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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.

Github Link

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.


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

 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},
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Dataset used to train SerdarHelli/Segmentation-of-Teeth-in-Panoramic-X-ray-Image-Using-U-Net

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