A radiomics-based machine learning pipeline to distinguish between metastatic and healthy bone using lesion-center-based geometric regions of interest; dataset

`output` is a folder containing the results of our radiomic-based machine learning pipeline in differentiating between healthy bone (HB) and bone metastases (BM) lesions. The pipeline was trained and tested using several resampling techniques (RS), feature selection methods (FS), and machine learning classifiers (ML) on single-point-based geometric ROIs with various shapes and sizes.