Using Segment Anything Model 2 for Zero-Shot 3D Segmentation of Abdominal Organs in Computed Tomography Scans to Adapt Video Tracking Capabilities for 3D Medical Imaging: Algorithm Development and Validation
SAM 2 demonstrated promising zero-shot performance in segmenting certain abdominal organs in CT scans, particularly larger organs. Performance was significantly influenced by input negative prompts and initial slice selection, highlighting the importance of optimizing these factors.
Authors
- Yosuke Yamagishi (ORCID: https://orcid.org/0009-0006-7688-3075)
- Tomohiro Kikuchi (ORCID: https://orcid.org/0000-0002-4222-4569)
- Osamu Abe (ORCID: https://orcid.org/0000-0002-1180-2629)
- Soichiro Miki (ORCID: https://orcid.org/0000-0001-6365-6531)
- T. Yoshikawa (ORCID: https://orcid.org/0000-0002-1924-5468)
- Takahiro Nakao (ORCID: https://orcid.org/0000-0001-9498-7501)
- Shouhei Hanaoka (ORCID: https://orcid.org/0000-0002-7496-1651)
- Yukihiro Nomura (ORCID: https://orcid.org/0000-0001-6471-9936)
- Yuta Nakamura (ORCID: https://orcid.org/0000-0001-6962-6704)
Institutions
- Jichi Medical University (JP)
- Chiba University (JP)
- University of Tokyo Hospital (JP)
- The University of Tokyo (JP)
Publication Details
- Journal
- JMIR AI
- Published
- 2025-04-29
- DOI
- https://doi.org/10.2196/72109
- Citations
- 2
- Primary Topic
- Advanced X-ray and CT Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.35