Deep learning-based identification and maturation assessment of the zygomaticomaxillary suture in cone-beam computed tomography images

Abstract Objective This study addresses maxillary deficiency management by developing a deep learning-based system for zygomaticomaxillary suture assessment. As the maturation status serves as a pivotal indicator for optimal maxillary protraction timing, its accurate evaluation is crucial for treatm...

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Bibliografische gegevens

Hoofdauteurs:	Zehua Jin, Yuhua Shan, Jianxing Feng, Jingtao Li, Zhelin Shi, Haotian Wu, Xiaochen Fan, Ruomei Li, Zhenqi Chen
Formaat:	Artigo
Taal:	Inglês
Gepubliceerd in:	SpringerOpen 2026-03-01
Reeks:	Progress in Orthodontics
Onderwerpen:	Maxillary protraction Zygomaticomaxillary suture Maturation staging Cone-beam computed tomography Convolutional neural network
Online toegang:	https://doi.org/10.1186/s40510-026-00614-5
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