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

• Hlavní autoři: Xi Lin (Autor), Weini Xin (Autor), Jingna Huang (Autor), Yang Jing (Autor), Pengfei Liu (Autor), Jingdan Han (Autor), Jie Ji (Autor)
• Médium: Kniha
• Vydáno: BMC, 2023-08-01T00:00:00Z.
• Témata: article
• On-line přístup: Connect to this object online.

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...