FCFDiff-Net: full-conditional feature diffusion embedded network for 3D brain tumor segmentation
The proposed FCFDiff-Net provides an efficient and robust solution for 3D BraTS, outperforming existing models in terms of accuracy and robustness. Future work will focus on exploring the model's generalization capabilities and conducting lightweight experiments to further enhance its applicability.
Authors
- Zhaozhao Xu (ORCID: https://orcid.org/0000-0002-7811-3799)
- Shuihua Wang (ORCID: https://orcid.org/0000-0003-2238-6808)
- Chaosheng Tang (ORCID: https://orcid.org/0000-0001-6923-855X)
- Xiaosheng Wu (ORCID: https://orcid.org/0000-0003-1688-9564)
- Yudong Zhang (ORCID: https://orcid.org/0000-0002-4870-1493)
- Junding Sun (ORCID: https://orcid.org/0000-0001-7349-0248)
- Qingyi Hou (ORCID: https://orcid.org/0009-0009-6198-5118)
Institutions
- University of Leicester (GB)
- King Abdulaziz University (SA)
- Henan Polytechnic University (CN)
- Xi’an Jiaotong-Liverpool University (CN)
Publication Details
- Journal
- Quantitative Imaging in Medicine and Surgery
- Published
- 2025-04-30
- DOI
- https://doi.org/10.21037/qims-24-2300
- Citations
- 2
- Primary Topic
- Brain Tumor Detection and Classification
- Type
- article
- Field-Weighted Citation Impact
- 1.68