Assessment of CNNs, transformers, and hybrid architectures in dental image segmentation
As deep-learning-based image analysis is part of modern dentistry, practitioners and dental researchers should be aware of strength and limitations of modern model architectures for dental-image analysis. Models that demonstrate optimal performance in other domains do not necessarily constitute the optimal selection for the purpose of dental imaging.
Authors
- Vinay Pitchika (ORCID: https://orcid.org/0000-0001-6947-2602)
- Lisa Schneider (ORCID: https://orcid.org/0000-0002-4431-2669)
- Falk Schwendicke (ORCID: https://orcid.org/0000-0003-1223-1669)
- M. Büttner
- Aleksander Krasowski (ORCID: https://orcid.org/0000-0003-0192-788X)
- Lisa Bombeck
Institutions
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin (DE)
- Charité - Universitätsmedizin Berlin (DE)
- Ludwig-Maximilians-Universität München (DE)
Publication Details
- Journal
- Journal of Dentistry
- Published
- 2025-03-08
- DOI
- https://doi.org/10.1016/j.jdent.2025.105668
- Citations
- 12
- Primary Topic
- Dental Radiography and Imaging
- Type
- article
- Field-Weighted Citation Impact
- 21.49
Funders
- Deutsche Forschungsgemeinschaft