The purpose of this project is to automate the radiomics workflow and find the best composition of features, settings and parameters that can be used in order to achieve the best performance. Performance can be measured with some specific metrics (like accuracy or AUC) after our AI model has been trained.

This is a whole workflow of radiomics。

This project contains a series of Python scripts for extracting radiomics features from medical imaging data and performing clustering analysis and evaluation. The scripts cover the entire workflow from feature extraction to clustering metric calculation.

This project contains a series of Python scripts for extracting radiomics features from medical imaging data and performing clustering analysis and evaluation. The scripts cover the entire workflow from feature extraction to clustering metric calculation.

This project contains a series of Python scripts for extracting radiomics features from medical imaging data and performing clustering analysis and evaluation. The scripts cover the entire workflow from feature extraction to clustering metric calculation.