Automatic identification of posteroanterior cephalometric landmarks using a novel deep learning algorithm: a comparative study with human experts
Abstract This study aimed to propose a fully automatic posteroanterior (PA) cephalometric landmark identification model using deep learning algorithms and compare its accuracy and reliability with those of expert human examiners. In total, 1032 PA cephalometric images were used for model training an...
Main Authors: | Hwangyu Lee, Jung Min Cho, Susie Ryu, Seungmin Ryu, Euijune Chang, Young-Soo Jung, Jun-Young Kim |
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Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2023-09-01
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Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-023-42870-z |
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