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 | |
| Risse, Benjamin |
| Kiefer, Friedemann | |
| Risse, Benjamin |
Duration: 01/01/2025 - 31/12/2028 | 2nd Funding period Funded by: DFG - Collaborative Research Centre Type of project: Subproject in DFG-joint project hosted at University of Münster |
Duration: 01/01/2021 - 31/12/2024 | 1st Funding period Funded by: DFG - Collaborative Research Centre Type of project: Main DFG-project hosted at University of Münster |