Interactive and computational analysis of large multiscale imaging data

Principal investigators: Xiaoyi Jiang, Lars Linsen
Project number: CRC 1450 Z01
Project term: 01/2021–12/2028

Within the multiscale imaging strategy of this CRC, the acquired data is large, time-varying, multimodal, multiscale, and represents cohorts. The analysis of such highly complex data requires basic research in image analysis, machine learning, and visualisation. Machine learning will be the key methodological backbone to uncover inherent relationships between patterns at multiple scales. A user-centric analysis of extracted information will be provided based on an interactive visual approach. This project will deliver generally applicable, effective, and efficient methods and tools for multiscale data analysis useful for answering important biomedical questions of this CRC and beyond.

Blood vessels in the kidney tissue of a mouse. This abstract visualisation is based on images of a tissue sample taken using lightsheet fluorescence microscopy and was generated using 3D image processing techniques. These techniques were developed as part of our project to handle large high-resolution datasets in a way that enabels a simultaneously coarse and fine-scale analysis of vessel structures and quantitative comparison between multiple datasets. Here, the vessel tree volume was segmented before extracting the topology and specific vessel properties. The light blue spheres mark the ends and branch points of the blood vessels. A colour scale visualizes the different diameters of the vessels.
© Dominik Drees/Xiaoyi Jiang's research group, microscopy data by Nils Kirschnick/Friedemann Kiefer's research group

Team

Principal investigators

Project members

Publications

The names of the principal investigators in our network have been bolded. Publications released prior to 2021, when funding for our network commenced, represent previous project-related work.