The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
A fully automatic AI system for tooth and alveolar bone segmentation from cone-beam CT images
Open accessAbstract
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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Cited by
ChatGPT for shaping the future of dentistry: the potential of multi-modal large language model
Huang, H., Zheng, O., Wang, D., Yin, J., Wang, Z., Ding, S., Yin, H., Xu, C., Yang, R., Zheng, Q., et al. (2023) · International Journal of Oral Science · doi:10.1038/s41368-023-00239-y · Cited by 324
Artificial intelligence in dentistry-a review
Ding, H., Wu, J., Zhao, W., Matinlinna, J. P., Burrow, M. F., & Tsoi, J. K. H. (2023) · Frontiers in Dental Medicine · doi:10.3389/fdmed.2023.1085251 · Cited by 297
Metadata
- Authors
- 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.
- Venue
- Nature Communications
- Published
- 2022-04-19
- Volume
- 13
- Issue
- 1
- Pages
- 2096-2096
- ISSN
- 2041-1723 (ISSN-L)
- OpenAlex
- W4224246525
- Cited by
- 348
- References
- 35
- FWCI
- 53.36
- Type
- journal article
- Language
- en
- Open access
- gold
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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. (2022). A fully automatic AI system for tooth and alveolar bone segmentation from cone-beam CT images. Nature Communications. https://doi.org/10.1038/s41467-022-29637-2
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