Research focus

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