PyRadiomics is an open-source python package for the extraction of Radiomics features from medical imaging. This package aims to establish a reference standard for Radiomics Analysis, and provide a tested and maintained open-source platform for easy and reproducible Radiomics Feature extraction. By doing so, its developers hope to increase awareness of radiomics capabilities and expand the community. The platform supports both the feature extraction in 2D and 3D and can be used to calculate single values per feature for a region of interest (“segment-based”) or to generate feature maps (“voxel-based”). The package is not intended for clinical use.
Supported Feature Classes
- First Order Statistics
- Shape-based (2D and 3D)
- Gray Level Cooccurence Matrix (GLCM)
- Gray Level Run Length Matrix (GLRLM)
- Gray Level Size Zone Matrix (GLSZM)
- Gray Level Dependece Matrix (GLDM)
- Neighboring Gray Tone Difference Matrix (NGTDM)
Supported Built-in Filter Classes:
- Laplacian of Gaussian (LoG, based on SimpleITK functionality)
- Wavelet (using the PyWavelets package)
- Square Root
- Gradient (Magnitude)
- Local Binary Pattern (LBP) 2D / 3D
Supported reproducible extraction: Aside from calculating features, the PyRadiomics package includes provenance information in the output. This information contains information on used image and mask, as well as applied settings and filters, thereby enabling fully reproducible feature extraction.
Finally, SlicerRadiomics is an extension for 3DSlicer encapsulating PyRadiomics library that calculates a variety of radiomics features. SlicerRadiomics is currently distributed as an extension via the 3DSlicer Extension Manager.
Official Website: GitHub, Radiomics.io, Sphinx
Source Code: GitHub, SlicerRadiomics
Tutorials: ReadMe, Installation Guide, Documentation Index, User’s Guide, PyRadiomics in 3DSlicer (Link 1 & Link 2), Developer’s Guide, Forum, FAQs, Release Notes, Examples
Reference Papers: Main Paper