Multi-Scale 3D Cephalometric Landmark Detection Based on Direct Regression with 3D CNN Architectures

Multi-Scale 3D Cephalometric Landmark Detection Based on Direct Regression with 3D CNN Architectures

Background: Cephalometric analysis is important in diagnosing and planning treatments for patients, traditionally relying on 2D cephalometric radiographs. With advancements in 3D imaging, automated landmark detection using deep learning has gained prominence. However, 3D imaging introduces challenge...

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Bibliographic Details
Main Authors: Chanho Song, Yoosoo Jeong, Hyungkyu Huh, Jee-Woong Park, Jun-Young Paeng, Jaemyung Ahn, Jaebum Son, Euisung Jung
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Diagnostics
Subjects:
cephalometric landmark detection
3D convolutional neural network (CNN)
cephalometric analysis
Online Access:https://www.mdpi.com/2075-4418/14/22/2605
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