Min-Suk Heo
서울대학교 Odontology · 치의학
헤오 민석 교수의 연구실은 구강·악면 방사선 영상과 인공지능 기반 분석을 융합한 첨단 의료 기술 개발에 주력하고 있습니다. 특히 치과 편측 방사선 영상에서 자연 치아와 치료 패턴을 자동으로 식별하는 딥러닝 기반 기술을 통해 재난 피해자 신원 확인 및 뼈의 노화 관련 변화를 정량적으로 평가하는 데 초점을 맞추고 있습니다. 연구는 한국인 대상으로 실시된 대규모 방사선 영상 데이터를 기반으로 하며, 골다공로시스 등 뼈 질환의 조기 진단 및 평가에 기여하고자 합니다.
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
Artificial intelligence, which has been actively applied in a broad range of industries in recent years, is an active area of interest for many researchers. Dentistry is no exception to this trend, and the applications of artificial intelligence are particularly promising in the field of oral and maxillofacial (OMF) radiology. Recent researches on artificial intelligence in OMF radiology have mainly used convolutional neural networks, which can perform image classification, detection, segmentati
Disaster victim identification issues are especially critical and urgent after a large-scale disaster. The aim of this study was to suggest an automatic detection of natural teeth and dental treatment patterns based on dental panoramic radiographs (DPRs) using deep learning to promote its applicability as human identifiers. A total of 1 638 DPRs, of which the chronological age ranged from 20 to 49 years old, were collected from January 2000 to November 2020. This dataset consisted of natural tee
It is important to investigate the irregularities in aging-associated changes in bone, between men and women for bone strength and osteoporosis. The purpose of this study was to characterize the changes and associations of mandibular cortical and trabecular bone measures of men and women based on age and to the evaluation of cortical shape categories, in a large Korean population. Panoramic radiographs of 1047 subjects (603 women and 444 men) aged between 15 to 90 years were used. Mandibular cor
