mlsanityData to 7 Oct 2026

Generating Realistic Brain MRIs via a Conditional Diffusion Probabilistic Model

arXiv 2212.08034 ↗First posted 15 Dec 2022eess.IVcited by 28

On the map: Diffusion models → Medical imaging and segmentation

Abstract (arXiv)

As acquiring MRIs is expensive, neuroscience studies struggle to attain a sufficient number of them for properly training deep learning models. This challenge could be reduced by MRI synthesis, for which Generative Adversarial Networks (GANs) are popular. GANs, however, are commonly unstable and struggle with creating diverse and high-quality data. A more stable alternative is Diffusion Probabilistic Models (DPMs) with a fine-grained training strategy. To overcome their need for extensive computational resources, we propose a conditional DPM (cDPM) with a memory-efficient process that generates realistic-looking brain MRIs. To this end, we train a 2D cDPM to generate an MRI subvolume conditioned on another subset of slices from the same MRI. By generating slices using arbitrary combinations between condition and target slices, the model only requires limited computational resources to learn interdependencies between slices even if they are spatially far apart. After having learned these dependencies via an attention network, a new anatomy-consistent 3D brain MRI is generated by repeatedly applying the cDPM. Our experiments demonstrate that our method can generate high-quality 3D MRIs that share a similar distribution to real MRIs while still diversifying the training set. The code is available at https://github.com/xiaoiker/mask3DMRI_diffusion and also will be released as part of MONAI, at https://github.com/Project-MONAI/GenerativeModels.

Key facts. Cited by 28 papers in the map (data through 7 Oct 2026). Placed in Medical imaging and segmentation, one of 14 directions in Diffusion models. Builds on 21 of its 31 references that are in the map. First posted on arXiv 15 Dec 2022.

Builds on

21 of 31 references.

Closest ancestors · 2

Same direction, newest first

  1. 2022Brain Imaging Generation with Latent Diffusion Models15 Sep
  2. 2022Diffusion Models for Medical Anomaly Detection8 Mar

Other references · 19

  1. 2017Attention Is All You Needcited by 59,932
  2. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  3. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  4. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
  5. 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 5,986
  6. 2022Generative Adversarial Networkscited by 5,603
  7. 2017Improved Training of Wasserstein GANscited by 2,223
  8. 2018Self-Attention with Relative Position Representationscited by 1,112
  9. 2015Autoencoding beyond pixels using a learned similarity metriccited by 407
  10. 2020Deep Structural Causal Models for Tractable Counterfactual Inferencecited by 210
  11. 2018Medical Image Synthesis for Data Augmentation and Anonymization using Generative Adversarial Networkscited by 146
  12. 2018Image Synthesis in Multi-Contrast MRI with Conditional Generative Adversarial Networkscited by 131
7 more
  1. 2022Diffusion models for missing value imputation in tabular datacited by 77
  2. 2019Generation of 3D Brain MRI Using Auto-Encoding Generative Adversarial Networkscited by 65
  3. 2020Hierarchical Amortized Training for Memory-efficient High Resolution 3D GANcited by 60
  4. 2020Longitudinal Self-Supervised Learningcited by 30
  5. 2021Representation Disentanglement for Multi-modal brain MR Analysiscited by 22
  6. 2018Learning Implicit Brain MRI Manifolds with Deep Learningcited by 20
  7. 2022Anatomically constrained CT image translation for heterogeneous blood vessel segmentationcited by 6

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 4; 2024: 12; 2025: 6; 2026: 6.

28 papers.

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  1. 2023Large language models in healthcare and medical domain: A reviewcited by 126
  2. 2024WDM: 3D Wavelet Diffusion Models for High-Resolution Medical Image Synthesiscited by 56
  3. 2023MedSyn: Text-guided Anatomy-aware Synthesis of High-Fidelity 3D CT Imagescited by 41
  4. 2023DiffBoost: Enhancing Medical Image Segmentation via Text-Guided Diffusion Modelcited by 23
  5. 2024Generative Enhancement for 3D Medical Imagescited by 14
  6. 2024Deep Generative Models for 3D Medical Image Synthesiscited by 14
  7. 2023Metadata-Conditioned Generative Models to Synthesize Anatomically-Plausible 3D Brain MRIscited by 12
  8. 2024Replication in Visual Diffusion Models: A Survey and Outlookcited by 11
  9. 2024PASTA: Pathology-Aware MRI to PET Cross-Modal Translation with Diffusion Modelscited by 10
  10. 2024Latent Causal Modeling for 3D Brain MRI Counterfactualscited by 7
  11. 2024Vision-Language Synthetic Data Enhances Echocardiography Downstream Taskscited by 6
  12. 2024Addressing Asynchronicity in Clinical Multimodal Fusion via Individualized Chest X-ray Generationcited by 6
16 more
  1. 2025Diffusion Models for Computational Neuroimaging: A Surveycited by 5
  2. 2024Blaze3DM: Marry Triplane Representation with Diffusion for 3D Medical Inverse Problem Solvingcited by 4
  3. 2024A Comprehensive Survey on Diffusion Models and Their Applicationscited by 4
  4. 2025Latent Diffusion Autoencoders: Toward Efficient and Meaningful Unsupervised Representation Learning in Medical Imagingcited by 4
  5. 2025MedLoRD: A Medical Low-Resource Diffusion Model for High-Resolution 3D CT Image Synthesiscited by 3
  6. 2025Temporal Differential Fields for 4D Motion Modeling via Image-to-Video Synthesiscited by 3
  7. 2025Evaluation of 3D Counterfactual Brain MRI Generationcited by 2
  8. 2026Anatomically Guided Latent Diffusion for Brain MRI Progression Modelingcited by 2
  9. 2024FetalDiffusion: Pose-Controllable 3D Fetal MRI Synthesis with Conditional Diffusion Modelcited by 1
  10. 2024The Role of Language Models in Modern Healthcare: A Comprehensive Reviewcited by 1
  11. 2025Integrating Anatomical Priors into a Causal Diffusion Modelcited by 1
  12. 2026Cortex-Grounded Diffusion Models for Brain Image Generationcited by 1
  13. 2026Translating MRI to PET through Conditional Diffusion Models with Enhanced Pathology Awarenesscited by 1
  14. 2026Modality-Aware and Anatomical Vector-Quantized Autoencoding for Multimodal Brain MRIcited by 0
  15. 2026Progression as Latent Drift: Generative Forecasting of Slow-Evolving Pathologiescited by 0
  16. 2026AnaDiffusion: Anatomically CompositionalLatent Diffusion for Controllable 3D Brain MRI Generationcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Comparative Analysis of GAN and Diffusion for MRI-to-CT translation
  2. 2025Deep generative priors for 3D brain analysis
  3. 2024Cross-conditioned Diffusion Model for Medical Image to Image Translation
  4. 2023Make-A-Volume: Leveraging Latent Diffusion Models for Cross-Modality 3D Brain MRI Synthesis
  5. 2025Diffusion Models for conditional MRI generation
  6. 2025Benchmarking GANs, Diffusion Models, and Flow Matching for T1w-to-T2w MRI Translation
  7. 2025Scalable Diffusion Transformer for Conditional 4D fMRI Synthesis
  8. 2023A 3D generative model of pathological multi-modal MR images and segmentations