A smart home dental care system: integration of deep learning, image sensors, and mobile controller
| Autor: | Eunil Park, Dogun Kim, Jaeho Choi, Sangyoon Ahn |
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| Rok vydání: | 2020 |
| Předmět: |
medicine.medical_specialty
General Computer Science business.industry Computer science Deep learning Controller (computing) Dentistry Convolutional neural network Applied artificial intelligence Dental care Home care stomatognathic diseases stomatognathic system Home automation Dental surgery medicine Image acquisition System integration Dental Computer vision Artificial intelligence Image sensor business Original Research |
| Zdroj: | Journal of Ambient Intelligence and Humanized Computing |
| ISSN: | 1868-5137 |
| Popis: | In this study, a home dental care system consisting of an oral image acquisition device and deep learning models for maxillary and mandibular teeth images is proposed. The presented method not only classifies tooth diseases, but also determines whether a professional dental treatment (NPDT) is required. Additionally, a specially designed oral image acquisition device was developed to perform image acquisition of maxillary and mandibular teeth. Two evaluation metrics, namely, tooth disease and NPDT classifications, were examined using 610 compounded and 5251 tooth images annotated by an experienced dentist with a Doctor of Dental Surgery and another dentist with a Doctor of Dental Medicine. In the tooth disease and NPDT classifications, the proposed system showed accuracies greater than 96% and 89%, respectively. Based on these results, we believe that the proposed system will allow users to effectively manage their dental health by detecting tooth diseases by providing information on the need for dental treatment. Supplementary Information The online version contains supplementary material available at 10.1007/s12652-021-03366-8. |
| Databáze: | OpenAIRE |
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