3D segmentation of uterine fibroids based on deep supervision and an attention gate
This shows that our proposed method can improve the automatic segmentation accuracy of magnetic resonance image (MRI) data of uterine fibroids to a certain extent.
Authors
- Chengwei Li (ORCID: https://orcid.org/0000-0002-5883-4812)
- Zhi‐Wei Liu (ORCID: https://orcid.org/0000-0003-3005-1792)
- Chuen–Tsai Sun (ORCID: https://orcid.org/0000-0002-4757-9131)
- Fajin Lv (ORCID: https://orcid.org/0000-0002-8431-0350)
Institutions
- Ganzhou People's Hospital (CN)
- The Affiliated Yongchuan Hospital of Chongqing Medical University (CN)
- Chongqing Medical University (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2025-03-13
- DOI
- https://doi.org/10.3389/fonc.2025.1522399
- Citations
- 5
- Primary Topic
- Uterine Myomas and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 10.29