Deep Learning-Based Detection of Impacted Teeth on Panoramic Radiographs
Published in Biomedical Engineering and Computational Biology, 2024
This study fine-tunes MedSAM for impacted tooth segmentation in X-ray images, aiding dental diagnoses. We modified SAM model for individual tooth segmentation using 1016 X-ray images, achieving an accuracy of 86.73%, F1-score of 0.5350, and IoU of 0.3652.
Recommended citation: He Zhicheng, Wang Yipeng, Li Xiao. (2024). "Deep Learning-Based Detection of Impacted Teeth on Panoramic Radiographs." Biomedical Engineering and Computational Biology, 15, 11795972241288319.
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