A dual-labeled dataset and fusion model for automatic teeth segmentation, numbering, and state assessment on panoramic radiographs
Abstract Background Recently, deep learning has been increasingly applied in the field of dentistry. The aim of this study is to develop a model for the automatic segmentation, numbering, and state assessment of teeth on panoramic radiographs. Methods We created a dual-labeled dataset on panoramic r...
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Format: | Book |
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BMC,
2024-10-01T00:00:00Z.
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A1234.567 |
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