Analysis of the feasibility of using deep learning for multiclass classification of dental anomalies on panoramic radiographs

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Title ( eng )
Analysis of the feasibility of using deep learning for multiclass classification of dental anomalies on panoramic radiographs
Title ( jpn )
深層学習によるパノラマエックス線画像からの歯数異常の多値分類
Creator
Okazaki Shota
Language
eng
Resource Type doctoral thesis
Rights
© by author, The copyright of this paper belongs to the Japanese Society for Dental Materials and Devices.
Access Rights open access
Source Identifier
Dental Materials Journal 2022 Volume 41 Issue 6 Pages 889-895
[DOI] https://doi.org/10.4012/dmj.2022-098
Dissertation Number 甲第9586号
Degree Name
Date of Granted 2024-03-23
Degree Grantors
広島大学
Hiroshima University