Open-source python package for the extraction of Radiomics features from 2D and 3D images and binary masks. Support: https://discourse.slicer.org/c/community/radiomics

Cancer Imaging Phenomics Toolkit (CaPTk) is a software platform to perform image analysis and predictive modeling tasks. Documentation: https://cbica.github.io/CaPTk

Clinically-Interpretable Radiomics [MICCAI'22, CMPB'21]

Image processing tools for radiomics analysis

Python Implementation of the CoLlAGe radiomics descriptor. CoLlAGe captures subtle anisotropic differences in disease pathologies by measuring entropy of co-occurrences of voxel-level gradient orientations on imaging computed within a local neighborhood.

Code to Implement the Smooth Euler Characteristic Transform (SECT)

Predict survival time from PET scans

Reference MATLAB and Python implementations of the RADISTAT algorithm

Python implementation of topology descriptors which capture subtle sharpness and curvature differences along the surface of diseased pathologies on imaging.

Classification of spondylodiscitidis vs metastasis in the spine using Neural Networks

The purpose of this GitHub repository is to provide a prototype for conducting radiogenomics research, particularly focusing on the interplay between imaging features and genomic profiles in glioblastoma patients.

Calculate 43 texture features of a 2D or 3D image

Official implementation of the Fréchet Radiomics Distance | pip install frd-score

Dashboard and survival models for the TRAIN project linking Dicom, Clinical and Radiomics data

SQLite4Radiomics is a Conquest DICOM & pyradiomics integration software project