Evaluation of deep learning and convolutional neural network algorithms accuracy for detecting and predicting anatomical landmarks on 2D lateral cephalometric images: A systematic review and meta-analysis

Evaluation of deep learning and convolutional neural network algorithms accuracy for detecting and predicting anatomical landmarks on 2D lateral cephalometric images: A systematic review and meta-analysis

Introduction: Cephalometry is the study of skull measurements for clinical evaluation, diagnosis, and surgical planning. Machine learning (ML) algorithms have been used to accurately identify cephalometric landmarks and detect irregularities related to orthodontics and dentistry. ML-based cephalomet...

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Bibliographic Details
Main Authors: Jimmy Londono, Shohreh Ghasemi, Altaf Hussain Shah, Amir Fahimipour, Niloofar Ghadimi, Sara Hashemi, Zohaib Khurshid, Mahmood Dashti
Format: Article
Language:English
Published: Springer 2023-07-01
Series:Saudi Dental Journal
Subjects:
Machine learning
Convolutional neural network
Artificial intelligence
Lateral cephalometry
Orthodontics
Accuracy
Online Access:http://www.sciencedirect.com/science/article/pii/S1013905223000962
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