Welcome to Radiomics.jl
Radiomics.jl is a comprehensive Julia library designed for medical imaging researchers and clinicians. Our tool enables the extraction of high-throughput quantitative features from radiological images, supporting advanced research in precision medicine and computer-aided diagnosis.
Navigate through our documentation using the sidebar to explore detailed information about feature extraction methods, installation procedures, and implementation examples.
Contribution
Radiomics.jl is an open-source project. Contributions are welcome! You can find the source code, report issues, or submit pull requests on our official GitHub repository:
Quick Start Example
Once installed, you can begin extracting radiomic features with just a few lines of code. The following example demonstrates feature extraction using sample data included with the library:
using NIfTI
using Radiomics
# Load medical image and segmentation mask
ct = niread("sample_data/CTChest.nii.gz")
mask = niread("sample_data/Lungs.nii.gz")
# Extract voxel spacing from image header
spacing = [ct.header.pixdim[2], ct.header.pixdim[3], ct.header.pixdim[4]]
# Extract radiomic features
radiomic_features = Radiomics.extract_radiomic_features(
ct.raw,
mask.raw,
spacing;
verbose = true
)
