A comparative study of computer vision models for oral cancer detection from oral photographs
This study underscores the potential of artificial intelligence in aiding early detection of oral cancers while identifying areas for improvement (notably: small lesion detection and distinguishing between malignant and benign). These findings provide a foundation for advancing medical computer vision tools to support early diagnosis and improve patient outcomes.
Authors
- Jérôme de Chauveron (ORCID: https://orcid.org/0000-0001-7653-5325)
- Juliette Rochefort (ORCID: https://orcid.org/0000-0002-9835-8275)
- Chenyu Zha (ORCID: https://orcid.org/0009-0009-7523-5860)
- Géraldine Lescaille (ORCID: https://orcid.org/0000-0002-0590-635X)
- Laurent Wendling (ORCID: https://orcid.org/0000-0003-1091-5995)
- Isabelle Brochériou
- Camille Kurtz (ORCID: https://orcid.org/0000-0001-9254-7537)
- Caroline Shaar-Chneker
Institutions
- Délégation Paris 5 (FR)
- Inserm (FR)
- Université Paris Cité (FR)
- Sorbonne Université (FR)
- Assistance Publique – Hôpitaux de Paris (FR)
- Pitié-Salpêtrière Hospital (FR)
- LIP6 (FR)
Publication Details
- Journal
- Computer Methods and Programs in Biomedicine
- Published
- 2025-12-05
- DOI
- https://doi.org/10.1016/j.cmpb.2025.109198
- Citations
- 1
- Primary Topic
- Dental Radiography and Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.79