Replacing the generic Stable Diffusion VAE with domain-specific MedVAE pretrained on 1.6M medical images improves diffusion-based SR PSNR by 2.91-3.29 dB on knee/brain MRI and chest X-ray, with gains in fine details and VAE quality predicting SR performance (R²=0.67).
Unsupervised medical image translation with adversarial diffusion models
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FGSB is a two-stage neural Schrödinger bridge that generates missing MRI modalities from limited paired data and preserves lesions via expert priors.
End-to-end pipeline uses ResViT-2.5D to synthesize post-resection MRI from ioUS then anchors deformable registration, yielding 5.86 mm TRE on 14 ReMIND subjects while producing an integrated whole-brain volume reflecting intraoperative state.
Lightweight U-Net outperforms DDPM on T2w-to-MRI-SFF translation (r=0.975 vs 0.962, MAE=0.014 vs 0.019) with 208x faster inference on 230k paired images from NAKO.
citing papers explorer
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Fully Guided Neural Schr\"odinger bridge for Brain MR image synthesis
FGSB is a two-stage neural Schrödinger bridge that generates missing MRI modalities from limited paired data and preserves lesions via expert priors.
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What neurosurgeons need to see: synthetic intra-operative MRI from ultrasound for brain-shift compensation in brain tumour surgery
End-to-end pipeline uses ResViT-2.5D to synthesize post-resection MRI from ioUS then anchors deformable registration, yielding 5.86 mm TRE on 14 ReMIND subjects while producing an integrated whole-brain volume reflecting intraoperative state.
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Do We Really Need Diffusion? A Fast U-Net for Paired Medical Image Translation
Lightweight U-Net outperforms DDPM on T2w-to-MRI-SFF translation (r=0.975 vs 0.962, MAE=0.014 vs 0.019) with 208x faster inference on 230k paired images from NAKO.