An Unsupervised Deep Learning Framework for Retrospective Gating of Catheter-Based Cardiac Imaging

Figure 5

Training UFL module using a twin subnetwork composed of two UFL modules with shared weights. Two correlated images, x_i,1 and x_i,2, are generated from the ith sample x_i in the training set using a random data augmenter. They are inputted into the twin UFL subnetwork to extract their feature vectors v_i,1 and v_i,2.