Prediction of lymphovascular invasion in rectal cancer based on multimodal magnetic resonance imaging radiomics model

Figure 3 Radiomics feature selection process. Feature-reduction pipeline across three magnetic resonance imaging sequences (fat-suppressed T2-weighted imaging, diffusion-weighted imaging, T1-weighted contrast-enhanced imaging). Bars show the number of radiomic features remaining after each filtering step: Initial extraction, intraclass correlation coefficient thresholding, variance filtering, correlation filtering, univariate selection, and least absolute shrinkage and selection operator regression. FS-T2WI: Fat-suppressed T2-weighted imaging; DWI: Diffusion-weighted imaging; T1CE: T1-weighted contrast-enhanced imaging; ICC: Intraclass correlation coefficient; LASSO: Least absolute shrinkage and selection operator.