Instructions to use SerdarHelli/Segmentation-of-Teeth-in-Panoramic-X-ray-Image-Using-U-Net with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use SerdarHelli/Segmentation-of-Teeth-in-Panoramic-X-ray-Image-Using-U-Net with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy) # See https://github.com/keras-team/tf-keras for more details. from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("SerdarHelli/Segmentation-of-Teeth-in-Panoramic-X-ray-Image-Using-U-Net") - Notebooks
- Google Colab
- Kaggle
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.
Original Dataset
DATASET ref - H. Abdi, S. Kasaei, and M. Mehdizadeh, βAutomatic segmentation of mandible in panoramic x-ray,β J. Med. Imaging, vol. 2, no. 4, p. 44003, 2015
Link DATASET for only original images.
Paper
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
- 42
Dataset used to train SerdarHelli/Segmentation-of-Teeth-in-Panoramic-X-ray-Image-Using-U-Net
Viewer β’ Updated β’ 116 β’ 165 β’ 9