Segmentation Of Teeth In Panoramic X Ray Image Using U Net

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

This project aims to achieve automatic semantic segmentation and measure the total length of teeth in one-shot panoramic x-ray images. It uses a deep learning method with the U-Net Model and binary image analysis to provide diagnostic information for dental disorder management.

📋 Key Information

🚀 Quick Start

The core objective of this study is to conduct automatic semantic segmentation and measure the total length of teeth in a single panoramic x-ray image. It leverages a deep learning approach with the U-Net Model and binary image analysis. The goal is to offer diagnostic insights for the management of dental disorders, diseases, and conditions.

Github Link

📦 Dataset

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.

📚 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}
}