Innovative Medical Imaging and Image Analysis Pooling competencies – enhanced cooperation in research – improved diagnostics and care

MIB – Medical Imaging Center Bonn

What is the MIB?
The MIB is a center of excellence where medical imaging activities and expertise from different disciplines come together. 

What is the mission of the MIB?
To foster interdisciplinary networking. To advance best practices.

What is unique about the MIB?
Broad networking between research and industry. Platform for direct exchange among experts.

The Medical Imaging Center Bonn (MIB) is a competence center in which all imaging activities at the Bonn site, in clinical and basic sciences as well as other research institutions and networks, are bundled in order to improve interdisciplinary networking within existing structures. In addition, networking with external partners from science and industry will be further expanded. The MIB covers the entire range of imaging techniques and resolution levels along the translational chain from clinical and experimental imaging to optical methods and molecular imaging. 

Moreover, innovative methods of image analysis using artificial intelligence and machine learning are of eminent importance and are represented by several excellent research groups within the MIB.

We are convinced that we can achieve more scientific results in the shortest possible time in the future by providing a platform for researchers that shortens communication paths between disciplines, strengthens collaborations and bundles competencies.


Second MIB expert talk on March 14th, starting at 4pm (CET)

Speaker: Professor Shadi Albarqouni, Clinic for Radiology, University Hospital Bonn.
Title: The Next Generation of AI in Medicine —Towards Deep Federated Learning in Healthcare

After a 30-minute talk, the presentation will be followed by an open discussion.

Please register here
After registration, you will receive the login data for Zoom.

Deep Learning (DL) has emerged as a leading technology in computer science for accomplishing many challenging tasks. This technology shows an outstanding performance in a broad range of computer vision and medical applications. However, this success comes at the cost of collecting and processing a massive amount of data, which are in healthcare often inaccessible due to privacy issues. Federated Learning is a new technology that allows training DL models without sharing the data. Using Federated Learning, DL models at local hospitals share only the trained parameters with a centralized DL model, which is, in return, responsible for updating the local DL models as well. Yet, a couple of well-known challenges in the medical imaging community, e.g., heterogeneity, domain shift, scarcity of labeled data, and multi-modal data, might hinder the utilization of Federated Learning. In this talk, a brief introduction about the clinical workflow and the common challenges for AI in Medicine will be presented before diving into the federated learning topic, its challenges, and potential solutions.

Research Groups of the MIB

Steering Committee of the MIB

The project is supported by the steering committee, which is made up of experts from various disciplines.

The founding of the MIB Medical Imaging Center Bonn was initiated by Prof. Dr. med. Frank G. Holz, director of the University Eye Hospital Bonn.