MR-DiffuSR applies cross-modality structural swin-attention from HR T1w images to guide 3D latent diffusion super-resolution of FLAIR, with mixed-scale training and DINOv3 loss, yielding PSNR 32.46 dB and robust downstream WMH segmentation on ADNI-4.
arXiv preprint arXiv:2509.00549 (2025)
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ReMAP-PET learns metabolic semantics in PET encoders by supervising MedicalNet with SUVR profiles, yielding 0.070 MAE, 77.8% Recall@1, and language-aligned embeddings on 1015 samples.
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Cross-Modality Structural Guidance in 3D Latent Diffusion for Robust FLAIR Super-Resolution
MR-DiffuSR applies cross-modality structural swin-attention from HR T1w images to guide 3D latent diffusion super-resolution of FLAIR, with mixed-scale training and DINOv3 loss, yielding PSNR 32.46 dB and robust downstream WMH segmentation on ADNI-4.
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ReMAP-PET: Beyond Visual Understanding -- Learning Region-Guided Metabolic Alignment Semantics from Brain PET
ReMAP-PET learns metabolic semantics in PET encoders by supervising MedicalNet with SUVR profiles, yielding 0.070 MAE, 77.8% Recall@1, and language-aligned embeddings on 1015 samples.