Automated Identification of Cephalometric Landmarks: Part 2- Might It Be Better Than human?

OBJECTIVES: To compare detection patterns of 80 cephalometric landmarks identified by an automated identification system (AI) based on a recently proposed deep-learning method, the You-Only-Look-Once version 3 (YOLOv3), with those identified by human examiners. MATERIALS AND METHODS: The YOLOv3 algo...

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Dettagli Bibliografici
Pubblicato in:Angle Orthod
Autori principali: Hwang, Hye-Won, Park, Ji-Hoon, Moon, Jun-Ho, Yu, Youngsung, Kim, Hansuk, Her, Soo-Bok, Srinivasan, Girish, Aljanabi, Mohammed Noori A., Donatelli, Richard E., Lee, Shin-Jae
Natura: Artigo
Lingua:Inglês
Pubblicazione: Edward H. Angle Society of Orthodontists 2019
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Original Articles
Accesso online:https://ncbi.nlm.nih.gov/pmc/articles/PMC8087057/
https://ncbi.nlm.nih.gov/pubmed/31335162
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.2319/022019-129.1
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