Artificial intelligence-based metal artefact correction algorithm for radiotherapy patients with dental hardware in head and neck CT: towards precise imaging
AI-MAC is a novel deep learning-based technique for reducing metal artefacts on CT. This in vivo study demonstrated its capability of reducing metal artefacts while preserving organ visualization, as compared with conventional MAC.
Authors
- Sihua Zhong (ORCID: https://orcid.org/0000-0002-1450-6761)
- Guangyu Wang (ORCID: https://orcid.org/0000-0001-7679-540X)
- Jiang Hu (ORCID: https://orcid.org/0000-0001-6356-2201)
- Guozhi Zhang (ORCID: https://orcid.org/0000-0002-0420-871X)
- Jinlong Du
- Xiaoli Yu (ORCID: https://orcid.org/0000-0002-9315-5663)
Institutions
- Sun Yat-sen University (CN)
- Sun Yat-sen Memorial Hospital (CN)
- United Imaging Healthcare (China) (CN)
- Sun Yat-sen University Cancer Center (CN)
Publication Details
- Journal
- Dentomaxillofacial Radiology
- Published
- 2025-05-14
- DOI
- https://doi.org/10.1093/dmfr/twaf038
- Citations
- 1
- Primary Topic
- Advanced X-ray and CT Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.67