Soft-tissue prediction based on 3D photographs for virtual surgery planning of orthognathic surgery
This study demonstrated the potential of a deep learning-based approach for real-time prediction of facial soft-tissue changes following various orthognathic procedures, achieving clinically relevant accuracy comparable to existing deep learning-based methods.
Authors
- Bo Berends (ORCID: https://orcid.org/0000-0002-3305-4916)
- Thomas J. J. Maal
- Ruud Schreurs (ORCID: https://orcid.org/0000-0003-2429-2071)
- Freek Bielevelt (ORCID: https://orcid.org/0000-0003-2539-562X)
- Frank Baan (ORCID: https://orcid.org/0000-0002-3626-656X)
- Tong Xi (ORCID: https://orcid.org/0000-0002-9142-9253)
- Guido de Jong (ORCID: https://orcid.org/0000-0002-8014-0622)
Institutions
- Radboud University Nijmegen (NL)
- Radboud University Medical Center (NL)
- Radboud Institute for Molecular Life Sciences (NL)
Publication Details
- Journal
- Computers in Biology and Medicine
- Published
- 2025-06-11
- DOI
- https://doi.org/10.1016/j.compbiomed.2025.110529
- Citations
- 3
- Primary Topic
- Orthodontics and Dentofacial Orthopedics
- Type
- article
- Field-Weighted Citation Impact
- 5.03