Ocular fundus imaging technology has developed rapidly in the past decade. The exsiting imaging technology is constantly updated and new imaging technology emerges one after another. The related research and development investment, equipment usage and paper publication are all growing rapidly. At the same time, it is developing towards the direction of multi-technology combination, integration of artificial intelligence and big data, as well as small-size and automation use of equipment. However, there are many challenges behind the prosperity of ocular fundus imaging, such as professionally remodeling of fundus diseases knowledge system standardization, balance and independence of scholarly communication, misunderstanding of "multimodal images", validation of the effectiveness and applicability of emerging technologies, clinical imaging research innovation, original technology innovation and technology reserve, fundus imaging data integration and analysis system for the future.