Generative models such as generative adversarial networks and autoencoders have gained
a great deal of attention in the medical field due to their excellent data generation capability …

Deep generative modeling has emerged as a powerful tool for synthesizing realistic medical
images, driving advances in medical image analysis, disease diagnosis, and treatment …

Medical imaging systems are often evaluated and optimized via objective, or task-specific,
measures of image quality (IQ) that quantify the performance of an observer on a specific …

Synthesis of images has recently seen many works that produce high-quality real world
images. In the domain of medical imaging the application of deep generative models …

Modern generative models, such as generative adversarial networks (GANs), hold
tremendous promise for several applications in medical imaging that include unconditional …