Streamlit Teeth Segmentation

What is Streamlit Teeth Segmentation ?

Streamlit Teeth Segmentation is an AI-powered tool designed for medical imaging applications, specifically for segmenting teeth in X-ray images. It leverages the Streamlit framework to provide a user-friendly web interface where users can upload X-ray images and receive accurate tooth segmentation results in real-time. This tool is particularly useful for dental professionals and researchers who need to analyze dental structures efficiently.

Features

• AI-Powered Segmentation: Utilizes advanced machine learning models to precisely identify and segment teeth in X-ray images.
• Real-Time Processing: Provides fast and accurate results immediately after image upload.
• User-Friendly Interface: Streamlit's intuitive interface ensures ease of use for both technical and non-technical users.
• Visualization Tools: Includes features to highlight and visualize segmented teeth for better analysis.
• Cross-Platform Compatibility: Can be run on various operating systems with minimal setup.

How to use Streamlit Teeth Segmentation ?

1. Install Required Packages: Run pip install streamlit and install any additional dependencies specified in the project documentation.
2. Clone the Repository: Download the Streamlit Teeth Segmentation codebase from the official repository.
3. Run the App: Execute the Streamlit app using streamlit run your_app_script.py.
4. Upload an X-ray Image: Use the interface to upload a dental X-ray image for analysis.
5. Process the Image: Click the "Process" button to initiate the segmentation.
6. View Results: The app will display the original image alongside the segmented teeth, highlighting the results for easy interpretation.
7. Export Results: Save the segmented image or data for further analysis or reporting.

Frequently Asked Questions

1. What formats of X-ray images are supported?
Streamlit Teeth Segmentation supports common medical image formats such as DICOM, PNG, and JPEG. Ensure your images are in one of these formats for proper processing.

2. Can the app handle low-quality X-ray images?
While the app is designed to work with various image qualities, best results are achieved with high-resolution X-rays. Low-quality images may result in less accurate segmentation.

3. Is the app suitable for real-time clinical use?
The app is primarily intended for research and diagnostic assistance. Always consult a professional for clinical decisions, as the tool should not replace expert judgment.