Deep Learning to Detect and Classify Teeth, Dental Caries and Restorations: A Systematic Mapping

Abstract

Purpose: Oral health is an indicator of individuals' health and quality of life. Consequently, it is a concerning topic faced everyday by healthcare professionals. X-ray images are essential resources for detecting oral problems. Artificial Intelligence has gained attention in the detection of oral diseases and conditions. We carry out a systematic mapping in the literature regarding the application of deep learning in dental radiographs for detection, segmentation, and classification of teeth, caries, and restorations. Methods: Through automated searches in the ACM Digital Library, IEEE Xplore Digital Library, PubMed, and Scopus, 394 primary articles were found, published between 2012-2023. After applying inclusion and exclusion criteria, 69 articles were read and analyzed considering: consistency and adequacy of the used databases, implemented techniques, and results. Results: 40.82% of the analyzed articles did not present clear information on the approval of ethics committees to carry out the research. Although the application of computational techniques in oral health is an interdisciplinary topic, 37.68% of the 69 surveys were conducted by teams composed only of professionals from one area. 66.67% of the articles explored only panoramic radiographs and the most used metrics were accuracy, recall, and precision. The U-Net and Mask R-CNN networks were the most applied. Conclusion: Despite the increase in the number of investigations, some challenges, such as the low availability of public data sets, the lack of details in the developed methodologies, and the lack of standardization when presenting results, complicate a fair comparison between papers, which is an obstacle to be overcome.

Performance analysis of DMF teeth detection using deep learning: A comparative study with clinical examination as quasi experimental study

“…11 DL has been utilized in the field of dentistry. 12 Research by You et al stated that the developed AI model can detect plaque on primary teeth. 13 Studies conducted by Lian et al stated that DL methods can detect and classify the depth of caries lesions from panoramic radiographs.…”