Segment Anything in Medical Images

arXiv:2304.12306v3 Announce Type: replace-cross
Abstract: Medical image segmentation is a critical component in clinical practice, facilitating accurate diagnosis, treatment planning, and disease monitoring. However, existing methods, often tailored to specific modalities or disease types, lack generalizability across the diverse spectrum of medical image segmentation tasks. Here we present MedSAM, a foundation model designed for bridging this gap by enabling universal medical image segmentation. The model is developed on a large-scale medical image dataset with 1,570,263 image-mask pairs, covering 10 imaging …

abstract arxiv clinical cs.cv diagnosis disease diverse eess.iv foundation foundation model however image images medical monitoring planning practice segment segment anything segmentation spectrum tasks treatment type types