AI RESEARCH
Automatic Segmentation of 3D CT scans with SAM2 using a zero-shot approach
arXiv CS.CV
•
ArXi:2603.23116v1 Announce Type: new Foundation models for image segmentation have shown strong generalization in natural images, yet their applicability to 3D medical imaging remains limited. In this work, we study the zero-shot use of Segment Anything Model 2 (SAM2) for automatic segmentation of volumetric CT data, without any fine-tuning or domain-specific