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Institute for Imaging Science and Computational Modelling in Cardiovascular Medicine

In the early 19th century, the Berlin scientist Alexander von Humboldt (from Berlin) was one of the first researchers who had the leitmotiv to connect information with one another in order to generate knowledge. At our institute, we are pursuing this way of thinking, which has never been more important than at the times of digital transformation.

The Institute for Imaging Science and Computational Modelling in Cardiovascular Medicine is the innovation driver in the field of digital transformation in cardiac medicine in Berlin. The institute combines modern imaging methods with data science methods (AI, visual analysis, etc.) and biophysical modelling (hemodynamics, metabolism, etc.) to develop methods for diagnostics, therapy planning and decision support systems. The work is therefore always in a direct clinical context (bench-to-bedside) and unites interdisciplinary teams of physicians, mathematicians, computer scientists, physicists and engineers.

Our institute is divided into the following main research areas:

  • Imaging science & image guided therapy with a focus on quantification & visualization
  • Image processing with machine learning methods (e.g. segmentation for diagnostic applications)
  • Data science & machine intelligence (data driven models & complex data analytics, together with the DHZB group Medical Data Science and Machine Intelligence)
  • Simulations & modelling by physiology based models
  • Development & application of experimental methods for the validation of numerical models

Our goal is to achieve a holistic system view of a patient's disease status (systems medicine) and to better tailor therapies to the individual needs of a patient (precision medicine).

For this purpose, we work with medical data that represent different biological scales (organ, tissue, cell) and originate from various data sources (imaging, clinical information, omics).

In the clinic, our methods are used in a variety of applications ranging from prevention to model-based therapy planning. Our work is carried out with a direct clinical reference and close connection to the cardiovascular clinics of the Charité and the German Heart Center Berlin.

The German Heart Center Berlin is also a close partner of the Institute and makes important contributions in the form of endowed professorships and equipment.


The Berlin Institute for the Foundations of Learning and Data (BIFOLD) is also a close partner of the institute with joint projects in the area of AI, Data Science and Machine Learning.


Within the German Network of University Medicine (NUM), the ICM is involved in providing the image data management system.