Automatic identification of hard and soft tissue landmarks in cone-beam computed tomography via deep learning with diversity datasets: a methodological study

Automatic identification of hard and soft tissue landmarks in cone-beam computed tomography via deep learning with diversity datasets: a methodological study

Abstract Background Manual landmark detection in cone beam computed tomography (CBCT) for evaluating craniofacial structures relies on medical expertise and is time-consuming. This study aimed to apply a new deep learning method to predict and locate soft and hard tissue craniofacial landmarks on CB...

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Bibliographic Details
Main Authors: Yan Jiang, Canyang Jiang, Bin Shi, You Wu, Shuli Xing, Hao Liang, Jianping Huang, Xiaohong Huang, Li Huang, Lisong Lin
Format: Article
Language:English
Published: BMC 2025-04-01
Series:BMC Oral Health
Subjects:
3D landmark identification
Accuracy
CBCT
Deep learning
Online Access:https://doi.org/10.1186/s12903-025-05831-8
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https://doi.org/10.1186/s12903-025-05831-8

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