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38 w - Translate

https://www.selleckchem.com/pr....oducts/gkt137831.htm
PURPOSE To develop a deep learning-based Bayesian estimation for MRI reconstruction. METHODS We modeled the MRI reconstruction problem with Bayes's theorem, following the recently proposed PixelCNN++ method. The image reconstruction from incomplete k-space measurement was obtained by maximizing the posterior possibility. A generative network was utilized as the image prior, which was computationally tractable, and the k-space data fidelity was enforced by using an equality constraint. The stochastic backpropagation was utilized to cal

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