IB-cGAN is designed to address two main challenges in deep-learning-based synthesis: (a) training with a roughly aligned dataset suffering from noisy correspondences; (b) making synthesized images have real clinical meanings that faithfully reflects MV-DRs rather than nonaligned KV-DRRs. Accordingly...