Figure 2
From: Deep learning segmentation of fibrous cap in intravascular optical coherence tomography images
SegResNet Architecture for FC Segmentation. The preprocessed IVOCT image serves as the input, starting with an initial 3 × 3 convolution and dropout layers. Each green block represents a ResNet-like block with group normalization. The decoder outputs a predicted label, followed by a sigmoid activation function to generate a pixel-wise classification map. Both the input and output images have the same size (200 × 448 pixels in (r,θ)). In the input image, the black strip indicates the removed guidewire shadow.
