An attention-based transformer model for dental caries detection

Che Sun; Hu Chen

doi:10.1117/12.2635362

6 May 2022 An attention-based transformer model for dental caries detection

Che Sun, Hu Chen

Proceedings Volume 12256, International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2022); 122562R (2022) https://doi.org/10.1117/12.2635362
Event: 2022 International Conference on Electronic Information Engineering, Big Data and Computer Technology, 2022, Sanya, China

Abstract

Dental caries is one of the most common diseases suffered by modern people. If early diagnosis and treatment are not carried out in time, dental caries may greatly affect the quality of life. However, the doctor’s diagnosis often misses tooth decay that is not obvious. In our research, we propose a caries detection model that combines attention mechanism and transformer. A new attention mechanism is introduced to represent features in different channels better. The AP50 of the model reached 63.81%, and even unlabeled caries in the X-ray image could be found.

Citation Download Citation

Che Sun and Hu Chen "An attention-based transformer model for dental caries detection", Proc. SPIE 12256, International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2022), 122562R (6 May 2022); https://doi.org/10.1117/12.2635362

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