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Pattern-Aware Diffusion Synthesis of fMRI/dMRI with Tissue and Microstructural Refinement

arXiv 2511.04963 ↗First posted 7 Nov 2025cs.CV cs.AIcited by 0

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Abstract (arXiv)

Magnetic resonance imaging (MRI), especially functional MRI (fMRI) and diffusion MRI (dMRI), is essential for studying neurodegenerative diseases. However, missing modalities pose a major barrier to their clinical use. Although GAN- and diffusion model-based approaches have shown some promise in modality completion, they remain limited in fMRI-dMRI synthesis due to (1) significant BOLD vs. diffusion-weighted signal differences between fMRI and dMRI in time/gradient axis, and (2) inadequate integration of disease-related neuroanatomical patterns during generation. To address these challenges, we propose PDS, introducing two key innovations: (1) a pattern-aware dual-modal 3D diffusion framework for cross-modality learning, and (2) a tissue refinement network integrated with a efficient microstructure refinement to maintain structural fidelity and fine details. Evaluated on OASIS-3, ADNI, and in-house datasets, our method achieves state-of-the-art results, with PSNR/SSIM scores of 29.83 dB/90.84% for fMRI synthesis (+1.54 dB/+4.12% over baselines) and 30.00 dB/77.55% for dMRI synthesis (+1.02 dB/+2.2%). In clinical validation, the synthesized data show strong diagnostic performance, achieving 67.92%/66.02%/64.15% accuracy (NC vs. MCI vs. AD) in hybrid real-synthetic experiments. Code is available in hrefhttps://github.com/SXR3015/PDSPDS GitHub Repository

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References · 15

  1. 2017Attention Is All You Needcited by 60,361
  2. 2022Generative Adversarial Networkscited by 5,627
  3. 2022Diffusion Models: A Comprehensive Survey of Methods and Applicationscited by 1,114
  4. 2022Diffusion Models in Vision: A Surveycited by 1,015
  5. 2018Self-Attention Generative Adversarial Networkscited by 809
  6. 2022Unsupervised Medical Image Translation with Adversarial Diffusion Modelscited by 192
  7. 2023DiffiT: Diffusion Vision Transformers for Image Generationcited by 106
  8. 2023Conditional Diffusion Models for Semantic 3D Brain MRI Synthesiscited by 86
  9. 2023CoLa-Diff: Conditional Latent Diffusion Model for Multi-Modal MRI Synthesiscited by 65
  10. 2024WDM: 3D Wavelet Diffusion Models for High-Resolution Medical Image Synthesiscited by 56
  11. 2023Make-A-Volume: Leveraging Latent Diffusion Models for Cross-Modality 3D Brain MRI Synthesiscited by 43
  12. 2023DiffusionGAN3D: Boosting Text-guided 3D Generation and Domain Adaptation by Combining 3D GANs and Diffusion Priorscited by 19
3 more
  1. 2021Q-space Conditioned Translation Networks for Directional Synthesis of Diffusion Weighted Images from Multi-modal Structural MRIcited by 11
  2. 2022Synthetic Low-Field MRI Super-Resolution Via Nested U-Net Architecturecited by 3
  3. 2023PET Synthesis via Self-supervised Adaptive Residual Estimation Generative Adversarial Networkcited by 2

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  1. 2026Multiscale Structure-Guided Latent Diffusion for Multimodal MRI Translation
  2. 2024When Diffusion MRI Meets Diffusion Model: A Novel Deep Generative Model for Diffusion MRI Generation
  3. 2024Physics-Informed Latent Diffusion for Multimodal Brain MRI Synthesis
  4. 20253D Anatomical Structure-guided Deep Learning for Accurate Diffusion Microstructure Imaging
  5. 2024Cross-conditioned Diffusion Model for Medical Image to Image Translation
  6. 2024Phy-Diff: Physics-guided Hourglass Diffusion Model for Diffusion MRI Synthesis
  7. 2025Diffusion-Based Synthesis of 3D T1w MPRAGE Images from Multi-Echo GRE with Multi-Parametric MRI Integration
  8. 2025Diffusion Models for Computational Neuroimaging: A Survey