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Open AccessArticle

Deep Learning and Artificial Intelligence for the Determination of the Cervical Vertebra Maturation Degree from Lateral Radiography

1
Department of Orthodontics, University of Bordeaux, 33000 Bordeaux, France
2
International Science Consulting and Training (ISCT), 91440 Bures-sur-Yvette, France
*
Author to whom correspondence should be addressed.
Entropy 2019, 21(12), 1222; https://doi.org/10.3390/e21121222
Received: 29 September 2019 / Revised: 7 December 2019 / Accepted: 9 December 2019 / Published: 14 December 2019
Deep Learning (DL) and Artificial Intelligence (AI) tools have shown great success in different areas of medical diagnostics. In this paper, we show another success in orthodontics. In orthodontics, the right treatment timing of many actions and operations is crucial because many environmental and genetic conditions may modify jaw growth. The stage of growth is related to the Cervical Vertebra Maturation (CVM) degree. Thus, determining the CVM to determine the suitable timing of the treatment is important. In orthodontics, lateral X-ray radiography is used to determine it. Many classical methods need knowledge and time to look and identify some features. Nowadays, ML and AI tools are used for many medical and biological diagnostic imaging. This paper reports on the development of a Deep Learning (DL) Convolutional Neural Network (CNN) method to determine (directly from images) the degree of maturation of CVM classified in six degrees. The results show the performances of the proposed method in different contexts with different number of images for training, evaluation and testing and different pre-processing of these images. The proposed model and method are validated by cross validation. The implemented software is almost ready for use by orthodontists. View Full-Text
Keywords: Deep Learning (DL); Artificial Intelligence (AI); Convolutional Neural Network (CNN); classification; orthodontics; cervical vertebra maturation; machine learning Deep Learning (DL); Artificial Intelligence (AI); Convolutional Neural Network (CNN); classification; orthodontics; cervical vertebra maturation; machine learning
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Makaremi, M.; Lacaule, C.; Mohammad-Djafari, A. Deep Learning and Artificial Intelligence for the Determination of the Cervical Vertebra Maturation Degree from Lateral Radiography. Entropy 2019, 21, 1222.

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