Performance of DL model
Using the siamese neural network, 4096 deep learning features were extracted from each patient’s images, which included traditional US images and SMI images. Feature selection pipeline was performed using the same steps as radiomics analysis, and the most significant deep learning features were selected. Ultimately, seven deep features were selected to build the deep learning model (Spearman correlation coefficients were calculated for the 7 selected features in DL model, and their respective coefficient values. The longer x-axis variables of individual feature denoted that it played the more important role in the model.