Bayesian image quality transfer with CNNs: Exploring uncertainty in dMRI super-resolution
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 trans- formation problems, such as super-resolution (SR) and image synthesis. However, the highly ill-posed...
| Main Authors: | , , , , , , |
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| Format: | Conference item |
| Published: |
Springer
2017
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