Radiomics‐guided generative adversarial network for automatic primary target volume segmentation for nasopharyngeal carcinoma using computed tomography images
Integrating radiomics features into GAN is promising to solve unclear border limitations and increase the delineation accuracy of GTVp for patients with NPC.
Authors
- Xiance Jin (ORCID: https://orcid.org/0000-0002-4117-5953)
- Mingrou Guo
- Xuanxuan Zhu (ORCID: https://orcid.org/0009-0000-3056-1894)
- Heng Li (ORCID: https://orcid.org/0000-0003-2166-4116)
- Wenlong Li (ORCID: https://orcid.org/0000-0002-5351-7076)
- Ziqing Xiang
- Jicheng Zhang
- Xianwen Yu
- Jiayi Xu (ORCID: https://orcid.org/0000-0002-9868-2913)
- Juebin Jin (ORCID: https://orcid.org/0000-0002-5703-6296)
- Zeshuo Zhao
Institutions
- Wenzhou Medical University (CN)
Publication Details
- Journal
- Medical Physics
- Published
- 2024-11-13
- DOI
- https://doi.org/10.1002/mp.17493
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Wenzhou Municipal Science and Technology Bureau