CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image
Segmentation
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image
Segmentation
Medical images often exhibit distribution shifts due to variations in imaging protocols and scanners across different medical centers. Domain Generalization (DG) methods aim to train models on source domains that can generalize to unseen target domains. Recently, the segment anything model (SAM) has demonstrated strong generalization capabilities due to its …