Progressively-Growing AmbientGANs For Learning Stochastic Object Models From Imaging Measurements

The objective optimization of medical imaging systems requires full characterization of all sources of randomness in the measured data, which includes the variability within the ensemble of objects to-be-imaged. This can be accomplished by establishing a stochastic object model (SOM) that describes the variability in the class of objects to-be-imaged... (read more)

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