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Found 2 papers, 1 papers with code
Latent Signal Models: Learning Compact Representations of Signal Evolution for Improved Time-Resolved, Multi-contrast MRI
Purpose: Training auto-encoders on simulated signal evolution and inserting the decoder into the forward model improves reconstructions through more compact, Bloch-equation-based representations of signal in comparison to linear subspaces.
Autofocusing+: Noise-Resilient Motion Correction in Magnetic Resonance Imaging
Image corruption by motion artifacts is an ingrained problem in Magnetic Resonance Imaging (MRI).
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