AIM-Harvard/pyradiomics

Health v2 · maintenance only

Adoption not part of the score

1441 stars · 551 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

PyRadiomics is an open-source Python package for extracting radiomics features from 2D and 3D medical images and binary masks. It provides a tested, reproducible reference standard for radiomic analysis with segment-based and voxel-based feature computation.

Use cases

• extract radiomics features from medical images
• compute shape and texture features from tumor segmentations
• reproducible radiomic feature extraction for cancer research
• generate voxel-based feature maps from 3D scans
• apply wavelet and LoG filters before feature extraction
• quantify tumor phenotype from CT or MRI masks

When to choose

• you need IBSI-compliant radiomic features in Python
• you want reproducible feature extraction with provenance info
• you work with 2D/3D medical images and binary masks
• you need a maintained reference standard for radiomics research

When to avoid

• you need clinically validated software for patient care
• you need general-purpose image features for natural images
• you need deep-learning-based feature extraction rather than handcrafted features

Facets

library · maturity active

image-processing data-science machine-learning healthcare data-science machine-learning python cross-platform radiomics feature-extraction medical-imaging cancer-imaging ibsi simpleitk segmentation research docker

Member repositories

For agents

markdown · JSON · MCP: product_card(name="AIM-Harvard/pyradiomics")