Automatic Evaluation of SMI and Bone Age Using Artificial Intelligence and Deep Learning
Lecture Description
Introduction : With the development of AI, it has been possible to evaluate the growth status of children in the growing phase by evaluating the bone age through handwrist-xray. Although the bone age evaluation, which is important in determining the evaluation of facial bone growth and treatment timing, has large inter- and intra-observer errors in growth modification orthodontics, we will apply it to clinical orthodontic treatment using the newly developed automatic SMI evaluation.
Discussion : In orthodontics, cervical vertabrae maturity, hand-wrist x-ray, height growth, secondary sexual characteristics, and many growth evaluation methods are used in clinical practice, but the application of various growth evaluation results to clinical practice is still controversial. Developed a few years ago and used for adult height prediction estimation, the verified TW3, GP method is upgraded, big data and Retina deep neural network model are used, and an artificial intelligence method that integrates analysis with a vision transformer series deep neural model is used. It was possible to obtain the Fishman's Skeletal Maturity index, which can be evaluated objectively, quickly and accurately.
Conclusion : Orthodontists can improve the quality of skeletal growth improvement treatment by using the objective SMI evaluation to identify the growth stage of the facial skeleton in growing patients and determine the timing of treatment. In addition, it is possible to explain to the patient information about the evaluation of the child's adult predicted height and early growth or growth retardation.
October 28-30, 2022 ¡¤ COEX, Seoul, Korea