Evaluating procedures for establishing generative adversarial network-based stochastic image models in medical imaging. - Varun A. Kelkar; Dimitrios S. Gotsis; Frank J. Brooks; Kyle J. Myers; Prabhat K. C.; Rongping Zeng; Mark A. Anastasio (Image Perception, Observer Performance, and Technology Assessment, 2022)

Evaluating generative stochastic image models using task-based image quality measures. - Varun A. Kelkar; Dimitrios S. Gotsis; Rucha Deshpande; Frank J. Brooks; Prabhat K. C.; Kyle J. Myers; Rongping Zeng; Mark A. Anastasio (Image Perception, Observer Performance, and Technology Assessment, 2023)

Assessing the Ability of Generative Adversarial Networks to Learn Canonical Medical Image Statistics. - Varun A. Kelkar; Dimitrios S. Gotsis; Frank J. Brooks; Prabhat K. C.; Kyle J. Myers; Rongping Zeng; Mark A. Anastasio (IEEE Trans. Medical Imaging, 2023)

Report on the AAPM Grand Challenge on deep generative modeling for learning medical image statistics. - Rucha Deshpande; Varun A. Kelkar; Dimitrios S. Gotsis; Prabhat K. C.; Rongping Zeng; Kyle J. Myers; Frank J. Brooks; Mark A. Anastasio (CoRR, 2024)