The group’s research focuses mainly on:

• Development of robust, generalizable neural networks (CNNs, Deep Learning)
• Data-/Annotation-efficient models based on Semi-/Self-Supervised Learning (SSL)
• Outlier-detection and imputation of incomplete data records
• Reconstruction of image and video data. e.g., by means of super-resolution
• Segmentation problems, particularly MRI Brain Segmentation
• Quantification of uncertainties in classification problems
• Development of interpretable features to improve user-/patient-communication
• Evaluation of algorithm performance and quantification of data-biases
• Translation of research results into industry and medical workflows
• Quantification of human anatomy based on image data (MRI, X-ray, CT) in the context of diseases such as dementia, tumor and traumas