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09/19/2023
Assessing the capacity of a denoising diffusion probabilistic model to reproduce spatial context
Diffusion models have emerged as a popular family of deep generative mod...
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11/02/2022
Investigating the robustness of a learning-based method for quantitative phase retrieval from propagation-based x-ray phase contrast measurements under laboratory conditions
Quantitative phase retrieval (QPR) in propagation-based x-ray phase cont...
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04/26/2022
Assessing the ability of generative adversarial networks to learn canonical medical image statistics
In recent years, generative adversarial networks (GANs) have gained trem...
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04/07/2022
Evaluating Procedures for Establishing Generative Adversarial Network-based Stochastic Image Models in Medical Imaging
Modern generative models, such as generative adversarial networks (GANs)...
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11/24/2021
A Method for Evaluating the Capacity of Generative Adversarial Networks to Reproduce High-order Spatial Context
Generative adversarial networks are a kind of deep generative model with...
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06/27/2021
Learning stochastic object models from medical imaging measurements by use of advanced AmbientGANs
In order to objectively assess new medical imaging technologies via comp...
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01/30/2021
Advancing the AmbientGAN for learning stochastic object models
Medical imaging systems are commonly assessed and optimized by use of ob...
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12/01/2020
On hallucinations in tomographic image reconstruction
Tomographic image reconstruction is generally an ill-posed linear invers...
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05/29/2020
Learning stochastic object models from medical imaging measurements using Progressively-Growing AmbientGANs
It has been advocated that medical imaging systems and reconstruction al...
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01/26/2020
