||With the technological developments in microscopy, it is much easier to acquire live cell images. However, the amount of data gathered cannot be analysed using traditional manual tracking methods, since it is time consuming and it is possible for an investigator make mistakes. It is clear that analysing cell images should be automated. Like manual tracking, automated tracking is not perfect either, even if some sophisticated machine learning methods are used. To make an analysis more efficient, the calculation speed of a computer and the reasoning ability of a human should be used.
The aim of the project is to achieve this by implementing a user-friendly software tool which controls manual feedbacks and train the system by optimizing parameters for tracking of cell movements.