An Investigation of Segment Anything Model (SAM) on Uterus Segmentation.

Highly development of language-image models makes prompt-driven accurate segmentation become possible. Segment Anything Model (SAM) has recently made a breakthrough in zero-shot image segmentation, using an unprecedentedly large dataset to train a segmentation model with strong adaptability. In this paper, we investigate the capability of SAM for MRI medical images in uterus Segmentation. Experimental results that YOLOv8 with SAM implements end-to-end uterus segmentation and outperforms the traditional supervised learning U-net and U-net++ models.