Quantitative image analysis methods are of prime importance to many projects of this SFB to make use of the acquired data. Central tasks are segmentation and tracking. Segmentation is required to identify biological structures in microscopy images, and tracking is needed to determine their movement, enabling analysis at the level of single instances rather than at the population level.
In the second funding period, advances in the field of artificial neural networks were exploited to develop first deep learning-based image analysis methods. The methods were applied in several cooperation projects with partners from this SFB. While the methods were shown to be a clear improvement over those of the first funding phase, the need of our SFB partners for quantitative analysis has grown; and new data with, for example, longer time courses revealed limitations of our earlier work on tracking.