Automated segmentation of the primary tumor in nasopharyngeal carcinoma using a deep learning framework in positron emission tomography imaging: a comparative study
The PET-image-based automatic segmentation model for the primary tumor of NPC established in this study demonstrates the clinical potential of Nn-Unet in primary lesion of NPC segmentation tasks.
Authors
- JingXing Xiao (ORCID: https://orcid.org/0000-0002-0401-6101)
- Chengmao Guo
- X.-W. Liu (ORCID: https://orcid.org/0009-0001-2754-4345)
- Yongchu Pan (ORCID: https://orcid.org/0000-0002-6899-5994)
- Na Song (ORCID: https://orcid.org/0000-0002-0407-3309)
- H.Z. Li (ORCID: https://orcid.org/0009-0007-8463-1422)
- Ziyi Huang (ORCID: https://orcid.org/0000-0001-6985-0298)
- Jing Yang (ORCID: https://orcid.org/0000-0002-6389-1096)
- Dong Wang (ORCID: https://orcid.org/0000-0002-0421-655X)
- Meina Liang
Institutions
- Guangdong Medical College (CN)
Publication Details
- Journal
- Quantitative Imaging in Medicine and Surgery
- Published
- 2025-10-29
- DOI
- https://doi.org/10.21037/qims-2025-1090
- Primary Topic
- Head and Neck Cancer Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00