The aim of this study is automatic semantic segmentation in one-shot panoramic x-ray image by using deep learning method with U-Net Model and binary image analysis in order to provide diagnostic information for the management of dental disorders, diseases, and conditions.

The aim of this study is automatic semantic segmentation in one-shot panoramic x-ray image by using deep learning methods with U-Net Model and binary image analysis in order to provide diagnostic information for the management of dental disorders, diseases, and conditions.

The tooth numbering module classifies and numbering dental objects detected as a result of segmentation according to the FDI notation used universally by dentists.

Data set used in "A study on tooth segmentation and numbering using end-to-end deep neural networks"

Using deep learning a U-net architecture is used to make segmentation, detection, and extraction of the lower left third molar. The result of the proposed U-net is compared with Attention U-net and U-net++.