A Discrete Chain Graph Model for 3d+t Cell Tracking with High Misdetection Robustness

Bernhard X. Kausler¹, Martin Schiegg¹, Bjoern Andres^{1, 2}, Martin Lindner¹, Ullrich Koethe¹, Heike Leitte¹, Jochen Wittbrodt³, Lars Hufnagel⁴, and Fred A. Hamprecht¹

¹HCI/IWR, Heidelberg University, Germany
fred.hamprecht@iwr.uni-heidelberg.de

²SEAS, Harvard University, United States

³COS, Heidelberg University, Germany

⁴European Molecular Biology Laboratory (EMBL), Heidelberg, Germany

Abstract. Tracking by assignment is well suited for tracking a varying number of divisible cells, but suffers from false positive detections. We reformulate tracking by assignment as a chain graph–a mixed directed-undirected probabilistic graphical model–and obtain a tracking simultaneously over all time steps from the maximum a-posteriori configuration. The model is evaluated on two challenging four-dimensional data sets from developmental biology. Compared to previous work, we obtain improved tracks due to an increased robustness against false positive detections and the incorporation of temporal domain knowledge.

Keywords: chain graph, graphical model, cell tracking

LNCS 7574, p. 144 ff.

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