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Zhiming Cui, Yu Fang, Lanzhuju Mei, Bojun Zhang, Bo Yu, Jiameng Liu, Caiwen Jiang, Yuhang Sun, Lei Ma, Jiawei Huang and 6 more
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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Cui, Z., Fang, Y., Mei, L., Zhang, B., Yu, B., Liu, J., Jiang, C., Sun, Y., Ma, L., Huang, J., Liu, Y., Zhao, Y., Lian, C., Ding, Z., Zhu, M., & Shen, D. G. (2022). A fully automatic AI system for tooth and alveolar bone segmentation from cone-beam CT images. Nature Communications, 13(1), 2096. https://doi.org/10.1038/s41467-022-29637-2
Cui, Zhiming, et al. "A fully automatic AI system for tooth and alveolar bone segmentation from cone-beam CT images." Nature Communications, vol. 13, no. 1, 2022, pp. 2096, https://doi.org/10.1038/s41467-022-29637-2.
Cui, Zhiming, Yu Fang, Lanzhuju Mei, Bojun Zhang, Bo Yu, Jiameng Liu, Caiwen Jiang, et al. "A fully automatic AI system for tooth and alveolar bone segmentation from cone-beam CT images." Nature Communications 13, no. 1 (2022): 2096. https://doi.org/10.1038/s41467-022-29637-2.
Cui Z., Fang Y., Mei L. [и др.] A fully automatic AI system for tooth and alveolar bone segmentation from cone-beam CT images // Nature Communications. — 2022. — Vol. 13, № 1. — P. 2096. — URL: https://doi.org/10.1038/s41467-022-29637-2
@article{cui2022fully,
title = {{A fully automatic AI system for tooth and alveolar bone segmentation from cone-beam CT images}},
author = {Zhiming Cui and Yu Fang and Lanzhuju Mei and Bojun Zhang and Bo Yu and Jiameng Liu and Caiwen Jiang and Yuhang Sun and Lei Ma and Jiawei Huang and Yang Liu and Yue Zhao and Chunfeng Lian and Zhongxiang Ding and Min Zhu and Dinggang G. Shen},
journal = {Nature Communications},
year = {2022},
volume = {13},
number = {1},
pages = {2096},
doi = {10.1038/s41467-022-29637-2},
url = {https://doi.org/10.1038/s41467-022-29637-2}
}TY - JOUR AU - Cui, Zhiming AU - Fang, Yu AU - Mei, Lanzhuju AU - Zhang, Bojun AU - Yu, Bo AU - Liu, Jiameng AU - Jiang, Caiwen AU - Sun, Yuhang AU - Ma, Lei AU - Huang, Jiawei AU - Liu, Yang AU - Zhao, Yue AU - Lian, Chunfeng AU - Ding, Zhongxiang AU - Zhu, Min AU - Shen, Dinggang G. TI - A fully automatic AI system for tooth and alveolar bone segmentation from cone-beam CT images JO - Nature Communications VL - 13 IS - 1 SP - 2096 PY - 2022 DA - 2022/04/19 DO - 10.1038/s41467-022-29637-2 UR - https://doi.org/10.1038/s41467-022-29637-2 ER -
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