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Found 4 papers, 1 papers with code
A Flow-based Truncated Denoising Diffusion Model for Super-resolution Magnetic Resonance Spectroscopic Imaging
Recently, diffusion models have demonstrated superior learning capability than other generative models in various tasks, but sampling from diffusion models requires iterating through a large number of diffusion steps, which is time-consuming.
Predicting dynamic, motion-related changes in B0 field in the brain at a 7 T MRI using a subject-specific fine-tuned U-net
We further fine-tuned the network weights to each subject by measuring a limited number of head positions of the given subject, and trained the U-net with these data.
Flow-based Visual Quality Enhancer for Super-resolution Magnetic Resonance Spectroscopic Imaging
Specifically, we propose a flow-based enhancer network to improve the visual quality of super-resolution MRSI.
Multi-scale Super-resolution Magnetic Resonance Spectroscopic Imaging with Adjustable Sharpness
Magnetic Resonance Spectroscopic Imaging (MRSI) is a valuable tool for studying metabolic activities in the human body, but the current applications are limited to low spatial resolutions.
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