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BoneX - A Multi-Bone Fracture Detection System

BoneX is an AI-powered system designed to detect various types of bone fractures in X-ray images, improving upon previous models that achieved 79% accuracy.

Features

  • Detects seven types of fractures: elbow, finger, forearm, hand, humerus, shoulder, and wrist.
  • Provides a clear diagnosis indicating whether an X-ray image shows a fracture or is normal.

Getting Started

Prerequisites

To run this application, you'll need to have Flask installed. Ensure Flask is downloaded and set up before proceeding.

Running the Application

  1. Launch the Flask server.
  2. Open the web application in your browser.
  3. Upload an X-ray image (JPEG, PNG, or JPG format) showing a potential fracture or a normal bone.
  4. Click "Submit" to receive a prediction on whether the image shows a fracture and, if so, the type of fracture detected.

Dataset

The dataset used in this project originates from Stanford University. While not publicly available, access was granted upon request.

Usage

Simply upload an X-ray image in JPEG, PNG, or JPG format, and the system will analyze it, returning a result indicating whether a fracture is present and, if applicable, identifying the type of fracture.

Contributing

Contributions make the open-source community an incredible place to learn, inspire, and create. Any contributions to BoneX are highly appreciated!

If you have suggestions for features, or if you'd like to correct or enhance documentation, feel free to:

  • Open an issue to discuss it with the maintainers.
  • Directly create a pull request after editing the README.md or any other files with necessary changes.

Please ensure that all contributions are well-formatted and grammatically correct. Create individual pull requests for each suggestion.

Creating a Pull Request

To contribute, follow these steps:

  1. Fork the project.
  2. Create your feature branch:
    git checkout -b feature/AmazingFeature
  3. Commit your changes
    git commit -m "Add some AmazingFeature"
  4. Push it to branch
    git push origin feature/AmazingFeature
  5. Open a pull request.

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