Suppr超能文献

正颌外科中的面部对称性量化:一种整合 3D 轮廓图和高维计算的新方法。

Quantification of facial symmetry in orthognathic surgery: A novel approach integrating 3D contour maps and hyper-dimensional computing.

机构信息

Division of Orthodontics, Department of Dentistry, Chang Gung Memorial Hospital, Chang Gung University, Taoyuan, Taiwan.

Department of Plastic and Reconstructive Surgery and Craniofacial Research Center, Chang Gung Memorial Hospital, Chang Gung University, Taoyuan, Taiwan.

出版信息

Comput Biol Med. 2024 Dec;183:109189. doi: 10.1016/j.compbiomed.2024.109189. Epub 2024 Oct 5.

Abstract

This study aimed to enhance the evaluation of facial symmetry crucial for planning and assessing outcomes of orthognathic surgery (OGS). An innovative approach combining three-dimensional (3D) facial contour lines with hyperdimensional (HD) computing was developed for this purpose. Data were collected using 3D cone beam computed tomography (CBCT) at Chang Gung Memorial Hospital from 2016 to 2021. A comprehensive dataset was compiled, including images from 150 normal individuals and 2500 patients, totaling 5150 preoperative and postoperative facial images. A machine learning model was trained to analyze these images, and 3D contour data were used to create a facial symmetry quantification system with HD computing. Additionally, 3D CBCT data from 200 patients before and after OGS were retrospectively reviewed for clinical application. The developed facial symmetry algorithm demonstrated an overall accuracy of 84.1 %. Postoperative facial symmetry scores improved significantly, with a mean score increase of 53 %, from 2.40 to 3.63. The study culminated in the creation of a web-based system that leverages HD computing and 3D contour mapping to automate facial symmetry assessment. This system offers a user-friendly interface for rapid and accurate evaluations, facilitating better communication between clinicians and patients.

摘要

本研究旨在提高对正颌手术(OGS)规划和评估结果至关重要的面部对称性评估。为此,开发了一种将三维(3D)面部轮廓线与超高维(HD)计算相结合的创新方法。数据是 2016 年至 2021 年期间在长庚纪念医院使用 3D 锥形束 CT(CBCT)收集的。编制了一个综合数据集,包括 150 名正常个体和 2500 名患者的图像,共 5150 张术前和术后面部图像。训练了一个机器学习模型来分析这些图像,并使用 3D 轮廓数据通过 HD 计算创建一个面部对称性量化系统。此外,还回顾性地审查了 200 名接受 OGS 前后的患者的 3D CBCT 数据,以进行临床应用。开发的面部对称算法的总体准确性为 84.1%。术后面部对称性评分显著提高,平均评分从 2.40 增加到 3.63,增加了 53%。研究最终创建了一个基于网络的系统,该系统利用 HD 计算和 3D 轮廓映射来实现面部对称性自动评估。该系统提供了一个用户友好的界面,可实现快速准确的评估,促进了临床医生和患者之间的更好沟通。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验