Buy (2000 RUB)
|Generate QR code
Open Access
Subscription or Fee Access
ViSurgery, a new online platform for 2D-cephalometric analysis using artificial intelligence
Abstract
Artificial neural networks are now a common component of machine learning in many computer algorithms that deal with automated picture recognition. In orthodontics and maxillofacial surgery, the 2D-cephalometric radiograph is a significant and still applicable research approach, although the doctor must spend a lot of time analyzing the images. Utilizing artificial intelligence technologies, the new online platform ViSurgery enables the calculation of the lateral and frontal cephalograms automatically. Regardless of the image's source, the generated CNN handles cephalograms and achieves 98% accuracy. The proposed method requires five times less time than the conventional "manual" method of setting up cephalometric points.
About the Authors
N. Yu. Oborotistov
Московский государственный медико-стоматологический университет им. А.И. Евдокимова
Russian Federation
Russian Federation
A. A. Muraev
Российский университет дружбы народов
Russian Federation
Russian Federation
D. A. Senko
Компания «Stack Soft JSC»
Russian Federation
Russian Federation
References
1. Amberg B., Vetter T. Optimal landmark detection using shape models and branch and bound. Computer Vision (ICCV), 2011 IEEE International Conference on. IEEE. 2011;455-462.
2. Belhumeur P. N. et al. Localizing parts of faces using a consensus of exemplars. IEEE transactions on pattern analysis and machine intelligence. 2013;35(12):2930-2940.
3. Hwang H.W., Park J.H., Moon J.H. et al. Automated identification of cephalometric landmarks: Part 2-Might it be better than human?. Angle Orthod. 2020;90(1):69-76.
4. Kim H., Shim E., Park J., Kim Y.J., Lee U., Kim Y. Web-based fully automated cephalometric analysis by deep learning. Comput Methods Programs Biomed. 2020;194.
5. Kunz F., Stellzig-Eisenhauer A., Zeman F., Boldt J. Artificial intelligence in orthodontics: Evaluation of a fully automated cephalometric analysis using a customized convolutional neural network. Künstliche Intelligenz in der Kieferorthopädie: Evaluierung einer vollständig automatisierten Fernröntgenseitenanalyse unter Anwendung eines individualisierten «convolutional neural network». J Orofac Orthop. 2020;81(1):52-68.
6. Liang L. et al. Face alignment via component-based discriminative search. European conference on computer vision. Berlin – Heidelberg: Springer. 2008;72-85.
7. Lindner C., Wang C.W., Huang C.T., Li C.H., Chang S.W., Cootes T.F. Fully Automatic System for Accurate Localisation and Analysis of Cephalometric Landmarks in Lateral Cephalograms. Sci Rep. 2016;6:1-10.
8. Luo P., Wang X., Tang X. Hierarchical face parsing via deep learning. 2012 IEEE Conference on Computer Vision and Pattern Recognition. IEEE. 2012;2480-2487.
9. Muraev A.A., Kibardin I.A., Oborotistov N.Yu., Ivanov S.S., Ivanov S.Yu., Persin L.S. Use of neural network algorithms for the automated arrangement of cephalometric markers on lateral cephalograms. Russ Electron J Radiol. 2018;8:16-22.
10. Muraev A.A., Tsai P., Kibardin I., Oborotistov N., Shirayeva T., Ivanov S. et al. Frontal cephalometric landmarking: humans vs artificial neural networks. Int J Comput Dent. 2020;23:139-148.
11. Park J.H., Hwang H.W., Moon J.H. et al. Automated identification of cephalometric landmarks: Part 1-Comparisons between the latest deep-learning methods YOLOV3 and SSD. Angle Orthod. 2019;89(6):903-909.
12. Sun Y., Wang X., Tang X. Deep convolutional network cascade for facial point detection. Proceedings of the IEEE conference on computer vision and pattern recognition. 2013;3476-3483.
13. Yu H.J., Cho S.R., Kim M.J., Kim W.H., Kim J.W., Choi J. Automated skeletal classification with lateral cephalometry based on artificial intelligence. J Dent Res. 2020;99:249-256.
14. Zeng M., Yan Z., Liu S., Zhou Y., Qiu L. Cascaded convolutional networks for automatic cephalometric landmark detection. Med Image Anal. 2021;68:101904
Review
For citations:
Oborotistov N.Yu., Muraev A.A., Senko D.A. ViSurgery, a new online platform for 2D-cephalometric analysis using artificial intelligence. Orthodontia. 2022;(4):17-22. (In Russ.)
Views:
18
Email this article 