Patch-based convolutional neural networks for automatic landmark detection of 3D facial images in clinical settings

The automated method used in this study demonstrated accuracy comparable to that achieved with manual annotations within clinical settings. In addition, the proposed framework for automatic landmark localization exhibited improved accuracy over existing models in the literature. Despite these advancements, it is important to acknowledge the limitations of this research, such as that it was based on a single-centre study and a single annotator. Future work should address computational time challenges to achieve further enhancements. This approach has significant potential to improve the efficiency and accuracy of orthodontic and orthognathic procedures.