Prof. Dr. Andreas Maier

Chair of Pattern Recognition

Our research interests focuses on medical imaging, image and audio processing, digital humanities, and interpretable machine learning and the use of known operators.

Research projects

  • Image Analysis and Fusion
  • Learning Algorithms for Medical Big Data Analysis (LAMBDA)
  • Magnetic Resonance Imaging (MRI)
  • Speech Processing and Understanding
  • Development of a guideline for the three-dimensional non-destructive acquisition of manuscripts
  • Intelligent MR Diagnosis of the Liver by Linking Model and Data-driven Processes (iDELIVER)
  • Molecular Assessment of Signatures ChAracterizing the Remission of Arthritis
  • Improved dual energy imaging using machine learning

Current projects

  • Self-Supervised Learning on Chest X-Rays to improve classification and localization

    (Non-FAU Project)

    Term: 1. March 2023 - 1. March 2026

    Chest X-Rays (CXR) serve as crucial diagnostic tools for pulmonary and cardiothoracic diseases, generating millions of images daily, a number on the rise due to decreasing acquisition costs. However, there's a pronounced scarcity of radiologists to interpret these images. Traditionally, CXR research has centered on enhancing classification accuracy, often achieving state-of-the-art results. Despite progress, there remain rare and intricate findings challenging for both human radiologists and AI systems to diagnose. Our investigation focuses on leveraging self-supervised image-text models to enhance the classification and localization of diverse findings. These self-supervised models eliminate the need for annotations, enabling the Deep Learning system to effectively learn from extensive public and private datasets.

Recent publications






Related Research Fields