This repository contains a DICOM AI Service on creni.org designed to monitor a specified directory for DICOM files. When a new DICOM file is added to the INPUT directory via your gateway(s), the service automatically processes the file, modifying descriptions and adding custom text to the image before saving it to the OUTPUT directory. In production deployment, the all DICOM files in OUTPUT will only try one time to send to your desired PACS destinations configured in creni.org website.

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├── Dockerfile  # Dockerfile for building the Docker image
├── INPUT   # Directory to monitor for input DICOM files
│   ├── gateway_1  # input files by gateway_{id} where {id} is 1
│   │   ├── 1.2.276.0.7230010.3.1.2.330040832.1.1707350883.230569 # StudyInstanceUID
│   │   │   ├── 1.2.276.0.7230010.3.1.4.330040832.1.1707350883.230571 # SOPInstanceUID
│   │   │   ├── 1.2.276.0.7230010.3.1.4.330040832.1.1707350883.230572
│   │   │   └── 1.2.276.0.7230010.3.1.4.330040832.1.1707350883.230573
│   │   └── image.db # DICOM SQLite database to store tags
│   └── gateway_2  # input files by gateway_{id} where {id} is 2
│       ├── 1.2.276.0.7230010.3.1.2.330040832.1.1707350883.230569 # StudyInstanceUID
│       │   ├── 1.2.276.0.7230010.3.1.4.330040832.1.1707350883.230571  # SOPInstanceUID
│       │   ├── 1.2.276.0.7230010.3.1.4.330040832.1.1707350883.230572
│       │   └── 1.2.276.0.7230010.3.1.4.330040832.1.1707350883.230573
│       └── image.db # DICOM SQLite database to store tags
├── OUTPUT  # Directory where processed files will be saved
│   ├── gateway_1   # output files to gateway_{id} where {id} is 1. Output files must be DICOM format with any names.
│   │   ├── output.230571
│   │   ├── output.230572
│   │   └── output.230573
│   └── gateway_2   # output files to gateway_{id} where {id} is 2. Output files must be DICOM format in subfolders.
│       └── 1.2.276.0.7230010.3.1.2.330040832.1.1707350883.230569
│           ├── 1.2.276.0.7230010.3.1.4.330040832.1.1707350883.230571
│           ├── 1.2.276.0.7230010.3.1.4.330040832.1.1707350883.230572
│           └── 1.2.276.0.7230010.3.1.4.330040832.1.1707350883.230573
├── README.md   # Project documentation
├── development.sh  # Script to run the Docker Compose environment
├── docker-compose-development.yml  # Docker Compose configuration for development
├── main.py  # Main python script for the DICOM Watchdog Service
└── requirements.txt # Python dependencies for the project

DICOM SQLite database to store DICOM tags. Database schemma follows:

Ensure you have the following installed on your system:

• Docker
• Docker Compose

git clone https://github.com/PotatoThanh/creni.org.git
cd creni.org

In docker-compose-development.yml, Docker service maps:

• ./INPUT:/app/INPUT maps ./INPUT at your local machine to /app/INPUT inside docker service. We will change ./INPUT accordingly in our CLOUD.
• ./OUTPUT:/app/OUTPUT maps ./OUTPUT at your local machine to /app/OUTPUT inside docker service. We will change ./OUTPUT accordingly in our CLOUD.

To quickly start the development environment, use the provided development.sh script:

./development.sh

This script will:

• Stop any running Docker Compose services.
• Build and start the containers defined in docker-compose-development.yml.

Each gateway desktop application will be assigned gateway_{id} (e.g., gateway_1). {id} is unique for each gateway. You can only see your gateways. Once the environment is up and running:

• In development, place your DICOM files into the INPUT/gateway_{id} directory. In production, all DICOM files sent via your gateway(s) will appear in the INPUT/gateway_{id} folder.
• In development, the processed DICOM files will be automatically saved in the OUTPUT/gateway_{id} directory. In production, all DICOM files from the OUTPUT/gateway_{id} folder will transfer to your desired PACS destinations in creni.org website.

To stop the running service, simply press Ctrl+C in the terminal where the service is running or use the following command:

docker compose -f docker-compose-development.yml down

The Dockerfile is used to create a Docker image with Python 3.9 and all the necessary dependencies installed, including opencv for image processing.

This file defines the services needed for the development environment. You can modify the volume mappings, environment variables, or other configurations as needed.

The main.py script is the core of the DICOM Docker Service. It monitors the INPUT/gateway_{id} directory for new DICOM files, processes them, and saves the output in the OUTPUT/gateway_{id} directory. You can customize the processing logic by modifying the process_dicom, modify_descriptions, and add_text_to_image functions as well as your AI interence model.

If you need to install additional Python dependencies, add them to requirements.txt and rebuild the Docker image.

Contributions are welcome! Please submit a pull request or open an issue if you have suggestions or find a bug.