报告题目：3D Deep Learning for Shape Estimation in Orthognathic Surgical Planning

报告摘要

Virtual orthognathic surgical planning involves simulating surgical corrections of deformities on 3D facial bony shape models. Due to the lack of necessary guidance, the planning procedure is highly experience-dependent and the planning results are often suboptimal. A reference facial bony shape model representing normal anatomies can provide an objective guidance to improve planning accuracy. In this talk, I will introduce a series of 3D deep learning methods for automatically estimating reference facial bony shape models, and elaborate the solutions for several common problems in this topic, for example, how to apply supervised/unsupervised/self-supervised point-cloud deep learning to estimate facial bony surfaces, and how to estimate a patient-specific facial bony shape model from a 2D face photo?

嘉宾简介

肖德强，北京理工大学助理教授/特聘副研究员。2017年于中国科学院深圳先进技术研究院获得博士学位，曾在美国北卡罗莱纳大学教堂山分校从事博士后研究工作。主要从事计算机辅助手术/介入，长期专注于将计算机技术（如机器/深度学习、计算机视觉、计算机图形学等）应用于临床治疗中，包括颅额面畸形矫正手术、脑肿瘤和腹部肿瘤切除手术等。在 IEEE TMI, IEEE TBME, Physics in Medicine & Biology, IEEE JBHI, Medical Physics, MICCAI 等国际期刊和会议发表论文20余篇，其中第一作者论文10篇。参与并完成多项省部级以上科研项目，长期担任多个国际期刊及会议审稿人。

特别感谢本次Webinar主要组织者：

徐军（南京信息工程大学）