Figure 2.

Overview of weakly-supervised and fully-supervised deep learning (DL) algorithms for breast mass classification and localization. The weakly-supervised DL algorithm does not require image annotation of region of interest (ROI) of the lesion, whereas the fully-supervised DL algorithm requires tumor segmentation (manual or automated) and cropping for ROI before being put in the classifiers. For the weakly-supervised DL algorithm, a class activation map (CAM) is generated to visualize the region detected by this algorithm using a global average pooling layer (GAP) that is added to the final convolutional layer.