mlsanityData to 14 Oct 2026

Fast-DDPM: Fast Denoising Diffusion Probabilistic Models for Medical Image-to-Image Generation

arXiv 2405.14802 ↗First posted 23 May 2024eess.IV cs.CVcited by 33

On the map: Diffusion models → Medical imaging and segmentation

Abstract (arXiv)

Denoising diffusion probabilistic models (DDPMs) have achieved unprecedented success in computer vision. However, they remain underutilized in medical imaging, a field crucial for disease diagnosis and treatment planning. This is primarily due to the high computational cost associated with (1) the use of large number of time steps (e.g., 1,000) in diffusion processes and (2) the increased dimensionality of medical images, which are often 3D or 4D. Training a diffusion model on medical images typically takes days to weeks, while sampling each image volume takes minutes to hours. To address this challenge, we introduce Fast-DDPM, a simple yet effective approach capable of improving training speed, sampling speed, and generation quality simultaneously. Unlike DDPM, which trains the image denoiser across 1,000 time steps, Fast-DDPM trains and samples using only 10 time steps. The key to our method lies in aligning the training and sampling procedures to optimize time-step utilization. Specifically, we introduced two efficient noise schedulers with 10 time steps: one with uniform time step sampling and another with non-uniform sampling. We evaluated Fast-DDPM across three medical image-to-image generation tasks: multi-image super-resolution, image denoising, and image-to-image translation. Fast-DDPM outperformed DDPM and current state-of-the-art methods based on convolutional networks and generative adversarial networks in all tasks. Additionally, Fast-DDPM reduced the training time to 0.2x and the sampling time to 0.01x compared to DDPM. Our code is publicly available at: https://github.com/mirthAI/Fast-DDPM.

Key facts. Cited by 33 papers in the map (data through 14 Oct 2026). Placed in Medical imaging and segmentation, one of 14 directions in Diffusion models. Builds on 51 of its 62 references that are in the map. First posted on arXiv 23 May 2024.

Builds on

51 of 62 references.

Closest ancestors · 13

Same direction, newest first

  1. 2024MAEDiff: Masked Autoencoder-enhanced Diffusion Models for Unsupervised Anomaly Detection in Brain Images19 Jan
  2. 2023Adaptive Latent Diffusion Model for 3D Medical Image to Image Translation: Multi-modal Magnetic Resonance Imaging Study1 Nov
  3. 2023InverseSR: 3D Brain MRI Super-Resolution Using a Latent Diffusion Model23 Aug
  4. 2023Conditional Diffusion Models for Weakly Supervised Medical Image Segmentation6 Jun
  5. 2023Unsupervised Anomaly Detection in Medical Images Using Masked Diffusion Model31 May
  6. 2023Diff-UNet: A Diffusion Embedded Network for Volumetric Segmentation18 Mar
  7. 2022DOLCE: A Model-Based Probabilistic Diffusion Framework for Limited-Angle CT Reconstruction22 Nov
  8. 2022PET image denoising based on denoising diffusion probabilistic models13 Sep
  9. 2022High-Frequency Space Diffusion Models for Accelerated MRI10 Aug
  10. 2022Unsupervised Medical Image Translation with Adversarial Diffusion Models17 Jul
  11. 2022Adaptive Diffusion Priors for Accelerated MRI Reconstruction12 Jul
  12. 2022Diffusion Models for Medical Anomaly Detection8 Mar
1 more
  1. 2021DiffuseMorph: Unsupervised Deformable Image Registration Using Diffusion Model9 Dec

Other references · 38

  1. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  3. 2020Denoising Diffusion Implicit Modelscited by 9,781
  4. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 9,122
  5. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,255
  6. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,585
  7. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,355
  8. 2016Image-to-Image Translation with Conditional Adversarial Networkscited by 4,527
  9. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,761
  10. 2022Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flowcited by 3,700
  11. 2021GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Modelscited by 3,614
  12. 2022DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Stepscited by 1,979
26 more
  1. 2023Consistency Modelscited by 1,822
  2. 2021Image Super-Resolution via Iterative Refinementcited by 1,511
  3. 2021Palette: Image-to-Image Diffusion Modelscited by 1,300
  4. 2014Image Super-Resolution Using Deep Convolutional Networkscited by 1,224
  5. 2021Variational Diffusion Modelscited by 1,153
  6. 2022DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Modelscited by 938
  7. 2023Adversarial Diffusion Distillationcited by 759
  8. 2022On Distillation of Guided Diffusion Modelscited by 725
  9. 2023Simple diffusion: End-to-end diffusion for high resolution imagescited by 422
  10. 2021SRDiff: Single Image Super-Resolution with Diffusion Probabilistic Modelscited by 415
  11. 2023DeepCache: Accelerating Diffusion Models for Freecited by 359
  12. 2023Q-Diffusion: Quantizing Diffusion Modelscited by 273
  13. 2022Post-training Quantization on Diffusion Modelscited by 267
  14. 2017Low-Dose CT with a Residual Encoder-Decoder Convolutional Neural Network (RED-CNN)cited by 224
  15. 2023On the Importance of Noise Scheduling for Diffusion Modelscited by 194
  16. 2022Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Qualitycited by 182
  17. 2022Fast Sampling of Diffusion Models via Operator Learningcited by 175
  18. 2021On Fast Sampling of Diffusion Probabilistic Modelscited by 170
  19. 2018MedGAN: Medical Image Translation using GANscited by 152
  20. 2021Breaking the Dilemma of Medical Image-to-image Translationcited by 82
  21. 2022Conversion Between CT and MRI Images Using Diffusion and Score-Matching Modelscited by 69
  22. 2022MR Image Denoising and Super-Resolution Using Regularized Reverse Diffusioncited by 67
  23. 2022SinDDM: A Single Image Denoising Diffusion Modelcited by 60
  24. 2022Diffusion Adversarial Representation Learning for Self-supervised Vessel Segmentationcited by 55
  25. 2021DU-GAN: Generative Adversarial Networks with Dual-Domain U-Net Based Discriminators for Low-Dose CT Denoisingcited by 46
  26. 2021Geodesic Density Regression for Correcting 4DCT Pulmonary Respiratory Motion Artifactscited by 6

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 3; 2025: 18; 2026: 12.

33 papers.

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  1. 2025Regression is all you need for medical image translationcited by 8
  2. 2024Deformation-Recovery Diffusion Model (DRDM): Instance Deformation for Image Manipulation and Synthesiscited by 7
  3. 2025VasTSD: Learning 3D Vascular Tree-state Space Diffusion Model for Angiography Synthesiscited by 6
  4. 2024Physics-Inspired Generative Models in Medical Imaging: A Reviewcited by 5
  5. 2025Interactive Gadolinium-Free MRI Synthesis: A Transformer with Localization Prompt Learningcited by 3
  6. 2025PET Image Denoising via Text-Guided Diffusion: Integrating Anatomical Priors through Text Promptscited by 2
  7. 2025Diffusion Bridge Models for 3D Medical Image Translationcited by 2
  8. 2025TimeFlow: Towards Stochastic-Aware and Efficient Time Series Generation via Flow Matching Modelingcited by 2
  9. 2025Early Lung Cancer Diagnosis from Virtual Follow-up LDCT Generation via Correlational Autoencoder and Latent Flow Matchingcited by 2
  10. 2026MRI-to-CT synthesis using drifting modelscited by 2
  11. 2025Segmentation-Guided CT Synthesis with Pixel-Wise Conformal Uncertainty Boundscited by 1
  12. 2025PWD: Prior-Guided and Wavelet-Enhanced Diffusion Model for Limited-Angle CTcited by 1
21 more
  1. 2025MAN: Latent Diffusion Enhanced Multistage Anti-Noise Network for Efficient and High-Quality Low-Dose CT Image Denoisingcited by 1
  2. 2025Discrete Diffusion Models with MLLMs for Unified Medical Multimodal Generationcited by 1
  3. 2026SRUG: A Fusion-Driven Generator Network for Medical Image Translationcited by 1
  4. 2026MRI Cross-Modal Synthesis: A Comparative Study of Generative Models for T1-to-T2 Reconstructioncited by 1
  5. 2026Heterogeneous Decentralized Diffusion Modelscited by 1
  6. 2026Trust but Verify: Mitigating Medical Hallucinations via Post-Hoc Adversarial Auditing and Multi-Agent Feedback Loopscited by 1
  7. 2024Evaluating Utility of Memory Efficient Medical Image Generation: A Study on Lung Nodule Segmentationcited by 0
  8. 2025Geodesic Diffusion Models for Efficient Medical Image Enhancementcited by 0
  9. 2025Deterministic Medical Image Translation via High-fidelity Brownian Bridgescited by 0
  10. 2025Score-based Generative Diffusion Models to Synthesize Full-dose FDG Brain PET from MRI in Epilepsy Patientscited by 0
  11. 2025BrainNormalizer: Anatomy-Informed Pseudo-Healthy Brain Reconstruction from Tumor MRI via Edge-Guided ControlNetcited by 0
  12. 2025Towards Overcoming Data Scarcity in Nuclear Energy: A Study on Critical Heat Flux with Physics-consistent Conditional Diffusion Modelcited by 0
  13. 2025Sawtooth Sampling for Time Series Denoising Diffusion Implicit Modelscited by 0
  14. 2025Diffusion-Based Synthesis of 3D T1w MPRAGE Images from Multi-Echo GRE with Multi-Parametric MRI Integrationcited by 0
  15. 2026TAFG-MAN: Timestep-Adaptive Frequency-Gated Latent Diffusion for Efficient and High-Quality Low-Dose CT Image Denoisingcited by 0
  16. 2026Sketch2CT: Multimodal Diffusion for Structure-Aware 3D Medical Volume Generationcited by 0
  17. 2026HUydra: Full-Range Lung CT Synthesis via Multiple HU Interval Generative Modellingcited by 0
  18. 2026Structure-Adaptive Sparse Diffusion in Voxel Space for 3D Medical Image Enhancementcited by 0
  19. 2026Joint Medical Image Enhancement and Segmentation with Diffusion-based Symbiotic Information Interactioncited by 0
  20. 2026Learning Where and What to Lift for Bi-planar X-ray-to-CT Reconstructioncited by 0
  21. 2026Efficient 3D Whole-Body PET Image Denoising via Conditional Rectified Flow With Optimized Sampling Strategycited by 0

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  2. 2025Computationally Efficient Diffusion Models in Medical Imaging: A Comprehensive Review
  3. 2024Denoising Diffusion Probabilistic Models in Six Simple Steps
  4. 2021Learning to Efficiently Sample from Diffusion Probabilistic Models
  5. 2022Diffusion Models for Medical Image Analysis: A Comprehensive Survey
  6. 2023Assessing the capacity of a denoising diffusion probabilistic model to reproduce spatial context
  7. 2026VS-DDPM: Efficient Low-Cost Diffusion Model for Medical Modality Translation
  8. 2022Accelerating Diffusion Models via Early Stop of the Diffusion Process