Figure 2.

The architecture of the deep learning system. (a) A U-net style deep learning system architecture with a contracting pathway and an expanding pathway. The contracting pathway is visualised with red arrows, each marking a convolution block with a stride of two. The expanding pathway is visualised with green arrows, each marking a transpose convolution block with a stride of two. The pathways are connected with feature concatenation marked using arrows with the letter C. The number of feature maps is shown on each block and all the convolutions except the last one have a kernel size of 3 × 3 × 3. The last convolution has one feature, a kernel size of 1 × 1 × 1, no layer normalisation, and uses the sigmoid nonlinearity. (b) Each block includes two convolutions with a stride of one, batch normalisation (BN), and ReLU non-linearities with elementwise summation marked using arrows with a plus sign.