The aim of this project is to generate new hypoxia reporters and reporter mice based on the oxygen-independent fluorescent protein UnaG, as well as metabolic reporters, which will be functionally tested and applied in preclinical models of myocardial infarction, kidney ischemia and intestinal infection. Using probabilistic machine learning on the imaging data generated, we will attempt to quantitatively analyse tissue hypoxia across multiple imaging scales with a particular focus on the explainability of our deep learning models to ensure trustworthy predictions.
Kiefer, Friedemann | European Institute of Molecular Imaging (EIMI) |
Risse, Benjamin | Junior professorship for practical computer science (Prof. Risse) Professorship of Geoinformatics for Sustainable Development (Prof. Risse) |
Kiefer, Friedemann | European Institute of Molecular Imaging (EIMI) |
Risse, Benjamin | Junior professorship for practical computer science (Prof. Risse) Professorship of Geoinformatics for Sustainable Development (Prof. Risse) |