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AI-enabled cardiac MRI

Kolloquium der Abteilung 8

Artificial intelligence, in particular from the class of machine / deep learning, has shown great promise for applications in medical imaging. However, the success of AI-based techniques is limited by the availability and quality of the training data. A common approach is to train methods on well annotated and curated databases of high-quality image acquisitions, which then may fail on real patient cases in a hospital setting. Another problematic is the lack of sufficient numbers of clinical label annotations in the training data, or example for early markers of disease. In this talk I will present some of our recent approaches in cardiac magnetic resonance imaging (CMR) that aim to address some of these challenges, by using AI as an enabling technique for improved CMR image reconstruction, realistic CMR augmentation and further downstream tasks.