A High-Accuracy Detection System: Based on Transfer Learning for Apical Lesions on Periapical Radiograph.

Apical Lesions, one of the most common oral diseases, can be effectively detected in daily dental examinations by a periapical radiograph (PA). In the current popular endodontic treatment, most dentists spend a lot of time manually marking the lesion area. In order to reduce the burden on dentists, this paper proposes a convolutional neural network (CNN)-based regional analysis model for spical lesions for periapical radiographs. In this study, the database was provided by dentists with more than three years of practical experience, meeting the criteria for clinical practical application. The contributions of this work are (1) an advanced adaptive threshold preprocessing technique for image segmentation, which can achieve an accuracy rate of more than 96%; (2) a better and more intuitive apical lesions symptom enhancement technique; and (3) a model for apical lesions detection with an accuracy as high as 96.21%. Compared with existing state-of-the-art technology, the proposed model has improved the accuracy by more than 5%. The proposed model has successfully improved the automatic diagnosis of apical lesions. With the help of automation, dentists can focus more on technical and medical diagnoses, such as treatment, tooth cleaning, or medical communication. This proposal has been certified by the Institutional Review Board (IRB) with the certification number 202002030B0.

Removal efficiency of central vacuum system and protective masks to suspended particles from dental treatment.

BACKGROUND: High levels of suspended particulate matters (PMs) and bioaerosols are created by dental procedures. The present study aimed to evaluate the size and concentration of PMs produced by drilling and grinding teeth, and to assess the efficiency of central vacuum system and protective masks for the removal of PMs. METHODS: A total of 20 extracted permanent teeth were collected. A novel experimental system and particle counter were used to evaluate the PMs produced by dental procedures and the PM removal efficiency of a central vacuum system and surgical/N95 masks. RESULTS: The number concentration of total PMs produced by drilling and grinding teeth was significantly higher than the indoor background concentration. The average aerodynamic diameter of particle was generally less than 1 µm. The average number concentration of ultrafine particles was 2.1x1011 particles/m3 during tooth drilling and grinding. The efficiency of the central vacuum system was 35.74% for PM≥0.5 and 35.41% for PM10. For PM≥0.5, the ratios of inside and outside masks were 0.8-1.34 without vacuum and 1.18-1.36 with vacuum. No difference was found with the use of surgical/N95 masks during dental therapy, with or without vacuum use. CONCLUSIONS: High levels of PMs were found during tooth drilling and grinding procedures, especially among PM1. The PM removal efficiency of a central vacuum system and surgical/N95 masks were limited.