Classification of Caries Based on CBCT: A Deep Learning Network Interpretability Study.

This study aimed to create a caries classification scheme based on cone-beam computed tomography (CBCT) and develop two deep learning models to improve caries classification accuracy. A total of 2713 axial slices were obtained from CBCT images of 204 carious teeth. Both classification models were tr...

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Detalles Bibliográficos

Publicado en:	Journal of Digital Imaging Vol. 37; no. 6; pp. 3160 - 3174
Autores principales:	Chen, Surong, Yang, Yan, Wu, Weiwei, Wei, Ruonan, Wang, Zezhou, Tay, Franklin R., Hu, Jingyu, Ma, Jingzhi
Formato:	diagnostic images equations & formulas research tables/charts Journal Article
Publicado:	Springer Nature Dec2024
Acceso en línea:	Ver este registro en EBSCOhost