Particle-Cell Detecting and Tracking in Live-Cell Time-Lapse Images

摘要

Live-cell time-lapse images generated by biological experiments are useful for observing activities, even for proposing novel hypotheses. By identifying particles and cells as objects from live-cell time-lapse images and then tracking the pathways of particles (or cells) to calculate the measures between the particles and cells, such as the distances, they can be quantized for the relationship of particles and cells. Various tools of particle or cell tracking have been proposed. However, there is no famous tool has been proposed to achieve the above goals. Hence, in order to accomplish the purposes, a particle-cell relation mining method, abbreviate to PCRM, has been proposed here. In the PCRM method, there are four phases: object identification, objects tracking, measures calculation, and relation mining. By using the PCRM method, the relationship between particles and cells has tried to be found in this paper, and the PCRM method is useful for biologists to prove their hypotheses.