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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.

License: GNU Affero General Public License v3.0

Python 6.76% Jupyter Notebook 93.24%

segmentation-of-teeth-in-panoramic-x-ray-image's Introduction

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.

Try Demo App On Hugging Face

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.

Having Basic Usage , You can train your own model with Main.ipynb, Just Run Click

Examples of Model's Outputs

Results

Example of Final Output

Results

Architecture.

Results

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}
}

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