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Determination of the Cervical Vertebra Maturation Degree from Lateral Radiography

Sciprofile linkMasrour Makaremi, Sciprofile linkCamille Lacaule, Sciprofile linkAli Mohammad-Djafari
Published: 14 January 2020
 by  MDPI
Proceedings , Volume 33; doi:10.3390/proceedings2019033030

Abstract: 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 / artificial intelligence / Orthodontics / Deep Learning / Machin Learning / cervical vertebra maturation

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