Fig. 5. Schematic description of development process for radiomics classification model.

Model for staging liver fibrosis using gadoxetic acid-enhanced hepatobiliary phase magnetic resonance images is assumed for demonstration purposes. Input images undergo preprocessing, including normalization of gray-scale pixel values and image resampling to standardize image resolution. Radiomics features are then extracted, which may include shape, histogram, texture, and high-order features. Feature selection is performed to reduce feature dimension, and classification model is then developed using selected radiomics features. Final radiomics model is used for classification of new input images. LASSO = least absolute shrinkage and selection operator