A fully automatic AI system for tooth and alveolar bone segmentation from cone-beam CT images
Cui, Zhiming1,2,3; Fang, Yu1; Mei, Lanzhuju1; Zhang, Bojun4; Yu, Bo5; Liu, Jiameng1; Jiang, Caiwen1; Sun, Yuhang1; Ma, Lei1; Huang, Jiawei1
2022-12-01
发表期刊NATURE COMMUNICATIONS
EISSN2041-1723
卷号13期号:1
发表状态已发表
DOI10.1038/s41467-022-29637-2
摘要Accurate delineation of individual teeth and alveolar bones from dental cone-beam CT (CBCT) images is an essential step in digital dentistry for precision dental healthcare. In this paper, we present an AI system for efficient, precise, and fully automatic segmentation of real-patient CBCT images. Our AI system is evaluated on the largest dataset so far, i.e., using a dataset of 4,215 patients (with 4,938 CBCT scans) from 15 different centers. This fully automatic AI system achieves a segmentation accuracy comparable to experienced radiologists (e.g., 0.5% improvement in terms of average Dice similarity coefficient), while significant improvement in efficiency (i.e., 500 times faster). In addition, it consistently obtains accurate results on the challenging cases with variable dental abnormalities, with the average Dice scores of 91.5% and 93.0% for tooth and alveolar bone segmentation. These results demonstrate its potential as a powerful system to boost clinical workflows of digital dentistry.
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收录类别SCIE
语种英语
Scopus 记录号2-s2.0-85128405129
来源库Scopus
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文献类型期刊论文
条目标识符https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/176083
专题生物医学工程学院
物质科学与技术学院_特聘教授组_孙予罕组
信息科学与技术学院_硕士生
信息科学与技术学院_博士生
生物医学工程学院_PI研究组_沈定刚组
生物医学工程学院_PI研究组_崔智铭组
作者单位1.School of Biomedical Engineering,ShanghaiTech University,Shanghai,201210,China
2.Department of Computer Science,The University of Hong Kong,999077,Hong Kong
3.Shanghai United Imaging Intelligence Co.,Ltd.,Shanghai,200030,China
4.Shanghai Ninth People’s Hospital,Shanghai Jiao Tong University,Shanghai,200011,China
5.School of Public Health,Hangzhou Medical College,Hangzhou,310013,China
6.Department of Orthodontics,Stomatological Hospital of Chongqing Medical University,Chongqing,401147,China
7.School of Communication and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing,400065,China
8.School of Mathematics and Statistics,Xi’an Jiaotong University,Xi’an,710049,China
9.Department of Radiology,Hangzhou First People’s Hospital,Zhejiang University,Hangzhou,310006,China
第一作者单位生物医学工程学院
第一作者的第一单位生物医学工程学院
推荐引用方式
GB/T 7714
Cui, Zhiming,Fang, Yu,Mei, Lanzhuju,et al. A fully automatic AI system for tooth and alveolar bone segmentation from cone-beam CT images[J]. NATURE COMMUNICATIONS,2022,13(1).
APA Cui, Zhiming.,Fang, Yu.,Mei, Lanzhuju.,Zhang, Bojun.,Yu, Bo.,...&Shen, Dinggang.(2022).A fully automatic AI system for tooth and alveolar bone segmentation from cone-beam CT images.NATURE COMMUNICATIONS,13(1).
MLA Cui, Zhiming,et al."A fully automatic AI system for tooth and alveolar bone segmentation from cone-beam CT images".NATURE COMMUNICATIONS 13.1(2022).
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