AI accurate alternative to manual techniques for facial anthropometric measurements in prosthodontics: Study
Artificial Intelligence accurate alternative to manual techniques for facial anthropometric measurements in prosthodontics suggests a study published in the Journal of Prosthetic Dentistry.
Information regarding facial landmark measurement using machine learning (ML) techniques in prosthodontics is lacking. The objective of this study was to evaluate and compare the reliability, validity, and accuracy of facial anthropological measurements using both manual and ML landmark detection techniques. Two-dimensional (2D) frontal full-face photographs of 50 men and 50 women were made. The interpupillary width (IPW), interlateral canthus width (LCW), intermedial canthus width (MCW), interalar width (IAW), and intercommissural width (ICW) were measured on 2D digital images using manual and ML methods. The automated measurements were recorded using a programming language (Python), and a convolutional neural network (CNN) model was trained to detect human facial landmarks.
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