mlsanityData to 14 Oct 2026

Diffusion-Assisted Frequency Attention Model for Whole-body Low-field MRI Reconstruction

arXiv 2507.17764 ↗First posted 9 Jul 2025physics.med-ph cs.CVcited by 0

On the map: Diffusion models → Medical imaging and segmentation

Abstract (arXiv)

By integrating the generative strengths of diffusion models with the representation capabilities of frequency-domain attention, DFAM effectively enhances reconstruction performance under low-SNR condi-tions. Experimental results demonstrate that DFAM consistently outperforms both conventional reconstruction algorithms and recent learning-based approaches. These findings highlight the potential of DFAM as a promising solution to advance low-field MRI reconstruction, particularly in resource-constrained or underdeveloped clinical settings.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Medical imaging and segmentation, one of 14 directions in Diffusion models. Builds on 12 of its 28 references that are in the map. First posted on arXiv 9 Jul 2025.

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12 of 28 references.

Closest ancestors · 4

Same direction, newest first

  1. 2023Correlated and Multi-frequency Diffusion Modeling for Highly Under-sampled MRI Reconstruction2 Sep
  2. 2023Self-Supervised MRI Reconstruction with Unrolled Diffusion Models29 Jun
  3. 2022High-Frequency Space Diffusion Models for Accelerated MRI10 Aug
  4. 2021Score-based diffusion models for accelerated MRI8 Oct

Other references · 8

  1. 2021SwinIR: Image Restoration Using Swin Transformercited by 1,887
  2. 2021Restormer: Efficient Transformer for High-Resolution Image Restorationcited by 1,627
  3. 2017MoDL: Model Based Deep Learning Architecture for Inverse Problemscited by 387
  4. 2023DiffIR: Efficient Diffusion Model for Image Restorationcited by 255
  5. 2020Homotopic Gradients of Generative Density Priors for MR Image Reconstructioncited by 14
  6. 2021MRI Reconstruction Using Deep Energy-Based Modelcited by 8
  7. 2024WaveletFormerNet: A Transformer-based Wavelet Network for Real-world Non-homogeneous and Dense Fog Removalcited by 4
  8. 2023Partition-based K-space Synthesis for Multi-contrast Parallel Imagingcited by 1

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  1. 2025MDPG: Multi-domain Diffusion Prior Guidance for MRI Reconstruction
  2. 2025Dual-domain Multi-path Self-supervised Diffusion Model for Accelerated MRI Reconstruction
  3. 2024LDPM: Towards undersampled MRI reconstruction with MR-VAE and Latent Diffusion Prior
  4. 2024Generating Content for HDR Deghosting from Frequency View
  5. 2022Physics-informed Deep Diffusion MRI Reconstruction with Synthetic Data: Break Training Data Bottleneck in Artificial Intelligence
  6. 2024Rethinking Diffusion Model for Multi-Contrast MRI Super-Resolution
  7. 2024DP-MDM: Detail-Preserving MR Reconstruction via Multiple Diffusion Models
  8. 2023A Survey of Emerging Applications of Diffusion Probabilistic Models in MRI