![]() Although automatization is integrated in most modern microscopy systems on the market, the number of people who make the most out of their equipment seems to be moderate. A higher amount of difficult data, however, connotes a greater effort in analysis. The growing amount of fluorochromes, monoclonal antibodies, and organelle-specific dyes allows for investigation of complicated matter in multidimensional images. Automatization in research, especially with liquid handling robots, in cell culture and microscopy has enabled us to analyze larger samples in a shorter period of time, while data tend to be more and more complex. The first approaches of semiautomatic image analysis track back to the 1980s, but only the digital age, with cheap data storage and advanced computation, opened up new opportunities. Because of limitations in immunocytochemistry in our specific setup, we developed a semiautomatic approach to examine the interaction of lipid-laden MPs with VSMCs under hypoxic conditions based on nuclei morphology by high-content analysis using the open-source software CellProfiler ( We provide evidence that, in comparison with fully automatic analysis, a low threshold within the analysis workflow and subsequent manual control save time, while providing more objective and reliable results. ![]() Through exemplary use of a coculture of vascular smooth muscle cells (VSMCs) and macrophages (MPs), we demonstrate how rare interactions within this highly variable sample type can be analyzed. As there is no perfect method for image segmentation and fully automatic image analysis of complex content, we aimed to succeed by identification of unique and reliable features within the sample. ![]() Simple segmentation algorithms of biological imagery are nowadays widely spread in biomedical research, but processing of complex sample structures, for example, variable sample compositions, cell shapes, and sizes, and rare events remains a difficult task. Automatization in microscopy, cell culture, and the ease of digital imagery allow obtainment of more information from single samples and upscaling of image-based analysis to high-content approaches.
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