Prediction of orthognathic surgery plan from 3D cephalometric analysis via deep learning.

ABSTRACT:

Background

Preoperative planning of orthognathic surgery is indispensable for achieving ideal surgical outcome regarding the occlusion and jaws' position. However, orthognathic surgery planning is sophisticated and highly experience-dependent, which requires comprehensive consideration of facial morphology and occlusal function. This study aimed to investigate a robust and automatic method based on deep learning to predict reposition vectors of jawbones in orthognathic surgery plan.

Methods

A regression neural network named VSP transformer was developed based on Transformer architecture. Firstly, 3D cephalometric analysis was employed to quantify skeletal-facial morphology as input features. Next, input features were weighted using pretrained results to minimize bias resulte

SUBMITTER: Cheng M 

PROVIDER: S-EPMC10024836 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature