Report on the AAPM Grand Challenge on deep generative modeling for learning medical image statistics

no code implementations • 3 May 2024 • Rucha Deshpande, Varun A. Kelkar, Dimitrios Gotsis, Prabhat KC, Rongping Zeng, Kyle J. Myers, Frank J. Brooks, Mark A. Anastasio

The goal of this challenge was to promote the development of deep generative models (DGMs) for medical imaging and to emphasize the need for their domain-relevant assessment via the analysis of relevant image statistics.

Generative Adversarial Network Memorization