Tooth detection and classification on panoramic radiographs for automatic dental chart filing: improved classification by multi-sized input data.
Classification
Convolutional neural network
Dental chart
Detection
Panoramic radiographs
Journal
Oral radiology
ISSN: 1613-9674
Titre abrégé: Oral Radiol
Pays: Japan
ID NLM: 8806621
Informations de publication
Date de publication:
01 2021
01 2021
Historique:
received:
11
10
2019
accepted:
15
12
2019
pubmed:
2
1
2020
medline:
20
4
2021
entrez:
2
1
2020
Statut:
ppublish
Résumé
Dental state plays an important role in forensic radiology in case of large scale disasters. However, dental information stored in dental clinics are not standardized or electronically filed in general. The purpose of this study is to develop a computerized system to detect and classify teeth in dental panoramic radiographs for automatic structured filing of the dental charts. It can also be used as a preprocessing step for computerized image analysis of dental diseases. One hundred dental panoramic radiographs were employed for training and testing an object detection network using fourfold cross-validation method. The detected bounding boxes were then classified into four tooth types, including incisors, canines, premolars, and molars, and three tooth conditions, including nonmetal restored, partially restored, and completely restored, using classification network. Based on the visualization result, multisized image data were used for the double input layers of a convolutional neural network. The result was evaluated by the detection sensitivity, the number of false-positive detection, and classification accuracies. The tooth detection sensitivity was 96.4% with 0.5 false positives per case. The classification accuracies for tooth types and tooth conditions were 93.2% and 98.0%. Using the double input layer network, 6 point increase in classification accuracy was achieved for the tooth types. The proposed method can be useful in automatic filing of dental charts for forensic identification and preprocessing of dental disease prescreening purposes.
Identifiants
pubmed: 31893343
doi: 10.1007/s11282-019-00418-w
pii: 10.1007/s11282-019-00418-w
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
13-19Références
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