Automated tracking of migrating cells in phase-contrast video microscopy sequences using image registration

Analysis of in vitro cell motility is a useful tool for assessing cellular response to a range of factors. However, the majority of cell-tracking systems available are designed primarily for use with fluorescently labelled images. In this paper, five commonly used tracking systems are examined for their performance compared with the use of a novel in-house cell-tracking system based on the principles of image registration and optical flow. Image registration is a tool commonly used in medical imaging to correct for the effects of patient motion during imaging procedures and works well on low-contrast images, such as those found in bright-field and phase-contrast microscopy. The five cell-tracking systems examined were Retrac, a manual tracking system used as the gold standard; CellTrack, a recently released freely downloadable software system that uses a combination of tracking methods; ImageJ, which is a freely available piece of software with a plug-in for automated tracking (MTrack2) and Imaris and Volocity, both commercially available automated tracking systems. All systems were used to track migration of human epithelial cells over ten frames of a phase-contrast time-lapse microscopy sequence. This showed that the in-house image-registration system was the most effective of those tested when tracking non-dividing epithelial cells in low-contrast images, with a successful tracking rate of 95%. The performance of the tracking systems was also evaluated by tracking fluorescently labelled epithelial cells imaged with both phase-contrast and confocal microscopy techniques. The results showed that using fluorescence microscopy instead of phase contrast does improve the tracking efficiency for each of the tested systems. For the in-house software, this improvement was relatively small (<5% difference in tracking success rate), whereas much greater improvements in performance were seen when using fluorescence microscopy with Volocity and ImageJ.