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Open AccessProceedings

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), 10 rue de Montjay, 91440 Bures-sur-Yvette, France
*
Author to whom correspondence should be addressed.
Presented at the 39th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, Garching, Germany, 30 June–5 July 2019.
Proceedings 2019, 33(1), 30; https://doi.org/10.3390/proceedings2019033030
Published: 14 January 2020
Many environmental and genetic conditions may modify jaws growth. In orthodontics, the right treatment timing is crucial. This timing is a function of the Cervical Vertebra Maturation (CVM) degree. Thus, determining the CVM is important. In orthodontics, the lateral X-ray radiography is used to determine it. Many classical methods need knowledge and time to look and identify some features to do it. Nowadays, Machine Learning (ML) and Artificial Intelligent (AI) tools are used for many medical and biological image processing, clustering and classification. This paper reports on the development of a Deep Learning (DL) method to determine directly from the images the degree of maturation of CVM classified in six degrees. Using 300 such images for training and 200 for evaluating and 100 for testing, we could obtain a 90% accuracy. The proposed model and method are validated by cross validation. The implemented software is ready for use by orthodontists.
Keywords: classification; orthodontics; Cervical Vertebra Maturation; Machin Learning; Artificial Intelligence; Deep Learning classification; orthodontics; Cervical Vertebra Maturation; Machin Learning; Artificial Intelligence; Deep Learning
MDPI and ACS Style

Makaremi, M.; Lacaule, C.; Mohammad-Djafari, A. Determination of the Cervical Vertebra Maturation Degree from Lateral Radiography. Proceedings 2019, 33, 30.

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