mlsanityData to 7 Oct 2026

Ambiguous Medical Image Segmentation using Diffusion Models

arXiv 2304.04745 ↗First posted 10 Apr 2023cs.CVcited by 92

On the map: Diffusion models → Medical imaging and segmentation

Abstract (arXiv)

Collective insights from a group of experts have always proven to outperform an individual's best diagnostic for clinical tasks. For the task of medical image segmentation, existing research on AI-based alternatives focuses more on developing models that can imitate the best individual rather than harnessing the power of expert groups. In this paper, we introduce a single diffusion model-based approach that produces multiple plausible outputs by learning a distribution over group insights. Our proposed model generates a distribution of segmentation masks by leveraging the inherent stochastic sampling process of diffusion using only minimal additional learning. We demonstrate on three different medical image modalities- CT, ultrasound, and MRI that our model is capable of producing several possible variants while capturing the frequencies of their occurrences. Comprehensive results show that our proposed approach outperforms existing state-of-the-art ambiguous segmentation networks in terms of accuracy while preserving naturally occurring variation. We also propose a new metric to evaluate the diversity as well as the accuracy of segmentation predictions that aligns with the interest of clinical practice of collective insights.

Key facts. Cited by 92 papers in the map (data through 7 Oct 2026). Placed in Medical imaging and segmentation, one of 14 directions in Diffusion models. Builds on 39 of its 63 references that are in the map. First posted on arXiv 10 Apr 2023.

Builds on

39 of 63 references.

Closest ancestors · 5

Same direction, newest first

  1. 2022MedSegDiff: Medical Image Segmentation with Diffusion Probabilistic Model1 Nov
  2. 2022Accelerating Diffusion Models via Pre-segmentation Diffusion Sampling for Medical Image Segmentation27 Oct
  3. 2021Diffusion Models for Implicit Image Segmentation Ensembles6 Dec
  4. 2021Label-Efficient Semantic Segmentation with Diffusion Models6 Dec
  5. 2021SegDiff: Image Segmentation with Diffusion Probabilistic Models1 Dec

Other references · 34

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  3. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
  4. 2013Auto-Encoding Variational Bayescited by 3,980
  5. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,736
  6. 2017What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?cited by 2,335
  7. 2016V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentationcited by 2,284
  8. 2021TransUNet: Transformers Make Strong Encoders for Medical Image Segmentationcited by 1,552
  9. 2018UNet++: A Nested U-Net Architecture for Medical Image Segmentationcited by 1,518
  10. 2022RePaint: Inpainting using Denoising Diffusion Probabilistic Modelscited by 1,419
  11. 2019Generating Diverse High-Fidelity Images with VQ-VAE-2cited by 1,376
  12. 2020Improved Techniques for Training Score-Based Generative Modelscited by 1,036
22 more
  1. 2021ILVR: Conditioning Method for Denoising Diffusion Probabilistic Modelscited by 634
  2. 2020Scaling Laws for Autoregressive Generative Modelingcited by 510
  3. 2021Medical Transformer: Gated Axial-Attention for Medical Image Segmentationcited by 319
  4. 2018A Probabilistic U-Net for Segmentation of Ambiguous Imagescited by 281
  5. 2019CE-Net: Context Encoder Network for 2D Medical Image Segmentationcited by 219
  6. 2015Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understandingcited by 218
  7. 2019ResUNet++: An Advanced Architecture for Medical Image Segmentationcited by 211
  8. 2022UNeXt: MLP-based Rapid Medical Image Segmentation Networkcited by 185
  9. 2019Transformation Consistent Self-ensembling Model for Semi-supervised Medical Image Segmentationcited by 138
  10. 2019PHiSeg: Capturing Uncertainty in Medical Image Segmentationcited by 128
  11. 2018Improving GANs Using Optimal Transportcited by 122
  12. 2017The Cramer Distance as a Solution to Biased Wasserstein Gradientscited by 116
  13. 2020Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertaintycited by 100
  14. 2019A Hierarchical Probabilistic U-Net for Modeling Multi-Scale Ambiguitiescited by 65
  15. 2022Diffusion Adversarial Representation Learning for Self-supervised Vessel Segmentationcited by 55
  16. 2020KiU-Net: Towards Accurate Segmentation of Biomedical Images using Over-complete Representationscited by 49
  17. 2020KiU-Net: Overcomplete Convolutional Architectures for Biomedical Image and Volumetric Segmentationcited by 32
  18. 2020Uncertainty quantification in medical image segmentation with normalizing flowscited by 23
  19. 2022Generalized Probabilistic U-Net for medical image segementationcited by 10
  20. 2020Modal Uncertainty Estimation via Discrete Latent Representationcited by 4
  21. 2022Orientation-guided Graph Convolutional Network for Bone Surface Segmentationcited by 2
  22. 2022Simultaneous Bone and Shadow Segmentation Network using Task Correspondence Consistencycited by 1

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 20; 2024: 23; 2025: 30; 2026: 19.

92 papers.

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  1. 2024A Comprehensive Survey of Foundation Models in Medicinecited by 56
  2. 2023AdaptiveSAM: Towards Efficient Tuning of SAM for Surgical Scene Segmentationcited by 37
  3. 2024Image Segmentation in Foundation Model Era: A Surveycited by 35
  4. 2023Contrastive Conditional Latent Diffusion for Audio-visual Segmentationcited by 30
  5. 2023Diffusion Model for Camouflaged Object Detectioncited by 27
  6. 2024FlowSDF: Flow Matching for Medical Image Segmentation Using Distance Transformscited by 25
  7. 2023DiffBoost: Enhancing Medical Image Segmentation via Text-Guided Diffusion Modelcited by 23
  8. 2023CamoDiffusion: Camouflaged Object Detection via Conditional Diffusion Modelscited by 21
  9. 2023GCD-DDPM: A Generative Change Detection Model Based on Difference-Feature Guided DDPMcited by 21
  10. 2024Tyche: Stochastic In-Context Learning for Medical Image Segmentationcited by 20
  11. 2023Treatment-aware Diffusion Probabilistic Model for Longitudinal MRI Generation and Diffuse Glioma Growth Predictioncited by 19
  12. 2024FreeSeg-Diff: Training-Free Open-Vocabulary Segmentation with Diffusion Modelscited by 12
38 more
  1. 2024Generative AI-Driven Human Digital Twin in IoT-Healthcare: A Comprehensive Surveycited by 11
  2. 2024S-SAM: SVD-based Fine-Tuning of Segment Anything Model for Medical Image Segmentationcited by 11
  3. 2023Annotator Consensus Prediction for Medical Image Segmentation with Diffusion Modelscited by 10
  4. 2023A Survey of Emerging Applications of Diffusion Probabilistic Models in MRIcited by 9
  5. 2024Diversified and Personalized Multi-rater Medical Image Segmentationcited by 9
  6. 2024Pi-fusion: Physics-informed diffusion model for learning fluid dynamicscited by 9
  7. 2024SimuScope: Realistic Endoscopic Synthetic Dataset Generation through Surgical Simulation and Diffusion Modelscited by 8
  8. 2024A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentationcited by 6
  9. 2025MIFNet: Learning Modality-Invariant Features for Generalizable Multimodal Image Matchingcited by 6
  10. 2023A Recycling Training Strategy for Medical Image Segmentation with Diffusion Denoising Modelscited by 5
  11. 2025Conditional diffusion model with spatial attention and latent embedding for medical image segmentationcited by 5
  12. 2025Aleatoric Uncertainty Medical Image Segmentation Estimation via Flow Matchingcited by 5
  13. 2025Ambiguous Medical Image Segmentation Using Diffusion Schr"odinger Bridgecited by 5
  14. 2023C-DARL: Contrastive diffusion adversarial representation learning for label-free blood vessel segmentationcited by 4
  15. 2024Prompt-Softbox-Prompt: A Free-Text Embedding Control for Image Editingcited by 4
  16. 2024RadGazeGen: Radiomics and Gaze-guided Medical Image Generation using Diffusion Modelscited by 4
  17. 2025DiffAtlas: GenAI-fying Atlas Segmentation via Image-Mask Diffusioncited by 4
  18. 2025BrainMRDiff: A Diffusion Model for Anatomically Consistent Brain MRI Synthesiscited by 4
  19. 2025Conditional Latent Diffusion Models for Zero-Shot Instance Segmentationcited by 4
  20. 2023GenSelfDiff-HIS: Generative Self-Supervision Using Diffusion for Histopathological Image Segmentationcited by 3
  21. 2024Denoising Diffusion Models for Anomaly Localization in Medical Imagescited by 3
  22. 2025Diverse Image Generation with Diffusion Models and Cross Class Label Learning for Polyp Classificationcited by 3
  23. 2025Clinical Inspired MRI Lesion Segmentationcited by 3
  24. 2025Flow Stochastic Segmentation Networkscited by 3
  25. 2025FS-Diff: Semantic guidance and clarity-aware simultaneous multimodal image fusion and super-resolutioncited by 3
  26. 2026Imagine Before Concentration: Diffusion-Guided Registers Enhance Partially Relevant Video Retrievalcited by 3
  27. 2023Investigating and Improving Latent Density Segmentation Models for Aleatoric Uncertainty Quantification in Medical Imagingcited by 2
  28. 2023Surf-CDM: Score-Based Surface Cold-Diffusion Model For Medical Image Segmentationcited by 2
  29. 2025Marine Saliency Segmenter: Object-Focused Conditional Diffusion with Region-Level Semantic Knowledge Distillationcited by 2
  30. 2025UniSegDiff: Boosting Unified Lesion Segmentation via a Staged Diffusion Modelcited by 2
  31. 2025A Comprehensive Review of Diffusion Models in Smart Agriculture: Progress, Applications, and Challengescited by 2
  32. 2025Diffusion-FS: Multimodal Free-Space Prediction via Diffusion for Autonomous Drivingcited by 2
  33. 2025Generic Event Boundary Detection via Denoising Diffusioncited by 2
  34. 2025StereoSpace: Depth-Free Synthesis of Stereo Geometry via End-to-End Diffusion in a Canonical Spacecited by 2
  35. 2023Learning A Coarse-to-Fine Diffusion Transformer for Image Restorationcited by 1
  36. 2023BeSt-LeS: Benchmarking Stroke Lesion Segmentation using Deep Supervisioncited by 1
  37. 2023PULASki: Learning inter-rater variability using statistical distances to improve probabilistic segmentationcited by 1
  38. 2024Mitigate Target-level Insensitivity of Infrared Small Target Detection via Posterior Distribution Modelingcited by 1

50 most cited of 92 All 92 (JSON)

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  1. 2024Analysing Diffusion Segmentation for Medical Images
  2. 2024Enhancing Medical Image Segmentation with Deep Learning and Diffusion Models
  3. 2025DiffOSeg: Omni Medical Image Segmentation via Multi-Expert Collaboration Diffusion Model
  4. 2024Latent Diffusion for Medical Image Segmentation: End to end learning for fast sampling and accuracy
  5. 2024CTS: A Consistency-Based Medical Image Segmentation Model
  6. 2023Robust semi-supervised segmentation with timestep ensembling diffusion models
  7. 2023Diff-UNet: A Diffusion Embedded Network for Volumetric Segmentation
  8. 2025Noise-Consistent Siamese-Diffusion for Medical Image Synthesis and Segmentation