Bayesian Image Quality Transfer with CNNs: Exploring Uncertainty in dMRI Super-Resolution

1 May 2017Ryutaro TannoDaniel E. WorrallAurobrata GhoshEnrico KadenStamatios N. SotiropoulosAntonio CriminisiDaniel C. Alexander

In this work, we investigate the value of uncertainty modeling in 3D super-resolution with convolutional neural networks (CNNs). Deep learning has shown success in a plethora of medical image transformation problems, such as super-resolution (SR) and image synthesis... (read more)

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