Evaluation of an artificial intelligence system for detecting vertical root fracture on panoramic radiography

Objectives The aim of this study was to evaluate the use of a convolutional neural network (CNN) system for detecting vertical root fracture (VRF) on panoramic radiography. Methods Three hundred panoramic images containing a total of 330 VRF teeth with clearly visible fracture lines were selected fr...

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Veröffentlicht in:	Oral radiology Jg. 36; H. 4; S. 337 - 343
Hauptverfasser:	Fukuda, Motoki, Inamoto, Kyoko, Shibata, Naoki, Ariji, Yoshiko, Yanashita, Yudai, Kutsuna, Shota, Nakata, Kazuhiko, Katsumata, Akitoshi, Fujita, Hiroshi, Ariji, Eiichiro
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Singapore Springer Singapore 01.10.2020 Springer Nature B.V
Schlagworte:	Artificial Intelligence Cone-Beam Computed Tomography Deep learning Dentistry Humans Imaging Medicine Neural networks Oral and Maxillofacial Surgery Original Article Radiography Radiography, Panoramic Radiology Reproducibility of Results Teeth Tooth Fractures - diagnostic imaging Tooth Root - diagnostic imaging Deep learning Vertical root fracture Panoramic radiography Artificial intelligence Object detection
ISSN:	0911-6028, 1613-9674, 1613-9674
Online-Zugang:	Volltext
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