mlsanityData to 7 Oct 2026

Conversion Between CT and MRI Images Using Diffusion and Score-Matching Models

arXiv 2209.12104 ↗First posted 24 Sep 2022eess.IV cs.CV physics.med-phcited by 69

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Cited by 46 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

MRI and CT are most widely used medical imaging modalities. It is often necessary to acquire multi-modality images for diagnosis and treatment such as radiotherapy planning. However, multi-modality imaging is not only costly but also introduces misalignment between MRI and CT images. To address this challenge, computational conversion is a viable approach between MRI and CT images, especially from MRI to CT images. In this paper, we propose to use an emerging deep learning framework called diffusion and score-matching models in this context. Specifically, we adapt denoising diffusion probabilistic and score-matching models, use four different sampling strategies, and compare their performance metrics with that using a convolutional neural network and a generative adversarial network model. Our results show that the diffusion and score-matching models generate better synthetic CT images than the CNN and GAN models. Furthermore, we investigate the uncertainties associated with the diffusion and score-matching networks using the Monte-Carlo method, and improve the results by averaging their Monte-Carlo outputs. Our study suggests that diffusion and score-matching models are powerful to generate high quality images conditioned on an image obtained using a complementary imaging modality, analytically rigorous with clear explainability, and highly competitive with CNNs and GANs for image synthesis.

Key facts. Cited by 69 papers in the map (data through 7 Oct 2026). Builds on 29 of its 51 references that are in the map. First posted on arXiv 24 Sep 2022.

Builds on

29 of 51 references.

References · 29

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  3. 2020Denoising Diffusion Implicit Modelscited by 9,655
  4. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  5. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  6. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
  7. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,067
  8. 2016Perceptual Losses for Real-Time Style Transfer and Super-Resolutioncited by 2,678
  9. 2017Improved Training of Wasserstein GANscited by 2,223
  10. 2022DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Stepscited by 1,961
  11. 2021Image Super-Resolution via Iterative Refinementcited by 1,506
  12. 2022Diffusion Models in Vision: A Surveycited by 1,008
17 more
  1. 2021Solving Inverse Problems in Medical Imaging with Score-Based Generative Modelscited by 514
  2. 2017Learning a Variational Network for Reconstruction of Accelerated MRI Datacited by 340
  3. 2021Come-Closer-Diffuse-Faster: Accelerating Conditional Diffusion Models for Inverse Problems through Stochastic Contractioncited by 306
  4. 2017Low-Dose CT with a Residual Encoder-Decoder Convolutional Neural Network (RED-CNN)cited by 224
  5. 2021More Control for Free! Image Synthesis with Semantic Diffusion Guidancecited by 211
  6. 2017Low Dose CT Image Denoising Using a Generative Adversarial Network with Wasserstein Distance and Perceptual Losscited by 161
  7. 2018MedGAN: Medical Image Translation using GANscited by 152
  8. 2022Accelerating Diffusion Models via Early Stop of the Diffusion Processcited by 100
  9. 2018Translating and Segmenting Multimodal Medical Volumes with Cycle- and Shape-Consistency Generative Adversarial Networkcited by 97
  10. 2018Cross-modality image synthesis from unpaired data using CycleGAN: Effects of gradient consistency loss and training data sizecited by 42
  11. 2020Bidirectional Mapping Generative Adversarial Networks for Brain MR to PET Synthesiscited by 38
  12. 2018Cross-Modality Synthesis from CT to PET using FCN and GAN Networks for Improved Automated Lesion Detectioncited by 29
  13. 2019MRI Super-Resolution with Ensemble Learning and Complementary Priorscited by 27
  14. 2022Accelerating Score-based Generative Models with Preconditioned Diffusion Samplingcited by 19
  15. 2017Synthesis of Positron Emission Tomography (PET) Images via Multi-channel Generative Adversarial Networks (GANs)cited by 18
  16. 2017Virtual PET Images from CT Data Using Deep Convolutional Networks: Initial Resultscited by 9
  17. 2018Learning Myelin Content in Multiple Sclerosis from Multimodal MRI through Adversarial Trainingcited by 7

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 17; 2024: 24; 2025: 15; 2026: 11.

69 papers.

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  1. 2022Diffusion Models for Medical Image Analysis: A Comprehensive Surveycited by 269
  2. 2024Anatomically-Controllable Medical Image Generation with Segmentation-Guided Diffusion Modelscited by 69
  3. 2024Towards Generalizable Tumor Synthesiscited by 65
  4. 2023CoLa-Diff: Conditional Latent Diffusion Model for Multi-Modal MRI Synthesiscited by 64
  5. 2023Deep Learning Approaches for Data Augmentation in Medical Imaging: A Reviewcited by 48
  6. 2023Zero-shot Medical Image Translation via Frequency-Guided Diffusion Modelscited by 39
  7. 2024Efficient Diffusion Models: A Comprehensive Survey from Principles to Practicescited by 39
  8. 2023Echo from noise: synthetic ultrasound image generation using diffusion models for real image segmentationcited by 33
  9. 2024Fast-DDPM: Fast Denoising Diffusion Probabilistic Models for Medical Image-to-Image Generationcited by 33
  10. 2023Synthetic CT Generation from MRI using 3D Transformer-based Denoising Diffusion Modelcited by 29
  11. 2024Self-Consistent Recursive Diffusion Bridge for Medical Image Translationcited by 26
  12. 2023DiffBoost: Enhancing Medical Image Segmentation via Text-Guided Diffusion Modelcited by 23
38 more
  1. 2024MedM2G: Unifying Medical Multi-Modal Generation via Cross-Guided Diffusion with Visual Invariantcited by 21
  2. 2024Has Multimodal Learning Delivered Universal Intelligence in Healthcare? A Comprehensive Surveycited by 20
  3. 2023Diffusion Models for Contrast Harmonization of Magnetic Resonance Imagescited by 19
  4. 2023Cycle-guided Denoising Diffusion Probability Model for 3D Cross-modality MRI Synthesiscited by 18
  5. 2024MiM: Mask in Mask Self-Supervised Pre-Training for 3D Medical Image Analysiscited by 17
  6. 2023Denoising diffusion-based MRI to CT image translation enables automated spinal segmentationcited by 15
  7. 2023Full-dose Whole-body PET Synthesis from Low-dose PET Using High-efficiency Denoising Diffusion Probabilistic Model: PET Consistency Modelcited by 15
  8. 2025Scaling Tumor Segmentation: Best Lessons from Real and Synthetic Datacited by 13
  9. 2024Generative AI-Driven Human Digital Twin in IoT-Healthcare: A Comprehensive Surveycited by 11
  10. 2023DoseDiff: Distance-aware Diffusion Model for Dose Prediction in Radiotherapycited by 10
  11. 2024Cascaded Multi-path Shortcut Diffusion Model for Medical Image Translationcited by 9
  12. 2024Diff-Def: Diffusion-Generated Deformation Fields for Conditional Atlasescited by 8
  13. 2024A Survey on Responsible Generative AI: What to Generate and What Notcited by 8
  14. 2024Data Augmentation for Surgical Scene Segmentation with Anatomy-Aware Diffusion Modelscited by 8
  15. 2025Regression is all you need for medical image translationcited by 8
  16. 2025TRACE: Temporally Reliable Anatomically-Conditioned 3D CT Generation with Enhanced Efficiencycited by 8
  17. 2023Diffusion-based Radiotherapy Dose Prediction Guided by Inter-slice Aware Structure Encodingcited by 5
  18. 2024Functional Imaging Constrained Diffusion for Brain PET Synthesis from Structural MRIcited by 5
  19. 2023Energy-Guided Diffusion Model for CBCT-to-CT Synthesiscited by 4
  20. 2023Learning to Reconstruct Accelerated MRI Through K-space Cold Diffusion without Noisecited by 4
  21. 2024Cross-modality image synthesis from TOF-MRA to CTA using diffusion-based modelscited by 4
  22. 2024Leveraging Multimodal Diffusion Models to Accelerate Imaging with Side Informationcited by 3
  23. 2024Volumetric Conditioning Module to Control Pretrained Diffusion Models for 3D Medical Imagescited by 3
  24. 2025FgC2F-UDiff: Frequency-guided and Coarse-to-fine Unified Diffusion Model for Multi-modality Missing MRI Synthesiscited by 3
  25. 2022One Sample Diffusion Model in Projection Domain for Low-Dose CT Imagingcited by 2
  26. 2023SP-DiffDose: A Conditional Diffusion Model for Radiation Dose Prediction Based on Multi-Scale Fusion of Anatomical Structures, Guided by SwinTransformer and Projectorcited by 2
  27. 2024Diff-DTI: Fast Diffusion Tensor Imaging Using A Feature-Enhanced Joint Diffusion Modelcited by 2
  28. 2025seg2med: a bridge from artificial anatomy to multimodal medical imagescited by 2
  29. 2025Comparative Analysis of GAN and Diffusion for MRI-to-CT translationcited by 2
  30. 2026Cross-Modal Guidance for Fast Diffusion-Based Computed Tomographycited by 2
  31. 2026MRI-to-CT synthesis using drifting modelscited by 2
  32. 2024Synthetic Privileged Information Enhances Medical Image Representation Learningcited by 1
  33. 2024QID2: An Image-Conditioned Diffusion Model for Q-space Up-sampling of DWI Datacited by 1
  34. 2025Segmentation-Guided CT Synthesis with Pixel-Wise Conformal Uncertainty Boundscited by 1
  35. 2025Computationally Efficient Diffusion Models in Medical Imaging: A Comprehensive Reviewcited by 1
  36. 2025Discrete Diffusion Models with MLLMs for Unified Medical Multimodal Generationcited by 1
  37. 2026Unpaired Image-to-Image Translation via a Self-Supervised Semantic Bridgecited by 1
  38. 2026PPDM: Pixel Puzzling Diffusion Model for Speed and Memory Efficient Volumetric Medical Image Translationcited by 1

50 most cited of 69 All 69 (JSON)

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  1. 2025Pseudoinverse Diffusion Models for Generative CT Image Reconstruction from Low Dose Data
  2. 2024Cross-conditioned Diffusion Model for Medical Image to Image Translation
  3. 2024Integrating Deep Unfolding with Direct Diffusion Bridges for Computed Tomography Reconstruction
  4. 2025Deep generative priors for 3D brain analysis
  5. 2023CT Reconstruction using Diffusion Posterior Sampling conditioned on a Nonlinear Measurement Model
  6. 2025Lesion-Aware Post-Training of Latent Diffusion Models for Synthesizing Diffusion MRI from CT Perfusion
  7. 2023Brain tumor segmentation using synthetic MR images -- A comparison of GANs and diffusion models
  8. 2022Unsupervised Medical Image Translation with Adversarial Diffusion Models