In this paper we propose a workflow to detect and track mitotic cells intime-lapse microscopy image sequences. In order to avoid the requirement forcell lines expressing fluorescent markers and the associated phototoxicity,phase contrast microscopy is often preferred over fluorescence microscopy inlive-cell imaging. However, common specific image characteristics complicateimage processing and impede use of standard methods. Nevertheless, automatedanalysis is desirable due to manual analysis being subjective, biased andextremely time-consuming for large data sets. Here, we present the followingworkflow based on mathematical imaging methods. In the first step, mitosisdetection is performed by means of the circular Hough transform. The obtainedcircular contour subsequently serves as an initialisation for the trackingalgorithm based on variational methods. It is sub-divided into two parts: inorder to determine the beginning of the whole mitosis cycle, a backwardstracking procedure is performed. After that, the cell is tracked forwards intime until the end of mitosis. As a result, the average of mitosis duration andratios of different cell fates (cell death, no division, division into two ormore daughter cells) can be measured and statistics on cell morphologies can beobtained. All of the tools are featured in the user-friendlyMATLAB$^{\circledR}$ Graphical User Interface MitosisAnalyser.
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