Accurate mandibular canal segmentation of dental CBCT using a two-stage 3D-UNet based segmentation framework

Abstract Objectives The objective of this study is to develop a deep learning (DL) model for fast and accurate mandibular canal (MC) segmentation on cone beam computed tomography (CBCT). Methods A total of 220 CBCT scans from dentate subjects needing oral surgery were used in this study. The segment...

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Detalles Bibliográficos

Principais autores:	Xi Lin, Weini Xin, Jingna Huang, Yang Jing, Pengfei Liu, Jingdan Han, Jie Ji
Formato:	Artigo
Idioma:	Inglês
Publicado:	BMC 2023-08-01
Series:	BMC Oral Health
Assuntos:	Artificial intelligence Dental radiology Cone-beam computerized tomography Inferior alveolar nerve
Acceso en liña:	https://doi.org/10.1186/s12903-023-03279-2
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