SAMRI fine-tunes only the mask decoder of SAM on 1.1 million MRI slices from 30 datasets to reach mean DSC 0.87 on 47 targets and strong zero-shot performance.
Medical Image Segmentation Review: The Success of U -Net,
3 Pith papers cite this work. Polarity classification is still indexing.
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Physics-guided U-Net removes non-stationary artifacts from X-ray images, raising mean SSIM from 0.345 to 0.906 and 0.0679 to 0.945 in synthetic tests while preserving filament profiles better than Fourier filtering or DFFN.
An adapted U-Net model trained on mean-field phase diagrams accurately predicts Hamiltonian parameters for a cuprate superconductor when validated on Monte Carlo simulation data.
citing papers explorer
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SAMRI: Segment Any MRI
SAMRI fine-tunes only the mask decoder of SAM on 1.1 million MRI slices from 30 datasets to reach mean DSC 0.87 on 47 targets and strong zero-shot performance.
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Physics-Guided Deep Learning For High Resolution X-ray Imaging
Physics-guided U-Net removes non-stationary artifacts from X-ray images, raising mean SSIM from 0.345 to 0.906 and 0.0679 to 0.945 in synthetic tests while preserving filament profiles better than Fourier filtering or DFFN.
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Predicting parameters of a model cuprate superconductor using machine learning
An adapted U-Net model trained on mean-field phase diagrams accurately predicts Hamiltonian parameters for a cuprate superconductor when validated on Monte Carlo simulation data.