Automated visual-tracking systems of stem cell populations in vitro allow for high-throughput analysis of time-lapse phase-contrast microscopy. In these systems, detection of mitosis, or cell division, is critical to tracking performance as mitosis causes branching of the trajectory of a mother cell into the two trajectories of its daughter cells. Recently, one mitosis detection algorithm showed its success in detecting the time and location that two daughter cells first clearly appear as a result of mitosis. This detection result can therefore helps trajectories to correctly bifurcate and the relations between mother and daughter cells to be revealed. In this paper, we demonstrate that the functionality of this recent mitosis detection algorithm significantly improves state-of-the-art cell tracking systems through extensive experiments on 48 C2C12 myoblastic stem cell populations under four different conditions.
The results of mitosis detection are in turn used to improve cell tracking method REF .
Mitosis detection for stem cell tracking in phase-contrast microscopy images
2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro
2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro
Computer Science