The successful treatment of infectious diseases requires interdisciplinary studies of all aspects of infection processes. The overarching combination of experimental research and theoretical analysis in a systems biology approach can unravel mechanisms of complex interactions between pathogens and the human immune system. Taking into account spatial information is especially important in the context of infection, since the migratory behavior and spatial interactions of cells are often decisive for the outcome of the immune response. Spatial information is provided by image and video data that are acquired in microscopy experiments and that are at the heart of an imagebased systems biology approach. This review demonstrates how image-based systems biology improves our understanding of infection processes. We discuss the three main steps of this approach-imaging, quantitative characterization, and modeling-and consider the application of these steps in the context of studying infection processes. After summarizing the most relevant microscopy and image analysis approaches, we discuss ways to quantify infection processes, and address a number of modeling techniques that exploit image-derived data to simulate host-pathogen interactions in silico. V C 2015 International Society for Advancement of Cytometry Key terms systems biology; image analysis; mathematical modeling; live-cell imaging; infection; host-pathogen interactions INFECTIOUS diseases still remain one of the main causes of death, especially in developing countries (1). To effectively treat infections, it is indispensable to understand how the pathogenic microorganisms interact with the host immune system. The mechanisms of these interactions can be extremely complex and also difficult to observe in experiment under physiological conditions. For example, if contacts between immune cells last longer than can be recorded in a typical microscopy study, this hinders a direct measurement of their duration and complicates interpretations (2). Computer simulations of immune processes can decrease the costs of systems biology studies by reducing the need for time-consuming experiments, expensive chemicals and animal testing. For instance, simulations by Beltman et al. (2,3) estimated the duration of contacts between T cells and dendritic cells, which are not accessible in laboratory experiments. Furthermore, the knowledge provided by dataderived computer models can direct further experimental studies. For example, the virtual infection model of a human whole blood assay by H€ unniger et al. (4) predicted the importance of extracellular killing of the pathogenic fungus Candida albicans by antimicrobial factors released from neutrophils during the first hour of infection, suggesting to study this mechanism in this particular time-frame. This iterative "experiment-modeling-experiment" cycle represents the central component of systems biology and aims to reveal the mechanisms of a biological process by quantifying the experimental data, building predictive com...