ices of the corresponding FC layer, and 1 is a column vector with all elements as 1.
To accomplish malignancy prediction using mpMRI, an ensemble learning approach is employed to fuse the predictions of the three separated models (w.r.t T2, ADC, and hDWI). We train the classifier module, as inFigure 4 , using labeled source data. The FC layers in the source domain are employed, not only for cross-domain feature affinity, but also for malignancy classification. The cross-entropy loss is utilized to optimize the classifier module. Our classification loss can be defined as: