ShanghaiTech University Knowledge Management System
| A fully automatic AI system for tooth and alveolar bone segmentation from cone-beam CT images | |
| 2022-12-01 | |
| Source Publication | NATURE COMMUNICATIONS
 |
| EISSN | 2041-1723 |
| Volume | 13Issue:1 |
| Status | 已发表 |
| DOI | 10.1038/s41467-022-29637-2 |
| Abstract | 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. |
| URL | 查看原文 |
| Indexed By | SCIE |
| Language | 英语 |
| Scopus ID | 2-s2.0-85128405129 |
| Source Data | Scopus |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/176083 |
| Collection | 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 |
| Affiliation | 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 |
| First Author Affilication | School of Biomedical Engineering,ShanghaiTech University |
| First Signature Affilication | School of Biomedical Engineering,ShanghaiTech University |
| Recommended Citation 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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