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Authors: Mazin Mohammed 1 ; Salah Zrigui 1 ; 2 and Mounir Zrigui 3

Affiliations: 1 University of Monastir, Research Laboratory in Algebra, Numbers Theory and Intelligent sys-tem (RLANTIS), Monstir 5019, Tunisia ; 2 Lig Laboratory, Grenoble, France ; 3 University of Al-Mosul, University of the Presidency, Nineveh, Iraq

Keyword(s): Oral Disease Classification, Dental Caries Detection, Dental Images, Deep Learning.

Abstract: Recently, the automation diagnosis process of dental caries plays a critical role in medical applications. This paper presents a new dataset of photo-graphic images for six different types of oral diseases. The dataset is gathered and labelled by professional medical operators in the dentistry field. We use the collected dataset to train a binary classifier to determine whether the region of interests (ROI) needs detection or not inside the input image. Then, we train a detector to detect and localize the required ROI. Finally, we use the detected regions to train a CNN network by adopting transfer learning technique to classify various kinds of teeth diseases. With this model, we obtained an almost 93 % accuracy by modifying and re-training the pre-trained model VGG19.

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Paper citation in several formats:
Mohammed, M., Zrigui, S. and Zrigui, M. (2024). Oral Diseases Recognition Based on Photographic Images. In Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-680-4; ISSN 2184-433X, SciTePress, pages 486-493. DOI: 10.5220/0012361500003636

@conference{icaart24,
author={Mazin Mohammed and Salah Zrigui and Mounir Zrigui},
title={Oral Diseases Recognition Based on Photographic Images},
booktitle={Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2024},
pages={486-493},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012361500003636},
isbn={978-989-758-680-4},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Oral Diseases Recognition Based on Photographic Images
SN - 978-989-758-680-4
IS - 2184-433X
AU - Mohammed, M.
AU - Zrigui, S.
AU - Zrigui, M.
PY - 2024
SP - 486
EP - 493
DO - 10.5220/0012361500003636
PB - SciTePress

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