RACLAHE_Image_Enhancement_for_CNN_model_segmentation

RACLAHE Quick Start Guide

Prerequisites

Step 1: Prepare Your Data

Organize your medical images in folders:

input/
├── patient001/
│   ├── slice001.dcm
│   ├── slice002.dcm
│   └── ...
├── patient002/
│   └── scan.nii.gz
└── ...

Each patient folder should contain either:

Step 2: Run with Docker Compose

# Clone the repository
git clone <repository-url>
cd RACLAHE_Image_Enhancement_for_CNN_model_segmentation

# Create directories
mkdir -p input output shared

# Copy your patient data into input/
cp -r /path/to/your/patients/* input/

# Run processing
docker-compose up --build

Step 3: Get Results

Enhanced images will be saved in:

output/RACLAHE OUTPUT/
├── patient001/
│   ├── image_1.dcm
│   ├── image_2.dcm
│   └── ...
└── patient002/
    └── patient002.nii.gz

Alternative: Run with Docker (without Compose)

# Build image
docker build -t raclage:3.0 .

# Run with volumes
docker run \
  -v $(pwd)/input:/home/ds/datasets:ro \
  -v $(pwd)/output:/home/ds/persistent-home \
  raclage:3.0

EUCAIM Platform

On EUCAIM, volumes are automatically mounted:

Simply deploy the image and it will process all patients in the datasets directory.


Configuration

Override paths using environment variables:

docker run \
  -e INPUT_DIR=/custom/input \
  -e OUTPUT_DIR=/custom/output \
  -v $(pwd)/input:/custom/input:ro \
  -v $(pwd)/output:/custom/output \
  raclage:3.0

Troubleshooting

No output generated

Permission errors

Processing fails


Support

For issues or questions: