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

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...

Full description

Bibliographic Details
Main Authors: Xi Lin, Weini Xin, Jingna Huang, Yang Jing, Pengfei Liu, Jingdan Han, Jie Ji
Format: Article
Language:English
Published: BMC 2023-08-01
Series:BMC Oral Health
Subjects:
Artificial intelligence
Dental radiology
Cone-beam computerized tomography
Inferior alveolar nerve
Online Access:https://doi.org/10.1186/s12903-023-03279-2

Internet

https://doi.org/10.1186/s12903-023-03279-2

Similar Items