软体机器人研究中心团队成员参加2023年第十届医学图像计算青年研讨会（MICS 2023）并作学术报告

[2023-07-16]

2023年第十届医学图像计算青年研讨会7月14-17日在山西太原潇河国际会议中心召开。本次会议聚焦医学图像计算领域的最新原创、前沿研究，促进本领域专家学者交流合作。实验室团队博士研究生Uroosa Sehar参会并作题为“Dental Image Processing for Precision Orthodontic Treatment”学术报告，介绍了团队人工智能辅助精准口腔正畸诊疗的相关研究概况。
报告摘要：Oral health has continued to be recognized as a vital component of health. Malocclusion, a common condition affecting the alignment of the oral cavity, affects not only the aesthetics of the face but also can be a cause of other chronic disease. Automatic tooth segmentation is a fundamental process for orthodontic diagnosis and treatment planning, however the manual methods in clinics are very time-consuming and labor intensive. With the breakthrough point of "Precision Orthodontic Diagnosis and Treatment" based on robotics and computational biomechanics, we have ultimately promoted the transformation of current clinical orthodontic diagnosis and treatment as precision orthodontics.

In this talk, we will systematically introduce the computer-aided algorithms for tooth segmentation and reconstruction from various types of CBCTs obtained in different application scenarios for clinical orthodontic treatment. Specifically, to analyze the existing traditional methods of CBCT segmentation and use the level set method as an example to illustrate the basic framework of tooth segmentation. Then, we will elaborate on the segmentation methods of teeth in conventional scanning CT images, metal artifact CT images, and closed-mouth scanning CT images. Additionally, the deep learning-based methods for automatic tooth segmentation from CBCT images will be introduced. Finally, we will discuss the method of reconstructing corresponding models using the segmented oral tissue contours, as well as a tooth model reconstruction method based on the fusion of oral CT images and laser scanning images.