Cookie Settings

We use cookies to optimize our website. These include cookies that are necessary for the operation of the site, as well as those that are only used for anonymous statistic. You can decide for yourself which categories you want to allow. Further information can be found in our data privacy protection .


These cookies are necessary to run the core functionalities of this website and cannot be disabled.

Name Webedition CMS
Purpose This cookie is required by the CMS (Content Management System) Webedition for the system to function correctly. Typically, this cookie is deleted when the browser is closed.
Name econda
Purpose Session cookie emos_jcsid for the web analysis software econda. This runs in the “anonymized measurement” mode. There is no personal reference. As soon as the user leaves the site, tracking is ended and all data in the browser are automatically deleted.

These cookies help us understand how visitors interact with our website by collecting and analyzing information anonymously. Depending on the tool, one or more cookies are set by the provider.

Name econda
Purpose Statistics
External media

Content from external media platforms is blocked by default. If cookies from external media are accepted, access to this content no longer requires manual consent.

Name YouTube
Purpose Show YouTube content
Name Twitter
Purpose activate Twitter Feeds

Division of Intelligent Medical Systems

Prof. Dr. Lena Maier-Hein


Artificial intelligence (AI) is set to revolutionize various areas of everyday life. In healthcare, however, its integration into routine procedures and impact on patients are still limited. The mission of the Division of Intelligent Medical Systems is to tackle the unique challenges of medical imaging AI to generate lasting patient benefit. A particular focus of our research lies in the surgical application domain. Currently, patient outcome is heavily influenced by the surgical team's experience, with many potential complications being avoidable. To address such major socioeconomic problems and consistently elevate patient outcome beyond current standards, our multidisciplinary team works on intelligent medical systems in close collaboration with clinicians. Specific goals lie in the development of novel AI-enabled imaging techniques and trustworthy surgical AI systems that are ready for real-world clinical application. Key methodological challenges are related to the generalization of AI methods across devices, patient populations and hospitals, high data variability in an inherently sparse data regime, multimodal data integration, incorporation of prior knowledge into models, and the meaningful validation of AI systems under real-world clinical conditions.

Team Philosophy


Prof. Dr. Lena Maier-Hein
Intelligent Medical Systems (E130)
Deutsches Krebsforschungszentrum
Im Neuenheimer Feld 223
69120 Heidelberg
Tel: +49 6221 42 2354

Selected Publications

  • Maier-Hein L / Reinke A, et al. Metrics reloaded: Recommendations for image analysis validation. Nature Methods 21, 2024
  • Ayala L / Adler T, et al., Spectral imaging enables contrast agent-free real-time ischemia monitoring in laparoscopic surgery. Science Advances 9(10), 2023
  • Maier-Hein L, et al. Surgical data science - from concepts toward clinical translation. Medical Image Analysis 76:102306, 2022
  • Ardizzone L, et al. Analyzing inverse problems with invertible neural networks. International Conference on Learning Representations (ICLR) 2019
to top
powered by webEdition CMS