A deep learning approach to automatic teeth detection and numbering based on object detection in den...
A deep learning approach to automatic teeth detection and numbering based on object detection in dental periapical films
About this item
Full title
Author / Creator
Chen, Hu , Zhang, Kailai , Lyu, Peijun , Li, Hong , Zhang, Ludan , Wu, Ji and Lee, Chin-Hui
Publisher
London: Nature Publishing Group UK
Journal title
Language
English
Formats
Publication information
Publisher
London: Nature Publishing Group UK
Subjects
More information
Scope and Contents
Contents
We propose using faster regions with convolutional neural network features (faster R-CNN) in the TensorFlow tool package to detect and number teeth in dental periapical films. To improve detection precisions, we propose three post-processing techniques to supplement the baseline faster R-CNN according to certain prior domain knowledge. First, a fil...
Alternative Titles
Full title
A deep learning approach to automatic teeth detection and numbering based on object detection in dental periapical films
Authors, Artists and Contributors
Author / Creator
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6405755
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6405755
Other Identifiers
ISSN
2045-2322
E-ISSN
2045-2322
DOI
10.1038/s41598-019-40414-y
