Cookies on this website
We use cookies to ensure that we give you the best experience on our website. If you click 'Continue' we'll assume that you are happy to receive all cookies and you won't see this message again. Click 'Find out more' for information on how to change your cookie settings.

Advances in optical microscopy, biosensors and cell culturing technologies have transformed live cell imaging. Thanks to these advances live cell imaging plays an increasingly important role in basic biology research as well as at all stages of drug development. Image analysis methods are needed to extract quantitative information from these vast and complex data sets. The aim of this review is to provide an overview of available image analysis methods for live cell imaging, in particular required preprocessing image segmentation, cell tracking and data visualisation methods. The potential opportunities recent advances in machine learning, especially deep learning, and computer vision provide are being discussed. This review includes overview of the different available software packages and toolkits.

Original publication




Journal article



Publication Date





65 - 79


Biological image analysis, Cell segmentation, Cell tracking, Live cell imaging, Machine learning, Quantitative biological imaging, Animals, Biosensing Techniques, Cell Culture Techniques, Cell Tracking, Eukaryotic Cells, Humans, Image Processing, Computer-Assisted, Machine Learning, Microscopy, Molecular Imaging, Signal-To-Noise Ratio, Software