Fig. 1

The overview of Mask-Adaptive Normalization based Generative Adversarial Networks (MAN-GAN) with Cycle-Consistency Loss for CT translation. (a) The forward and backward cycle-consistency loss are utilized to reduce the space of possible mapping functions. (b) The forward generation includes a MaskNet to synthesize subtraction-image-like mask, a generator to fuse mask with non-contrast CT image and a discriminator to distinguish the real from fake MPECT image.