<scp>OralSegNet</scp> : An Approach to Early Detection of Oral Disease Using Transfer Learning
For application, the best performing model was exported to ONNX format with NMS enabled and deployed as a fully client-side responsive web app built in React.js and ONNX Runtime Web. The tool enables both clinicians and non-experts to detect oral diseases from intraoral images with a single click.
Authors
- Proloy Barua (ORCID: https://orcid.org/0000-0001-6951-6628)
- Mahmud Uz Zaman (ORCID: https://orcid.org/0000-0001-7364-530X)
- Huda Abutayyem (ORCID: https://orcid.org/0000-0002-6399-8467)
- Maher Al Shayeb (ORCID: https://orcid.org/0000-0002-3296-5945)
- Adel Alenazi (ORCID: https://orcid.org/0000-0002-1589-6685)
- Mohammad Khursheed Alam (ORCID: https://orcid.org/0000-0001-7131-1752)
- Nesrine A. Elsahn (ORCID: https://orcid.org/0000-0002-6539-2813)
- Fawaz Alqahtani (ORCID: https://orcid.org/0000-0003-2695-3603)
- Ruba Odeh (ORCID: https://orcid.org/0000-0003-4151-6196)
- Md. Rakibul Islam (ORCID: https://orcid.org/0000-0002-8246-4874)
Institutions
- Prince Sattam Bin Abdulaziz University (SA)
- Ajman University (AE)
- Jouf University (SA)
- Daffodil International University (BD)
- Universiti Teknologi Petronas (MY)
- Saveetha University (IN)
- University of Chittagong (BD)
Publication Details
- Journal
- Oral Diseases
- Published
- 2025-11-09
- DOI
- https://doi.org/10.1111/odi.70135
- Primary Topic
- Dental Radiography and Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Ajman University