dentist

Semantic-Segmentation-of-Teeth-in-Panoramic-X-ray-Image

The aim of this study is automatic semantic segmentation and measurement total length of teeth 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.

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Original Dataset

DATASET ref - H. Abdi, S. Kasaei, and M. Mehdizadeh, “Automatic segmentation of mandible in panoramic x-ray,” J. Med. Imaging, vol. 2, no. 4, p. 44003, 2015

Link DATASET for only original images.

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Examples of Model's Outputs

<img src="https://github.com/SerdarHelli/Semantic-Segmentation-of-Teeth-in-Panoramic-X-ray-Image/blob/master/Viewing_Estimations/Figures/example.png" alt="Results" width="1024" height="512">

Example of Final Output

<img src="https://github.com/SerdarHelli/Semantic-Segmentation-of-Teeth-in-Panoramic-X-ray-Image/blob/master/Viewing_Estimations/Figures/exampleofcca.png" alt="Results" width="1024" height="512">

Architecture.

<img src="https://github.com/SerdarHelli/Semantic-Segmentation-of-Teeth-in-Panoramic-X-ray-Image/blob/master/Viewing_Estimations/Figures/Architecture.png" alt="Results" width="1024" height="512">

Paper

The authors of this article are Selahattin Serdar Helli and Andaç Hamamcı with the Department of Biomedical Engineering, Faculty of Engineering, Yeditepe University, Istanbul, Turkey

BibTeX Entry and Citation Info

@article{helli10tooth,
 title={Tooth Instance Segmentation on Panoramic Dental Radiographs Using U-Nets and Morphological Processing},
 author={HELL{\.I}, Serdar and HAMAMCI, Anda{\c{c}}},
 journal={D{\"u}zce {\"U}niversitesi Bilim ve Teknoloji Dergisi},
 volume={10},
 number={1},
 pages={39--50}
}