Abstract: Multi-Scale GANs for Memory-Effcient Generation of High Resolution Medical Images

Hristina Uzunova, Jan Ehrhardt, Fabian Jacob, Alex Frydrychowicz, Heinz Handels

Abstract: Generative adversarial networks (GANs) have shown impressive results for photo-realistic image synthesis in the last couple of years. They also offer numerous applications in medical image analysis, such as generating images for data augmentation, image reconstruction and image synthesis for domain adaptation. Despite the undeniable success and the large variety of applications, GANs still struggle to generate images of high resolution.