DICOM AI Report Generation Project

This project aims to develop an AI system that reads DICOM files and generates comprehensive reports based on the analysis of medical images. The system utilizes deep learning models to detect anomalies in medical scans and provides natural language summaries of the findings.

Project Structure

• src/: Contains the main source code for the application.

  • data/: Includes modules for preprocessing and loading DICOM files.
  • models/: Contains the image analysis and report generation models.
  • utils/: Utility functions for handling DICOM files and visualizations.
  • main.py: The entry point for the application.

• tests/: Contains unit tests for the various components of the application.

• configs/: Configuration files for model settings and parameters.

• notebooks/: Jupyter notebooks for exploratory data analysis and model development.

• requirements.txt: Lists the dependencies required for the project.

• setup.py: Used for packaging the project.

• .gitignore: Specifies files and directories to be ignored by Git.

Installation

1. Clone the repository:

   git clone <repository-url>
   cd dicom-ai-report
   

2. Install the required dependencies:

   pip install -r requirements.txt
   

Usage

1. Place your DICOM files in the appropriate directory.

2. Run the main application:

   python src/main.py
   

3. The generated reports will be saved in the specified output directory.

Contributing

Contributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.

License

This project is licensed under the MIT License. See the LICENSE file for details.