interface.

Link to last year's course.

Course materials

Presentations: (for PDFs see GitLab instance)

1. Introduction to computational imaging and inverse problems
2. Image processing: cost functions and regularization
3. Image processing: optimization algorithms
4. Introduction to deep learning
5. Backpropagation and training neural networks
6. Introduction to the medical perspective of computational imaging
7. X-ray CT: the X-ray transform and its discretization
8. X-ray CT: statistical iterative reconstruction
9. X-ray CT: dealing with incomplete data (low dose, sparse acquisition, limited angle)
10. X-ray CT: reconstruction with deep learning
11. Generative adversarial networks
12. Saliency maps
13. Transformers
14. Stable diffusion
15. Reinforcement learning
16. Large language models
17. Fourier light field microscopy
18. X-ray dark-field imaging
19. X-ray tensor tomography
20. Out of distribution detection
21. Machine learning security