A Bibliometric Analysis of Segment Anything (SA) Research: Global Trends, Key Contributors, and Thematic Insights

Abstract

This bibliometric analysis provides a comprehensive overview of the research landscape surrounding "Segment Anything (SA)" technology, drawing on 704 documents from the Scopus database between 2020 and 2025. The study reveals a significant surge in scientific production, with publications peaking in 2024, marking it as a critical year for the field's growth. Lecture Notes in Computer Science emerged as the leading publication source, underscoring the foundational role of computer science in SA research, while high publication counts in Remote Sensing and IEEE Transactions on Geoscience and Remote Sensing demonstrate the technology's interdisciplinary applications. Key contributors include a concentrated group of prolific authors, led by Zhang Y and Li Y, who significantly shape the field’s development.

Geographically, Chinese institutions dominate research output, particularly Wuhan University, Tsinghua University, and the University of Chinese Academy of Sciences, establishing China as a central research hub. The analysis also highlights the influence of Canada and Brazil, where fewer yet highly impactful publications underscore the field's global relevance. Major thematic focuses, such as "image segmentation," "deep learning," and "medical imaging," indicate the field’s blend of foundational AI advancements and practical applications, especially in healthcare. Overall, this analysis showcases a dynamic and expanding research domain, driven by international collaborations and diverse interdisciplinary applications, setting the stage for further developments in SA technology.