Deep learning-based multimodal CT/MRI image fusion and segmentation strategies for surgical planning of oral and maxillofacial tumors: A pilot study
In this study, deep learning models capable of automatic multimodal CT/MRI image fusion and segmentation of oral and maxillofacial tumors were successfully trained with a high degree of accuracy. The results demonstrated the feasibility of using deep learning-based image fusion and segmentation to establish a basis for virtual surgical planning.
Authors
- Ji Tan (ORCID: https://orcid.org/0000-0001-6760-0316)
- Shanshan Cao (ORCID: https://orcid.org/0000-0001-7280-1657)
- Bin‐Zhang Wu (ORCID: https://orcid.org/0000-0002-8627-0153)
- Xin Peng (ORCID: https://orcid.org/0000-0001-9277-8415)
- Jingfan Fan (ORCID: https://orcid.org/0000-0003-4857-6490)
- Wenbo Zhang (ORCID: https://orcid.org/0000-0001-7071-5931)
- Lei‐Hao Hu
- Nian-Zha Danzeng
Institutions
- Beijing Institute of Technology (CN)
- Peking University (CN)
- National Clinical Research (US)
- Stomatology Hospital (CN)
- Tibet Autonomous Region People's Hospital (CN)
Publication Details
- Journal
- Journal of Stomatology Oral and Maxillofacial Surgery
- Published
- 2025-04-02
- DOI
- https://doi.org/10.1016/j.jormas.2025.102324
- Citations
- 4
- Primary Topic
- Dental Radiography and Imaging
- Type
- article
- Field-Weighted Citation Impact
- 7.16
Funders
- Natural Science Foundation of Beijing Municipality
- National Key Research and Development Program of China