F. Bunyak, K. Palaniappan, S. K. Nath, T. I. Baskin, and G. Dong

IEEE Int. Symposium on Biomedical Imaging (ISBI), pgs. 1040--1043, 2006

cell detection, cell segmentation, active contours, cell tracking, biomedical

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Abstract

Quantifying the behavior of cells individually, and in clus- ters as part of a population, under a range of experimental conditions, is a challenging computational task with many bi- ological applications. We propose a versatile algorithm for segmentation and tracking of multiple motile epithelial cells during wound healing using time-lapse video. The segmen- tation part of the proposed method relies on a level set-based active contour algorithm that robustly handles a large num- ber of cells. The tracking part relies on a detection-based multiple-object tracking method with delayed decision en- abled by multi-hypothesis testing. The combined method is robust to complex cell behavior including division and apop- tosis, and to imaging artifacts such as illumination changes.