Objective To conduct a systematic and comprehensive bibliometric analysis related to medical imaging in coronavirus disease 2019 (COVID-19) published by Chinese authors, and indicate the current status and guidance for coping with the challenges brought by long COVID. Methods Literature records pertaining to COVID-19 imaging were retrieved from the Web of Science (WOS) and Chinese Science Citation Database (CSCD) with a date range of January 1st, 2020 to December 31st, 2022. CiteSpace was used to analyze the popular topics and generate a visual map to further refine research trends. Results The search enrolled 2229 publications (1771 publications from WOS and 458 from CSCD). The monthly volume of publications showed a significant increase followed by a gradual decline, and then maintained a stable level. Clustering analysis of keywords and co-citations revealed that the research hotspots in COVID-19 imaging were clinical features, imaging differential diagnosis, and the application of artificial intelligence. Keyword burst analysis showed that “deep learning” was the most intensive keyword, while “attention mechanism” had the longest burst duration. Conclusions In recent years, the research in the field of COVID-19 imaging has made steady progress. Artificial intelligence has received the most attention. Clinical features, imaging features and artificial intelligence assisted diagnosis are the top of most concerns. The future focus of COVID-19 imaging research may be on improving algorithm models to expand the application of artificial intelligence in disease diagnosis, treatment, and management.