mlsanityData to 7 Oct 2026

What is Healthy? Generative Counterfactual Diffusion for Lesion Localization

arXiv 2207.12268 ↗First posted 25 Jul 2022cs.CV cs.AIcited by 52

Not on the map. Why?

Cited by 27 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Reducing the requirement for densely annotated masks in medical image segmentation is important due to cost constraints. In this paper, we consider the problem of inferring pixel-level predictions of brain lesions by only using image-level labels for training. By leveraging recent advances in generative diffusion probabilistic models (DPM), we synthesize counterfactuals of "How would a patient appear if X pathology was not present?". The difference image between the observed patient state and the healthy counterfactual can be used for inferring the location of pathology. We generate counterfactuals that correspond to the minimal change of the input such that it is transformed to healthy domain. This requires training with healthy and unhealthy data in DPMs. We improve on previous counterfactual DPMs by manipulating the generation process with implicit guidance along with attention conditioning instead of using classifiers. Code is available at https://github.com/vios-s/Diff-SCM.

Key facts. Cited by 52 papers in the map (data through 7 Oct 2026). Builds on 19 of its 23 references that are in the map. First posted on arXiv 25 Jul 2022.

Builds on

19 of 23 references.

References · 19

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  3. 2020Denoising Diffusion Implicit Modelscited by 9,655
  4. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  5. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
  6. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,322
  7. 2021GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Modelscited by 3,595
  8. 2018Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challengecited by 508
  9. 2022Diffusion Models for Medical Anomaly Detectioncited by 231
  10. 2020Deep Structural Causal Models for Tractable Counterfactual Inferencecited by 210
  11. 2020Autoencoders for Unsupervised Anomaly Segmentation in Brain MR Images: A Comparative Studycited by 146
  12. 2022Fast Unsupervised Brain Anomaly Detection and Segmentation with Diffusion Modelscited by 96
7 more
  1. 2022Diffusion Causal Models for Counterfactual Estimationcited by 87
  2. 2019Unsupervised Anomaly Localization using Variational Auto-Encoderscited by 73
  3. 2020Unsupervised Lesion Detection via Image Restoration with a Normative Priorcited by 65
  4. 2018Context-encoding Variational Autoencoder for Unsupervised Anomaly Detectioncited by 63
  5. 2021Challenging Current Semi-Supervised Anomaly Segmentation Methods for Brain MRIcited by 23
  6. 2020Pseudo-healthy synthesis with pathology disentanglement and adversarial learningcited by 19
  7. 2020Unsupervised anomaly localization using VAE and beta-VAEcited by 8

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 3; 2023: 19; 2024: 22; 2025: 3; 2026: 5.

52 papers.

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  1. 2022Diffusion Models in Vision: A Surveycited by 1,008
  2. 2022Diffusion Models for Medical Image Analysis: A Comprehensive Surveycited by 269
  3. 2022A Survey on Generative Diffusion Modelcited by 238
  4. 2023Generative AI for Medical Imaging: extending the MONAI Frameworkcited by 68
  5. 2023High Fidelity Image Counterfactuals with Probabilistic Causal Modelscited by 53
  6. 2023Diffusion-based Data Augmentation for Skin Disease Classification: Impact Across Original Medical Datasets to Fully Synthetic Imagescited by 45
  7. 2023Patched Diffusion Models for Unsupervised Anomaly Detection in Brain MRIcited by 45
  8. 2023RadEdit: stress-testing biomedical vision models via diffusion image editingcited by 28
  9. 2023Unsupervised Anomaly Detection in Medical Images Using Masked Diffusion Modelcited by 25
  10. 2023The role of noise in denoising models for anomaly detection in medical imagescited by 23
  11. 2024Benchmarking Counterfactual Image Generationcited by 22
  12. 2023Privacy Distillation: Reducing Re-identification Risk of Multimodal Diffusion Modelscited by 18
38 more
  1. 2023Guided Reconstruction with Conditioned Diffusion Models for Unsupervised Anomaly Detection in Brain MRIscited by 18
  2. 2023DreaMR: Diffusion-driven Counterfactual Explanation for Functional MRIcited by 14
  3. 2024Deep Generative Models for 3D Medical Image Synthesiscited by 14
  4. 2024Diffusion-based Iterative Counterfactual Explanations for Fetal Ultrasound Image Quality Assessmentcited by 13
  5. 2024Robust image representations with counterfactual contrastive learningcited by 12
  6. 2024Counterfactual contrastive learning: robust representations via causal image synthesiscited by 11
  7. 2024CardiacNet: Learning to Reconstruct Abnormalities for Cardiac Disease Assessment from Echocardiogram Videoscited by 11
  8. 2023Emerging Synergies in Causality and Deep Generative Models: A Surveycited by 10
  9. 2024Counterfactual Explanations for Medical Image Classification and Regression using Diffusion Autoencodercited by 10
  10. 2023Beyond Known Reality: Exploiting Counterfactual Explanations for Medical Researchcited by 9
  11. 2023A Survey of Emerging Applications of Diffusion Probabilistic Models in MRIcited by 9
  12. 2025Conditional Diffusion Models are Medical Image Classifiers that Provide Explainability and Uncertainty for Freecited by 9
  13. 2024Diff-Def: Diffusion-Generated Deformation Fields for Conditional Atlasescited by 8
  14. 2024Generating Counterfactual Trajectories with Latent Diffusion Models for Concept Discoverycited by 8
  15. 2024MedEdit: Counterfactual Diffusion-based Image Editing on Brain MRIcited by 8
  16. 2025Diffusion Counterfactual Generation with Semantic Abductioncited by 8
  17. 2024Binary Noise for Binary Tasks: Masked Bernoulli Diffusion for Unsupervised Anomaly Detectioncited by 7
  18. 2024Zero-Shot Medical Phrase Grounding with Off-the-shelf Diffusion Modelscited by 7
  19. 2023Class-Guided Image-to-Image Diffusion: Cell Painting from Brightfield Images with Class Labelscited by 6
  20. 2025Causally Steered Diffusion for Automated Video Counterfactual Generationcited by 5
  21. 2023Unsupervised Discovery of 3D Hierarchical Structure with Generative Diffusion Featurescited by 4
  22. 2024Promptable Counterfactual Diffusion Model for Unified Brain Tumor Segmentation and Generation with MRIscited by 4
  23. 2024Enhancing Reconstruction-Based Out-of-Distribution Detection in Brain MRI with Model and Metric Ensemblescited by 4
  24. 2023A Two-Stage Generative Model with CycleGAN and Joint Diffusion for MRI-based Brain Tumor Detectioncited by 3
  25. 2023Generating Realistic Counterfactuals for Retinal Fundus and OCT Images using Diffusion Modelscited by 3
  26. 2024Applications of interpretable deep learning in neuroimaging: a comprehensive reviewcited by 3
  27. 2024Denoising Diffusion Models for Anomaly Localization in Medical Imagescited by 3
  28. 2024VALD-MD: Visual Attribution via Latent Diffusion for Medical Diagnosticscited by 2
  29. 2024Reimagining Anomalies: What If Anomalies Were Normal?cited by 2
  30. 2024AnoFPDM: Anomaly Segmentation with Forward Process of Diffusion Models for Brain MRIcited by 2
  31. 2023Characterizing the Features of Mitotic Figures Using a Conditional Diffusion Probabilistic Modelcited by 1
  32. 2024Discrepancy-based Diffusion Models for Lesion Detection in Brain MRIcited by 1
  33. 2026An Interpretable Local Editing Model for Counterfactual Medical Image Generationcited by 1
  34. 2023Causal Image Synthesis of Brain MR in 3Dcited by 0
  35. 2024IgCONDA-PET: Weakly-Supervised PET Anomaly Detection using Implicitly-Guided Attention-Conditional Counterfactual Diffusion Modeling -- a Multi-Center, Multi-Cancer, and Multi-Tracer Studycited by 0
  36. 2024Longitudinal Causal Image Synthesiscited by 0
  37. 2026PolypSteer: Counterfactual Endoscopic Synthesis via Training-Free Activation Steeringcited by 0
  38. 2026Weakly-Supervised Lung Nodule Segmentation via Training-Free Guidance of 3D Rectified Flowcited by 0

50 most cited of 52 All 52 (JSON)

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  1. 2023Diffusion Models for Counterfactual Generation and Anomaly Detection in Brain Images
  2. 2025Generating healthy counterfactuals with denoising diffusion bridge models
  3. 2024Counterfactual MRI Data Augmentation using Conditional Denoising Diffusion Generative Models
  4. 2024Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis
  5. 2026Generating Medical Image Counterfactuals using Causal Explanations
  6. 2026MedDiME: Efficient Latent Diffusion with Adaptive Masking for Medical Counterfactual Generation
  7. 2023BiomedJourney: Counterfactual Biomedical Image Generation by Instruction-Learning from Multimodal Patient Journeys
  8. 2025PRISM: High-Resolution & Precise Counterfactual Medical Image Generation using Language-guided Stable Diffusion