Computer Assisted Medical Interventions

Division of Computer Assisted Medical Interventions

Prof. Dr. Lena Maier-Hein


The mission of the Div. Computer Assisted Medical Interventions is to improve the quality of interventional healthcare in a data-driven manner. To this end, our multidisciplinary group builds upon principles and knowledge from a diversity of research fields including artificial intelligence (AI), statistics, computer vision, biophotonics and medicine. Committed to the ultimate goal of creating benefit for patients and medical staff, we aim to develop a holistic concept spanning the three significant topics perception, data interpretation and real-time assistance and connecting them through a cycle of continuous learning: Novel spectral imaging techniques enabled by deep learning are being developed as safe, reliable and real-time imaging modalities during interventions. When interpreting the perceived data in the context of available knowledge, our division specifically addresses common roadblocks to clinical translation such as data sparsity, explainability and uncertainty handling. In close collaboration with clinical partners, these methods are leveraged for the development of context-aware interventional assistance systems. Finally, we place a strong focus on the reliable validation of AI algorithms for clinical purposes.


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

Selected Publications

  • Groehl J, Kircher, T, Adler, TJ, Hacker, L, Holzwarth, N, Hernándet-Aguilera, A, Herrera, MA, Santos, E, Bohndiek, SE, Maier-Hein L. Learned spectral decoloring enables photoacoustic oximetry. Nature Scientific Reports. 2021 11(6565).
  • Maier-Hein, L, Eisenmann, M, Reinke, A, Onogur, S, Stankovic, M, Scholz, P, Arbel, T, Bogunovic, H, Bradley, AP, Carass, A, Feldmann, C, Frangi, AF, Full, PM, van Ginneken, B, Hanbury, A, Honauer, K, Kozubek, M, Landman, BA, März, K, ... Kopp-Schneider, A. Why rankings of biomedical image analysis competitions should be interpreted with care. Nature Communications. 2018; 9(1):5217.
  • Wirkert, SJ, Vemuri, AS, Kenngott, HG, Moccia, S, Götz, M, Mayer, BFB, Maier-Hein, KH, Elson, DS, Maier-Hein, L. Physiological Parameter Estimation from Multispectral Images Unleashed. Medical Image Computing and Computer Assisted Intervention. 2017; LNCS 10435:134–141.
  • Maier-Hein, L, Vedula, SS, Speidel, S, Navab, N, Kikinis, R, Park, A, Eisenmann, M, Feussner, H, Forestier, G, Giannarou, S, ... Jannin, P. Surgical data science for next-generation interventions. Nature Biomedical Engineering, 2017; 1(9):691-696.
to top
powered by webEdition CMS