Hoehme – Image analysis and multiscale tissue modeling


Research interests

Our research is part of the search for understanding of the integrated physiological function of the human body in terms of structure and function of tissues, cells and proteins. Currently, we are focussing on two main objectives:

  • Technological advancement (novel algorithms, advanced programming and parallelization techniques etc.) for image processing and analysis, and 3D tissue modelling.
  • Automatization and standardization of creation of individual-cell-based spatio-temporal multi-scale models for biological tissues directly from experimental image modalities.
  • Application of these tissue models to elucidate the mechanisms behind liver regeneration after intoxication and partial liver resection in different species to better understand liver failure in human.


  • French National Institute for Research in Computer Science and Control (INRIA) in Paris, France >>>
  • Leibniz Research Centre for Working Environment and Human Factors (IfaDo) in Dortmund, Germany >>>
  • Helmholtz German Cancer Research Center (DKFZ) in Heidelberg, Germany >>>
  • Auckland Bioengineering Institute (ABI) in Auckland, New Zealand >>>
  • University College (UCL) in London, United Kingdom >>>
  • Chalmers University of Technology in Gothenburg, Sweden >>>
  • Molecular hepatology, University Hospital Mannheim, University of Heidelberg in Mannheim, Germany >>>
  • Fraunhofer Institute for Medical Image Computing (MEVIS) in Bremen,Germany >>>
  • Institute for Biochemistry, Medical Faculty, University of Leipzig >>>
  • Image and Signal Processing Group at the Department of Computer Science (IfI) University of Leipzig >>>
  • Bioinformatics Group at the Department of Computer Science, University of Leipzig >>>

follow our group here: https://hoehmelab.izbi.uni-leipzig.de/



2017 (1)

  • S. Hoehme, A. Friebel, S. Hammad, D. Drasdo, J. G. Hengstler. Creation of Three-Dimensional Liver Tissue Models from Experimental Images for Systems Medicine. Methods Mol Biol. 2017. 1506: 319-362.

2016 (1)

  • A. Ghallab, G. Celliere, S. G. Henkel, D. Driesch, S. Hoehme, U. Hofmann, S. Zellmer, P. Godoy, A. Sachinidis, M. Blaszkewicz, R. Reif, R. Marchan, L. Kuepfer, D. Haussinger, D. Drasdo, R. Gebhardt, J. G. Hengstler. Model-guided identification of a therapeutic strategy to reduce hyperammonemia in liver diseases. J Hepatol. 2016. 64: 860-71.