A weakly supervised method for surgical scene components detection with visual foundation model
This study introduced a novel weakly supervised method for detecting surgical components by integrating the surgical triplet recognition model with visual foundation model.
Authors
- Xiaoyan Zhang (ORCID: https://orcid.org/0000-0002-1815-5188)
- Jiquan Liu (ORCID: https://orcid.org/0000-0001-5994-6472)
- Yichen Zhu (ORCID: https://orcid.org/0000-0001-5126-838X)
- Huilong Duan (ORCID: https://orcid.org/0000-0003-3893-213X)
- Liming Wu (ORCID: https://orcid.org/0000-0002-5738-0468)
- Ziyu Zhou (ORCID: https://orcid.org/0009-0004-7251-9503)
- Jingyi Feng
- Qian Zhang (ORCID: https://orcid.org/0000-0001-5975-9781)
Institutions
- First Affiliated Hospital Zhejiang University (CN)
- Zhejiang University (CN)
Publication Details
- Journal
- PLoS ONE
- Published
- 2025-05-27
- DOI
- https://doi.org/10.1371/journal.pone.0322751
- Primary Topic
- Medical Image Segmentation Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Key Technologies Research and Development Program