Deep Learning Models for Evaluating the Anatomical Relationship Between Posterior Maxillary Teeth and Maxillary Sinus in Panoramic Radiographs
Deep learning models, particularly ResNet and ResNeXt, provide reliable assessment of the anatomical relationship between posterior maxillary teeth and the maxillary sinus using panoramic radiographs. These models can serve as efficient diagnostic aids when CBCT is unavailable, improving clinical decision-making in panoramic images.
Authors
- Parisa Soltani (ORCID: https://orcid.org/0000-0002-9273-5279)
- Akram Fallah (ORCID: https://orcid.org/0009-0004-2392-1133)
- Gianrico Spagnuolo (ORCID: https://orcid.org/0000-0003-3769-9786)
- Mojdeh Mehdizadeh (ORCID: https://orcid.org/0000-0002-4367-8132)
- Mahsa Moannaei (ORCID: https://orcid.org/0000-0001-5475-9627)
- Carlo Rengo (ORCID: https://orcid.org/0000-0003-1127-0877)
- Mostafa Riahi Farsani (ORCID: https://orcid.org/0000-0002-2272-0717)
- M. Hossaini
- Seyed Amir Hossein Ourang
Institutions
- Isfahan University of Medical Sciences (IR)
- Shahrekord University (IR)
- University of Hormozgan (IR)
- Research Institute for Endocrine Sciences (IR)
- Federico II University Hospital (IT)
- Shahid Beheshti University of Medical Sciences (IR)
- University of Naples Federico II (IT)
Publication Details
- Journal
- Clinical and Experimental Dental Research
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1002/cre2.70264
- Primary Topic
- Dental Radiography and Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00