Multiple cell tracking using ant estimator
Benlian Xu, Mingli Lu, Peiyi Zhu, Qinglan Chen, Xiaoying Wang · 2012
Quantitative analysis of cell dynamic processes through fluorescence microscopy imaging requires simultaneously tracking large and time-varying number of bright spots and its individual states in noisy image sequences. Such process is characterized as a challenging task due to several roadblocks including the severe image noise and clutter, the occlusion of one cell by others, and the weak image contrast. In this paper, we propose a novel ant stochastic searching behavior based tracking algorithm, which is called ANT estimator, to tracking multiple cells in fluorescence image sequences. In our ant system, each ant determines probabilistically potential state and then adjusts its mobility according to cell detection position heuristic information. Simulation results verify the effectiveness of our algorithm when applied to cell tracking cases, and its performance is also compared with the particle filter based cell tracking algorithm.