Development of novel computational methods

Image Analysis – Deep MI Lab
Deutsches Zentrum für Neurodegenerative Erkrankungen
Prof. Dr. rer. nat. Martin Reuter

The research focus of the DeepMI lab is on the development of a novel deep-learning (CNNs) and machine-learning methods for the automated analysis of medical images, such as human brain MRI. In addition to medical image computing and computational neuroimaging, our research interests include computational geometry and topology, computer vision, and statistical modeling.

Our network within DZNE and the University Clinic Bonn, as well as our close ties to the Harvard Medical School via faculty appointments of Prof. Reuter in Radiology and in Neurology promote our interdisciplinary research and foster deep international collaborations.


Geometry-based analysis of hippocampal thickness, sheet representation of the hippocampal body, and intrinsic reference system for the localization of effects. © Martin Reuter


  • Deep-learning and machine-learning methods
  • Automated analysis, segmentation, classification, diagnosis and prognosis of medical images
  • Computational neuroimaging and medical image analysis
  • Computational geometry and topology
  • Statistical modeling