47 citations · 101 across the 20 of their papers we have counts for
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A Hybrid Approach for Approximating the Ideal Observer for Joint Signal Detection and Estimation Tasks by Use of Supervised Learning and Markov-Chain Monte Carlo Methods
Kaiyan Li, Weimin Zhou, Hua Li +1
The ideal observer (IO) sets an upper performance limit among all observers and has been advocated for assessing and optimizing imaging systems. For general joint detection and est…
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…
Assessing the Impact of Deep Neural Network-based Image Denoising on Binary Signal Detection Tasks
Kaiyan Li, Weimin Zhou, Hua Li +1
A variety of deep neural network (DNN)-based image denoising methods have been proposed for use with medical images. Traditional measures of image quality (IQ) have been employed t…
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…