New imaging techniques enable visualizing and analyzing a multitude of unknown phenomena in many areas of science at high
spatio-temporal resolution. The rapidly growing amount of image data, however, can hardly be analyzed manually and, thus,
future research has to focus on automated image analysis methods that allow one to reliably extract the desired
information from large-scale multidimensional image data. Starting with infrastructural challenges, we present new
software tools, validation benchmarks and processing strategies that help coping with large-scale image data. The
presented methods are illustrated on typical problems observed in developmental biology that can be answered, e.g., by
using time-resolved 3D microscopy images.