Cell tracking for automated analysis of timelapse microscopy
This document presents an algorithm to automatically perform two dimensional tracking of cells in in-vitro cultures. The developed software handles all the necessary data processing, from preprocessing the images to automaticallytracking the cells and it also provides an interface to manually correct the obtained cell trajectories and functions to analyze the data. The system is developed for, and tested on, muscle stem cells (MuSCs) but it can also be applied to other cell types that look and behave similarly. The software was used in a bio-medical study to investigate the effects on mouse MuSC fate caused by culturing the cells on substrates of different rigidities. In this study the software enabled important findings about cell behavior. The software is capable of handling automatic track initialization, false detections, adhering cells, death and cell division. These are functionalities that can all be problematic to achieve. Cell tracking is normally done manually, which is very labor intensive and limits the parameters that can be analyzed. Having reliable systems to analyze a wide range of cell types automatically would therefore greatly benefit research in cell biology. The software package described here was named the Baxter Algorithm after the Donald E. & Delia B. Baxter Foundation that funded it’s development.
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