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Found 2 papers, 1 papers with code
Progressive Subsampling for Oversampled Data -- Application to Quantitative MRI
We build upon a recent dual-network approach that won the MICCAI MUlti-DIffusion (MUDI) quantitative MRI measurement sampling-reconstruction challenge, but suffers from deep learning training instability, by subsampling with a hard decision boundary.
Uncertainty Quantification in Deep Learning for Safer Neuroimage Enhancement
Here we introduce methods to characterise different components of uncertainty in such problems and demonstrate the ideas using diffusion MRI super-resolution.
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