Journal of clinical and experimental dentistry · 2024
Artificial Neural Network-Assisted Facial Analysis for Planning of Orthognathic Surgery.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Barbosa Lívia Mirelle, Silva Joana de Ângelis Alves, da Silva José Ivson Soares, Ren Tsang Ing, Vasconcelos Belmiro Cavalcanti do Egito, Filho José Rodrigues Laureano
Аннотация
BACKGROUND: Facial analysis for orthognathic surgery aims to identify facial features and determine how occlusion should be corrected to achieve facial balance. Several artificial neural networks have been developed to detect facial landmarks; however, no publications have reported the application of neural networks to measure facial proportions specifically for orthognathic surgery planning. Objectives: To develop a computer program that automates facial measurements through photograph capture, as well as to present the development stages of the program and the test results evaluating its effectiveness.
MATERIAL AND METHODS: Researchers from the Postgraduate Program in Oral and Maxillofacial Surgery at the University of Pernambuco (UPE), in collaboration with researchers from the IT Center at the Federal University of Pernambuco (UFPE), developed a computer program to automate facial measurements through photographic capture.
RESULTS: The developed program successfully detected nine measurements: (M1) middle third of the face, (M2) lower third, (M3) intercanthal distance, (M4) alar base, (M5) upper lip, (M6) upper lip vermilion, (M7) lower lip, (M8) lower lip vermilion, and (M9) interlabial gap. Of these measurements, only two showed significant discrepancies (p<0.01) compared to the actual size in both versions of the program. These discrepancies referred to the middle third of the face and the lower lip vermilion.
CONCLUSIONS: The developed program can be considered effective, as it automatically detected seven facial measurements relevant to orthognathic surgery. However, this line of research must be continued to create a larger database and train the network more robustly, increasing its ability to detect more facial landmarks and allowing the automated acquisition of additional measurements important for orthognathic surgery planning. Key words:Dentofacial deformities, maxillofacial abnormalities, orthognathic surgery, artificial intelligence, software.
MATERIAL AND METHODS: Researchers from the Postgraduate Program in Oral and Maxillofacial Surgery at the University of Pernambuco (UPE), in collaboration with researchers from the IT Center at the Federal University of Pernambuco (UFPE), developed a computer program to automate facial measurements through photographic capture.
RESULTS: The developed program successfully detected nine measurements: (M1) middle third of the face, (M2) lower third, (M3) intercanthal distance, (M4) alar base, (M5) upper lip, (M6) upper lip vermilion, (M7) lower lip, (M8) lower lip vermilion, and (M9) interlabial gap. Of these measurements, only two showed significant discrepancies (p<0.01) compared to the actual size in both versions of the program. These discrepancies referred to the middle third of the face and the lower lip vermilion.
CONCLUSIONS: The developed program can be considered effective, as it automatically detected seven facial measurements relevant to orthognathic surgery. However, this line of research must be continued to create a larger database and train the network more robustly, increasing its ability to detect more facial landmarks and allowing the automated acquisition of additional measurements important for orthognathic surgery planning. Key words:Dentofacial deformities, maxillofacial abnormalities, orthognathic surgery, artificial intelligence, software.