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Motivation: Automated identification of cell cycle phases captured via fluorescent microscopy is very important for understanding cell cycle and for drug discovery. In this paper, we propose a novel cell detection method that utilizes both the intensity and shape information of the cell for better segmentation quality. In contrast to conventional off-line learning algorithms, an Online Support Vector Classifier (OSVC) is thus proposed, which removes support vectors from the old model anddoi:10.1093/bioinformatics/btm530 pmid:17989093 fatcat:kxfbzqyjvbadhgj4urkzzfmgtu