Deep learning-based detection of dental prostheses and restorations

Abstract The purpose of this study is to develop a method for recognizing dental prostheses and restorations of teeth using a deep learning. A dataset of 1904 oral photographic images of dental arches (maxilla: 1084 images; mandible: 820 images) was used in the study. A deep-learning method to recog...

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Autores principales:	Toshihito Takahashi, Kazunori Nozaki, Tomoya Gonda, Tomoaki Mameno, Kazunori Ikebe
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/d672d398392745c2bb498f6af87383ea
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spelling	oai:doaj.org-article:d672d398392745c2bb498f6af87383ea2021-12-02T10:49:11ZDeep learning-based detection of dental prostheses and restorations10.1038/s41598-021-81202-x2045-2322https://doaj.org/article/d672d398392745c2bb498f6af87383ea2021-01-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-81202-xhttps://doaj.org/toc/2045-2322Abstract The purpose of this study is to develop a method for recognizing dental prostheses and restorations of teeth using a deep learning. A dataset of 1904 oral photographic images of dental arches (maxilla: 1084 images; mandible: 820 images) was used in the study. A deep-learning method to recognize the 11 types of dental prostheses and restorations was developed using TensorFlow and Keras deep learning libraries. After completion of the learning procedure, the average precision of each prosthesis, mean average precision, and mean intersection over union were used to evaluate learning performance. The average precision of each prosthesis varies from 0.59 to 0.93. The mean average precision and mean intersection over union of this system were 0.80 and 0.76, respectively. More than 80% of metallic dental prostheses were detected correctly, but only 60% of tooth-colored prostheses were detected. The results of this study suggest that dental prostheses and restorations that are metallic in color can be recognized and predicted with high accuracy using deep learning; however, those with tooth color are recognized with moderate accuracy.Toshihito TakahashiKazunori NozakiTomoya GondaTomoaki MamenoKazunori IkebeNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-7 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Toshihito Takahashi Kazunori Nozaki Tomoya Gonda Tomoaki Mameno Kazunori Ikebe Deep learning-based detection of dental prostheses and restorations
description	Abstract The purpose of this study is to develop a method for recognizing dental prostheses and restorations of teeth using a deep learning. A dataset of 1904 oral photographic images of dental arches (maxilla: 1084 images; mandible: 820 images) was used in the study. A deep-learning method to recognize the 11 types of dental prostheses and restorations was developed using TensorFlow and Keras deep learning libraries. After completion of the learning procedure, the average precision of each prosthesis, mean average precision, and mean intersection over union were used to evaluate learning performance. The average precision of each prosthesis varies from 0.59 to 0.93. The mean average precision and mean intersection over union of this system were 0.80 and 0.76, respectively. More than 80% of metallic dental prostheses were detected correctly, but only 60% of tooth-colored prostheses were detected. The results of this study suggest that dental prostheses and restorations that are metallic in color can be recognized and predicted with high accuracy using deep learning; however, those with tooth color are recognized with moderate accuracy.
format	article
author	Toshihito Takahashi Kazunori Nozaki Tomoya Gonda Tomoaki Mameno Kazunori Ikebe
author_facet	Toshihito Takahashi Kazunori Nozaki Tomoya Gonda Tomoaki Mameno Kazunori Ikebe
author_sort	Toshihito Takahashi
title	Deep learning-based detection of dental prostheses and restorations
title_short	Deep learning-based detection of dental prostheses and restorations
title_full	Deep learning-based detection of dental prostheses and restorations
title_fullStr	Deep learning-based detection of dental prostheses and restorations
title_full_unstemmed	Deep learning-based detection of dental prostheses and restorations
title_sort	deep learning-based detection of dental prostheses and restorations
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/d672d398392745c2bb498f6af87383ea
work_keys_str_mv	AT toshihitotakahashi deeplearningbaseddetectionofdentalprosthesesandrestorations AT kazunorinozaki deeplearningbaseddetectionofdentalprosthesesandrestorations AT tomoyagonda deeplearningbaseddetectionofdentalprosthesesandrestorations AT tomoakimameno deeplearningbaseddetectionofdentalprosthesesandrestorations AT kazunoriikebe deeplearningbaseddetectionofdentalprosthesesandrestorations
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Deep learning-based detection of dental prostheses and restorations

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