  Deep learning has transformed the way large and complex image datasets can be
processed, reshaping what is possible in bioimage analysis. As the complexity
and size of bioimage data continues to grow, this new analysis paradigm is
becoming increasingly ubiquitous. In this Review, we begin by introducing the
concepts needed for beginners to understand deep learning. We then review how
deep learning has impacted bioimage analysis and explore the open-source
resources available to integrate it into a research project. Finally, we
discuss the future of deep learning applied to cell and developmental biology.
We analyse how state-of-the-art methodologies have the potential to transform
our understanding of biological systems through new image-based analysis and
modelling that integrate multimodal inputs in space and time.
