Automated detection of mandibular landmarks in CT data using a dual-input approach in a two-stage design
The proposed method demonstrates high accuracy, robustness, and speed suggesting strong potential for integration into clinical workflows for automated, patient-specific surgical planning in cranio-maxillofacial surgery.
Authors
- Frank Hölzle
- Tobias Pankert (ORCID: https://orcid.org/0000-0001-5840-2115)
- Oliver Röhrle (ORCID: https://orcid.org/0000-0002-1934-6525)
- Stefan Raith (ORCID: https://orcid.org/0000-0001-8470-9145)
- Ali Modabber (ORCID: https://orcid.org/0000-0003-2160-4527)
- Srikrishna Jaganathan
- Matthias Deitermann
Institutions
- University of Stuttgart (DE)
- Abiomed (Germany) (DE)
- RWTH Aachen University (DE)
Publication Details
- Journal
- Computer Methods and Programs in Biomedicine
- Published
- 2025-10-11
- DOI
- https://doi.org/10.1016/j.cmpb.2025.109113
- Primary Topic
- Dental Radiography and Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00