Edit model card

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.

Github Link

Original Dataset

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

Link DATASET for only original images.

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}
}
Downloads last month
54
Inference Examples
Inference API (serverless) does not yet support tf-keras models for this pipeline type.

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

Spaces using SerdarHelli/Segmentation-of-Teeth-in-Panoramic-X-ray-Image-Using-U-Net 34