Tracking immune cells in time-lapse microscopy

Tracking immune cells in time-lapse microscopy

Research area
Internal groups
High Performance Methods for Numerical Simulation in Science, Medicine and Engineering
Recent advances in imaging methods have allowed to observe the complex network of interactions between immune cells in vivo, giving rise to new methods for unraveling the mechanisms of the immune system.
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.
Tracking and reconstruction of a Neutrophil (blue) approaching a Dendritic Cell (green).
This is an interdisciplinary project funded by developed as a joint collaboration between the Institute of Computational Science (ICS) and the Institute for Research in Biomedicine (IRB) - Universit√† della Svizzera Italiana.

Prof. Dr. Rolf Krause; PI; ICS Institute of Computational Science

Prof. Dr. Marcus Thelen

Researcher Santiago Fernandez Gonzalez




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