PnP-CoSMo is a modular plug-and-play iterative reconstruction technique that disentangles content and style in multi-contrast MR images to guide reconstruction from reference scans without k-space training data.
author Weiger, M
4 Pith papers cite this work. Polarity classification is still indexing.
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PICO estimates image-domain noise covariance in linear and nonlinear MRI reconstructions up to 7x faster than PMR by using complex random-phase probes.
A plug-and-play bilateral breast gradient insert prototype achieves 2.8 mT/m/A efficiency and local strengths up to 1850 mT/m, allowing b=10000 s/mm² diffusion MRI at TE=78 ms versus 161 ms with scanner gradients.
A public GPU workflow for non-Fourier SENSE MRI reconstruction with sensitivity and off-resonance mapping enables fast, accurate imaging from challenging spiral trajectories.
citing papers explorer
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A Plug-and-Play Method for Guided Multi-contrast MRI Reconstruction based on Content/Style Modeling
PnP-CoSMo is a modular plug-and-play iterative reconstruction technique that disentangles content and style in multi-contrast MR images to guide reconstruction from reference scans without k-space training data.
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Fast Voxelwise SNR Estimation for Iterative MRI Reconstructions
PICO estimates image-domain noise covariance in linear and nonlinear MRI reconstructions up to 7x faster than PMR by using complex random-phase probes.
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Bilateral breast gradient insert prototype for strong diffusion encoding at 3T
A plug-and-play bilateral breast gradient insert prototype achieves 2.8 mT/m/A efficiency and local strengths up to 1850 mT/m, allowing b=10000 s/mm² diffusion MRI at TE=78 ms versus 161 ms with scanner gradients.
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A GPU-enhanced workflow for non-Fourier SENSE reconstruction
A public GPU workflow for non-Fourier SENSE MRI reconstruction with sensitivity and off-resonance mapping enables fast, accurate imaging from challenging spiral trajectories.