אירועים והרצאות בפקולטה למדעי המחשב ע"ש הנרי ומרילין טאוב

In the talk I will present a novel framework for high-throughput cell lineage analysis in time-lapse microscopy images. The proposed algorithm ties together two fundamental aspects of cell lineage construction, namely cell segmentation and tracking, via a Bayesian inference of dynamic models. The proposed contribution exploits the Kalman inference problem by estimating the time-wise cell shape uncertainty in addition to cell trajectory. These inferred cell properties are combined with the observed image measurements within a fast marching (FM) algorithm, to achieve posterior probabilities for cell segmentation and association. An original idea for cell mitosis detection, which is not specific to a particular dataset and does not require training will also presented. Highly accurate results, with respect to the state-of-the-art, on different cell-tracking datasets were obtained.