Tumor Image Segmentation: A Bibliometric Analysis from 2003 to 2024

Within the last 20 years, the number of articles on the application of tumor image segmentation has increased steadily. From U-Net to MAMBA, many methods for tumor image segmentation have been proposed, and the limitations of models and algorithms are becoming increasingly smaller, which demonstrates the importance of advances in tumor image segmentation technology for disease prevention and monitoring. It presents a strong connection between countries/regions and authors, which reflects the global interest and support for the development of this field. This study shows global trends, research hotspots, and emerging topics in this field and reviews some of the knowledge about tumor image segmentation applications from past studies. And it will provide good research guidelines for researchers in this field.