Segment anything model for medical image segmentation: Current applications and future directions

Yichi Zhang, Zhenrong Shen, Rushi Jiao

Abstract: Highlights•The Segment Anything Model (SAM) signifies a noteworthy expansion of prompt-driven paradigm to image segmentation, but the viability of its application to medical images is uncertain..•We provide a comprehensive survey of recent endeavors aimed at extending the efficacy of SAM to medical image segmentation tasks.•We explore potential avenues for future research directions in SAM’s role within medical image segmentation.•We maintain an active repository that contains an up-to-date paper list and a succinct summary of open-source projects.