Abstract: Powered by large-scale pre-training, the Segment Anything Model (SAM) proposed by Meta AI Research has made significant progress in image segmentation and gained popularity in the field of computer vision. With a growing number of foundation models developed, Parameter-Efficient Fine-Tuning（PEFT）is increasingly exploited as a valuable approach for knowledge transfer from pre-trained foundation models to specific domain tasks. In this talk, we will give an introduction about SAM and PEFT, and then further focus on their applications in medical image analysis.