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| title: AI In Dentistry | |
| emoji: 📉 | |
| colorFrom: gray | |
| colorTo: indigo | |
| sdk: gradio | |
| sdk_version: 4.44.0 | |
| app_file: app.py | |
| pinned: false | |
| license: mit | |
| AI in Dentistry Advancing Imaging and Clinical Transcription | |
| This repository contains the code for AI Dentistry application. The application is based on three models: | |
| 1. **Calculus and Caries Detection**: This model is based on the VGG architecture and is trained on the [Dental Condition Dataset](https://www.kaggle.com/datasets/salmansajid05/oral-diseases/data). | |
| 2. **Caries Detection**: This model performs caries detection using Yolov8 model. This model is sourced from the [Yolov8 Caries Detector](https://github.com/AndreyGermanov/yolov8_caries_detector). | |
| 3. **Dental Image Segmentation**: This model performs semantic segmentation in one-shot panoramic x-ray image by using deep learning method with U-Net Model. The model is sourced from [Segmentation-of-Teeth-in-Panoramic-X-ray-Image-Using-U-Net](https://github.com/SerdarHelli/Segmentation-of-Teeth-in-Panoramic-X-ray-Image-Using-U-Net). | |