Fig. 2
Flow chart of this study. First, the largest MR image of the RC lesion, obtained through the T2WI, DWI, and T1C sequence models, was selected. A rectangular region of interest (ROI) covering the lesion was chosen. Second, the ResNet-101 network was employed for feature extraction. A series of operations, including convolution, pooling, and residual connection, were performed to obtain the DL features of the fully connected layers. mRMR and Lasso regression were used to screen for highly collinear features. Third, the coefficients of each deep feature were calculated using logistic regression, completing the construction of the DL model. Subsequently, the physician model was integrated with the DLRS model to create a nomogram model. Forth, clinical application of models.
