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Division of Intelligent Medical Systems

Prof. Dr. Lena Maier-Hein

© dkfz.de

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.

Research
Team Philosophy

Contact

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
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