Fig. 4.
Mask R-CNN (Backbone+FPN, RPN, RoI) and COVID-CT-Mask-Net architectures. The architecture of Mask R-CNN at training and test time is the same, except that at training time LSEG is computed for RPN and RoI. At test time, RPN and RoI do not compute any losses. See Section 3.1 for a detailed discussion of its functionality. The new classification module S (Fig. 5) takes the batch size N of the ranked encoded boxes with their confidence scores as an input and predicts the class of the input image. Normal arrows: tensors or data, broken arrows: boxes, dotted arrow: image class label. Best viewed in color