However, state-of- the-art imaging software for the analysis of microscopy acquisitions makes use of generic segmentation and tracking algorithms which can be poorly applied for leukocytes whose interaction involves high cytoskeleton remodeling, migration and repeated contacts with other cells.
In this interdisciplinary project, we propose a method that allows to extract biomedical relevant knowledge from microscopy movies by intrinsically identifying and tracking cells in space-time connected data using an inverse problem framework.
In addition, for a quantitative validation of tracking algorithms and to support knowledge sharing, an online leukocyte tracking database has been set up.
Prof. Dr. Rolf Krause; PI; ICS Institute of Computational Science
Prof. Dr. Marcus Thelen
Researcher Santiago Fernandez Gonzalez