Assessing the ability of generative adversarial networks to learn canonical medical image statistics

no code implementations • 26 Apr 2022 • Varun A. Kelkar, Dimitrios S. Gotsis, Frank J. Brooks, Prabhat KC, Kyle J. Myers, Rongping Zeng, Mark A. Anastasio

In recent years, generative adversarial networks (GANs) have gained tremendous popularity for potential applications in medical imaging, such as medical image synthesis, restoration, reconstruction, translation, as well as objective image quality assessment.

Image Generation Image Quality Assessment +1

Evaluating Procedures for Establishing Generative Adversarial Network-based Stochastic Image Models in Medical Imaging

no code implementations • 7 Apr 2022 • Varun A. Kelkar, Dimitrios S. Gotsis, Frank J. Brooks, Kyle J. Myers, Prabhat KC, Rongping Zeng, Mark A. Anastasio

However, procedures for establishing stochastic image models (SIMs) using GANs remain generic and do not address specific issues relevant to medical imaging.

Generative Adversarial Network Image Generation +2