Gross-tumor-volume segment-anything model for medical 2D images integrating gross tumor volume-minimal feature integration technology for lung cancer segmentation
By coupling SAM-Med2D with GTV-MFIT and GAN training, GTV-SAMGAN substantially improves lung cancer GTV segmentation, particularly for small and heterogeneous tumors, thereby enhancing the precision and efficiency of radiotherapy planning.
Authors
- Huaiwen Zhang (ORCID: https://orcid.org/0000-0002-3183-9218)
- Qiliang Xiong
- Shuhang Cao
- Chen Yi
- Yuxin Li
- Shaofeng Jiang
Institutions
- Jiangxi Provincial Cancer Hospital (CN)
Publication Details
- Journal
- Quantitative Imaging in Medicine and Surgery
- Published
- 2025-12-22
- DOI
- https://doi.org/10.21037/qims-2025-370
- Primary Topic
- Lung Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00