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The Rajaraman network for bone suppression used in this study. Every 2D convolutional layer (“Conv2d”) uses a filter size (f) of 3×3, a stride (s) of 1 and a padding (p) of 1. Arrows denote skip connections. Elementwise addition is used to combine tensors both in ResBlocks and in the larger network. In the ResBlock scaling layer, the input tensor is elementwise multiplied by 0.1. The final layer uses a sigmoid activation function to generate the bone-suppressed output image.
