ADDGAN learns clean image distributions from noisy CT and DBT measurements by feeding generated objects through the known imaging operator, and it beats AmbientGAN baselines on FID and observer-task metrics.
Effect of random background inhomogeneity on observer detection performance,
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Ambient Denoising Diffusion Generative Adversarial Networks for Establishing Stochastic Object Models from Noisy Image Data
ADDGAN learns clean image distributions from noisy CT and DBT measurements by feeding generated objects through the known imaging operator, and it beats AmbientGAN baselines on FID and observer-task metrics.