mlsanityData to 14 Oct 2026

A 3D Conditional Diffusion Model for Image Quality Transfer -- An Application to Low-Field MRI

arXiv 2311.06631 ↗First posted 11 Nov 2023eess.IV cs.CV cs.LGcited by 13

On the map: Diffusion models → Medical imaging and segmentation

Abstract (arXiv)

Low-field (LF) MRI scanners (<1T) are still prevalent in settings with limited resources or unreliable power supply. However, they often yield images with lower spatial resolution and contrast than high-field (HF) scanners. This quality disparity can result in inaccurate clinician interpretations. Image Quality Transfer (IQT) has been developed to enhance the quality of images by learning a mapping function between low and high-quality images. Existing IQT models often fail to restore high-frequency features, leading to blurry output. In this paper, we propose a 3D conditional diffusion model to improve 3D volumetric data, specifically LF MR images. Additionally, we incorporate a cross-batch mechanism into the self-attention and padding of our network, ensuring broader contextual awareness even under small 3D patches. Experiments on the publicly available Human Connectome Project (HCP) dataset for IQT and brain parcellation demonstrate that our model outperforms existing methods both quantitatively and qualitatively. The code is publicly available at urlhttps://github.com/edshkim98/DiffusionIQT.

Key facts. Cited by 13 papers in the map (data through 14 Oct 2026). Placed in Medical imaging and segmentation, one of 14 directions in Diffusion models. Builds on 19 of its 28 references that are in the map. First posted on arXiv 11 Nov 2023.

Builds on

19 of 28 references.

Closest ancestors · 2

Same direction, newest first

  1. 2022Solving 3D Inverse Problems using Pre-trained 2D Diffusion Models19 Nov
  2. 2022MedSegDiff: Medical Image Segmentation with Diffusion Probabilistic Model1 Nov

Other references · 17

  1. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
  2. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  3. 2020Denoising Diffusion Implicit Modelscited by 9,781
  4. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,255
  5. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,355
  6. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,761
  7. 2016Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Networkcited by 1,908
  8. 2018ESRGAN: Enhanced Super-Resolution Generative Adversarial Networkscited by 1,254
  9. 2016Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Networkcited by 1,204
  10. 2021Variational Diffusion Modelscited by 1,153
  11. 2021SRDiff: Single Image Super-Resolution with Diffusion Probabilistic Modelscited by 415
  12. 2018Efficient Attention: Attention with Linear Complexitiescited by 368
5 more
  1. 2019FastSurfer -- A fast and accurate deep learning based neuroimaging pipelinecited by 112
  2. 2018Tiling and Stitching Segmentation Output for Remote Sensing: Basic Challenges and Recommendationscited by 24
  3. 2023Low-field magnetic resonance image enhancement via stochastic image quality transfercited by 19
  4. 2021SOUP-GAN: Super-Resolution MRI Using Generative Adversarial Networkscited by 18
  5. 2019Multi-Stage Prediction Networks for Data Harmonizationcited by 7

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 2; 2025: 6; 2026: 5.

13 papers.

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  1. 2024Tackling Structural Hallucination in Image Translation with Local Diffusioncited by 21
  2. 2025Tackling Hallucination from Conditional Models for Medical Image Reconstruction with DynamicDPScited by 11
  3. 2024Alternative Learning Paradigms for Image Quality Transfercited by 4
  4. 2025Low-Field Magnetic Resonance Image Quality Enhancement using a Conditional Flow Matching Modelcited by 3
  5. 2025MRIQT: Physics-Aware Diffusion Model for Image Quality Transfer in Neonatal Ultra-Low-Field MRIcited by 2
  6. 2026Direct low-field MRI super-resolution using undersampled k-spacecited by 2
  7. 2025HalluGen: Synthesizing Realistic and Controllable Hallucinations for Evaluating Image Restorationcited by 1
  8. 2025MInDI-3D: Iterative Deep Learning in 3D for Sparse-view Cone Beam Computed Tomographycited by 0
  9. 2025HULFSynth : An INR based Super-Resolution and Ultra Low-Field MRI Synthesis via Contrast factor estimationcited by 0
  10. 2026MPFlow: Multi-modal Posterior-Guided Flow Matching for Zero-Shot MRI Reconstructioncited by 0
  11. 2026Low-Field Magnetic Resonance Image Quality Enhancement using Undersampled k-Space and Out-of-Distribution Generalisationcited by 0
  12. 2026Low-Field Magnetic Resonance Image Enhancement using Undersampled k-Spacecited by 0
1 more
  1. 2026Subject-Specific Low-Field MRI Synthesis via a Neural Operatorcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Conditional Denoising Diffusion Model-Based Robust MR Image Reconstruction from Highly Undersampled Data
  2. 2026Zero-shot Low-Field MRI Enhancement via Diffusion-Based Adaptive Contrast Transport
  3. 2026Uncertainty-Aware 3D Residual Wavelet Diffusion for Ultra Low-Field MRI Super-Resolution
  4. 2024Unpaired Volumetric Harmonization of Brain MRI with Conditional Latent Diffusion
  5. 2024cWDM: Conditional Wavelet Diffusion Models for Cross-Modality 3D Medical Image Synthesis
  6. 2024Non-Reference Quality Assessment for Medical Imaging: Application to Synthetic Brain MRIs
  7. 2025MDPG: Multi-domain Diffusion Prior Guidance for MRI Reconstruction
  8. 2024Denoising Diffusion Probabilistic Models for Magnetic Resonance Fingerprinting