This is a complete guide on how to do Pyradiomics based feature extraction and then, build a model to calculate the grade of glioma.

Extract and evaluate radiomics for liver cancer tumors from DICOM segmentation masks. Using SimpleITK, PyRadiomics and PyDicom.

Open source of Pyradiomics extension

A complete radiomics feature selection pipeline for binary classification tasks

Predict survival time from PET scans

Ontology-guided Radiomics Analysis Workflow (O-RAW)

This repository contains a deep learning-based cancer type prediction system using a trained convolutional neural network (CNN). The model is deployed using Streamlit, allowing users to upload medical images and receive predictions with a probability distribution displayed in a pie chart.

This script reads DICOM files in a source directory or in a list of source directories and searches for the patients in the given patients' list creates a DICOM DataBase in the destination directory, copies the files, and creates a DicomDataBase.csv file and a summary.txt file.

Lung Cancer Detection using CT Scans.

Radiomics-based feature extraction pipeline for the HEST dataset using PyRadiomics and CellViT, supporting intensity, texture, cell-shape, and cell-composition descriptors.

Lung Cancer Classification with CT Scans [Labs of AI and DS Course Project]

Workflow for Optimal Radiomics Classification, WORC toolbox.

A comprehensive pipeline for the analysis of dynamic contrast-enhanced MRI (DCE-MRI) data from the MAMA-MIA public dataset. Includes biomarker extraction, pseudo-color map generation, and multicenter signal harmonization using ComBat. Developed for educational purposes at the Hellenic Mediterranean University by Kalaitzakis Nikolaos.

GSoC 2026 ML4Sci PREDICT2 evaluation submission — radiomics feature extraction for coronary calcium phenotyping

Quantitative Analysis of Chromatin Organization in Neuroendocrine Lung Cancer using PyRadiomics and StarDist. This project leverages advanced image processing techniques to segment cell nuclei and extract detailed radiomic features from small-cell and large-cell neuroendocrine lung cancers.

Repository for CoRa, a CLI which can extract radiomics from COVID-19 CT scans.

A leakage-free ML pipeline for early pancreatic cancer detection from CT scans — combining handcrafted radiomics (PyRadiomics, ComBat) with volumetric deep learning (3D ResNet-10, MONAI) and explainable AI (SHAP, Grad-CAM).

I extracted the tumor features according to the data annotation of all four stages of 3D MRI data. And I deployed Graph Neural Networks based on important features such as First Order Statistics, Shape-based (3D), Shape-based (2D), GLCM, GLRLM, GLSZN, NGTDM, and GLDM.

Radiomics pipeline for extracting and analyzing breast imaging features using PyRadiomics and the CBIS-DDSM dataset.