Fig. 1.

Example of a typical radiomics pipeline. Regions of interests (ROI) are created based on the neuroradiological images and binary masks are created. The corresponding radiomics features are extracted through applying predefined formulae to ROI numerical representations. A model is used to infer the output based on the input radiomics. The task for which the pipeline is implemented determines type of output. Classification, risk score assessment (regression), and survival analysis are the most common purposes of radiomics-based pipelines