15 citations · 27 across the 11 of their papers we have counts for
3 papers · 1 filter
A Method for Evaluating Deep Generative Models of Images via Assessing the Reproduction of High-order Spatial Context
Rucha Deshpande, Mark A. Anastasio, Frank J. Brooks
Deep generative models (DGMs) have the potential to revolutionize diagnostic imaging. Generative adversarial networks (GANs) are one kind of DGM which are widely employed. The over…
Learning stochastic object models from medical imaging measurements by use of advanced ambient generative adversarial networks
Weimin Zhou, Sayantan Bhadra, Frank J. Brooks +2
Purpose: To objectively assess new medical imaging technologies via computer-simulations, it is important to account for the variability in the ensemble of objects to be imaged. Th…
Advancing the AmbientGAN for learning stochastic object models
Weimin Zhou, Sayantan Bhadra, Frank J. Brooks +3
Medical imaging systems are commonly assessed and optimized by use of objective-measures of image quality (IQ) that quantify the performance of an observer at specific tasks. Varia…