Transformer-Based Deep Learning Network for Tooth Segmentation on Panoramic Radiographs-Reference-Cited by-同舟云学术

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Transformer-Based Deep Learning Network for Tooth Segmentation on Panoramic Radiographs

Published:2022-10-14 Issue:1 Volume:36 Page:257-272
ISSN:1009-6124
Container-title:Journal of Systems Science and Complexity
language:en
Short-container-title:J Syst Sci Complex

Author:

Sheng Chen,Wang Lin,Huang Zhenhuan,Wang Tian,Guo Yalin,Hou Wenjie,Xu Laiqing,Wang Jiazhu,Yan Xue

Publisher

Springer Science and Business Media LLC

Subject

Information Systems,Computer Science (miscellaneous)

Link

https://link.springer.com/content/pdf/10.1007/s11424-022-2057-9.pdf

Reference35 articles.

1. Perschbacher S, Interpretation of panoramic radiographs, Australian Dental Journal, 2012, 57: 40–45.

2. Kim J, Kim H, and Ro Y, Iterative deep convolutional encoder-decoder network for medical image segmentation, Proceedings of Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2017, 685–688.

3. Zhao J, Ma Y, Pan Z, et al., Research on image signal identification based on adaptive array stochastic resonance, Journal of Systems Science and Complexity, 2022, 35(1): 179–193.

4. Wu C, Tsai W, Chen Y, et al., Model-based orthodontic assessments for dental panoramic radiographs, IEEE Journal of Biomedical and Health Informatics, 2017, 22(2): 545–551.

5. Ammar H, Ngan P, Crout R, et al., Three-dimensional modeling and finite element analysis in treatment planning for orthodontic tooth movement, American Journal of Orthodontics and Dentofacial Orthopedics, 2011, 139(1): 59–71.

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