CBCT-IDDNet: a three-dimensional Res-UNet based image domain denoising network for clinical dose cone-beam computed tomography—winner of the International Conference on Acoustics, Speech, and Signal Processing-2024 challenge
The proposed CBCT-IDDNet model improves CBCT image quality by effectively reducing noise, making it a valuable tool for clinical applications.
Authors
- Yi Du (ORCID: https://orcid.org/0000-0002-4030-2738)
- Xuzhi Zhao (ORCID: https://orcid.org/0009-0005-6361-3220)
- Yahui Peng (ORCID: https://orcid.org/0000-0002-2520-1170)
- Xinyi Wang (ORCID: https://orcid.org/0009-0006-0731-6069)
Institutions
- Peking University (CN)
- Beijing Jiaotong University (CN)
- China People's Public Security University (CN)
- Peking University Cancer Hospital (CN)
- Second Affiliated Hospital of Inner Mongolia Medical University (CN)
- Inner Mongolia Medical University (CN)
Publication Details
- Journal
- Quantitative Imaging in Medicine and Surgery
- Published
- 2025-09-24
- DOI
- https://doi.org/10.21037/qims-24-1902
- Citations
- 1
- Primary Topic
- Medical Imaging Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 1.36