Learning goals:
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After the workshop, participants will be able to:
- Define basic principles of Artificial Intelligence
- Interpret schematic figures of neural networks
- Describe neural network architectures for different purposes
- Evaluate main steps for designing and building an AI algorithm
- Describe pitfalls in medical image segmentation
- Discuss potentials and current limitations of AI for medical image segmentation in clinical practice.
Dates: Friday, 25th March 2022 & Saturday 26th March 2022
Location: TranslaTUM, Munich & online
Scientific program:
Friday, 25th March 2022
| 13:00 – 13:15 | Welcome & Introduction | |
| 13:15 – 14:00 | Introduction to Artificial Intelligence in Medical Imaging | Daniel Rückert |
| 14:00 – 15:00 | From Machine Learning to Neural Networks | Matthias Keicher |
| Break | ||
| 15:30 – 16:30 | Basics of Convolutional Neural Networks | Martin Menten |
| 16:30 – 17:15 | How to design and build an AI algorithm for Medical Imaging | Tobias Czempiel |
| Break | ||
| 17:30 – 18:15 | Keynote: AI and the Future of Radiology | Julia Schnabel |
| 18:30 – 20:00 | Social Event @TranslaTUM |
Saturday, 26 March 2022
| 09:00 – 09:45 | Segmentation in Medical Imaging: From image-wise to voxel-wise prediction. | Veronika Zimmer |
| 09:45 – 10:30 | Segmentation in Medical Imaging: Evaluation measures and pitfalls | Veronika Zimmer & Anne Rickmann |
| Break | ||
| 11:00 – 11:45 | State of the art brain segmentation using Deep Learning | Christian Wachinger |
| 11:45 – 12:30 | Applications of image segmentation (I): Oncology | Rickmer Braren |
| Break | ||
| 13:30 – 14:15 | Applications of image segmentation (II): Neuroradiology | Dennis Hedderich |
| 14:15 – 15:00 | Applications of image segmentation (III): Pathology | Tingying Peng |