mlsanityData to 7 Oct 2026

A Morphology Focused Diffusion Probabilistic Model for Synthesis of Histopathology Images

arXiv 2209.13167 ↗First posted 27 Sep 2022eess.IV cs.CVcited by 74

On the map: Diffusion models → Medical imaging and segmentation

Abstract (arXiv)

Visual microscopic study of diseased tissue by pathologists has been the cornerstone for cancer diagnosis and prognostication for more than a century. Recently, deep learning methods have made significant advances in the analysis and classification of tissue images. However, there has been limited work on the utility of such models in generating histopathology images. These synthetic images have several applications in pathology including utilities in education, proficiency testing, privacy, and data sharing. Recently, diffusion probabilistic models were introduced to generate high quality images. Here, for the first time, we investigate the potential use of such models along with prioritized morphology weighting and color normalization to synthesize high quality histopathology images of brain cancer. Our detailed results show that diffusion probabilistic models are capable of synthesizing a wide range of histopathology images and have superior performance compared to generative adversarial networks.

Key facts. Cited by 74 papers in the map (data through 7 Oct 2026). Placed in Medical imaging and segmentation, one of 14 directions in Diffusion models. Builds on 26 of its 48 references that are in the map. First posted on arXiv 27 Sep 2022.

Builds on

26 of 48 references.

Closest ancestors · 1

Same direction, newest first

  1. 2021SegDiff: Image Segmentation with Diffusion Probabilistic Models1 Dec

Other references · 25

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  3. 2022Generative Adversarial Networkscited by 5,603
  4. 2015Rethinking the Inception Architecture for Computer Visioncited by 5,451
  5. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,736
  6. 2017Progressive Growing of GANs for Improved Quality, Stability, and Variationcited by 2,967
  7. 2016Improved Techniques for Training GANscited by 2,938
  8. 2018Large Scale GAN Training for High Fidelity Natural Image Synthesiscited by 2,609
  9. 2018ESRGAN: Enhanced Super-Resolution Generative Adversarial Networkscited by 1,250
  10. 2019Improved Precision and Recall Metric for Assessing Generative Modelscited by 925
  11. 2021Tackling the Generative Learning Trilemma with Denoising Diffusion GANscited by 515
  12. 2021Grad-TTS: A Diffusion Probabilistic Model for Text-to-Speechcited by 445
13 more
  1. 2016Tutorial on Variational Autoencoderscited by 404
  2. 2022Perception Prioritized Training of Diffusion Modelscited by 301
  3. 2021Generating Images with Sparse Representationscited by 262
  4. 2018cGANs with Projection Discriminatorcited by 253
  5. 2018A Note on the Inception Scorecited by 225
  6. 2022The Role of ImageNet Classes in Fr'echet Inception Distancecited by 211
  7. 2019Deep neural network models for computational histopathology: A surveycited by 165
  8. 2020Federated Learning for Computational Pathology on Gigapixel Whole Slide Imagescited by 54
  9. 2021Selective Synthetic Augmentation with HistoGAN for Improved Histopathology Image Classificationcited by 35
  10. 2020Diffusion models for Handwriting Generationcited by 25
  11. 2018Multi-Resolution Networks for Semantic Segmentation in Whole Slide Imagescited by 14
  12. 2018Deep Semi Supervised Generative Learning for Automated PD-L1 Tumor Cell Scoring on NSCLC Tissue Needle Biopsiescited by 9
  13. 2020Private data sharing between decentralized users through the privGAN architecturecited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 24; 2024: 30; 2025: 14; 2026: 4.

74 papers.

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  1. 2022Diffusion Models for Medical Image Analysis: A Comprehensive Surveycited by 269
  2. 2022Diffusion Probabilistic Models beat GANs on Medical Imagescited by 77
  3. 2023PathLDM: Text conditioned Latent Diffusion Model for Histopathologycited by 51
  4. 2023Deep Learning Approaches for Data Augmentation in Medical Imaging: A Reviewcited by 48
  5. 2023Learned representation-guided diffusion models for large-image generationcited by 39
  6. 20243D MedDiffusion: A 3D Medical Latent Diffusion Model for Controllable and High-quality Medical Image Generationcited by 37
  7. 2024Conditional Image Synthesis with Diffusion Models: A Surveycited by 29
  8. 2023DiffInfinite: Large Mask-Image Synthesis via Parallel Random Patch Diffusion in Histopathologycited by 28
  9. 2024Data-Centric Foundation Models in Computational Healthcare: A Surveycited by 27
  10. 2023Beware of diffusion models for synthesizing medical images -- A comparison with GANs in terms of memorizing brain MRI and chest x-ray imagescited by 23
  11. 2023NASDM: Nuclei-Aware Semantic Histopathology Image Generation Using Diffusion Modelscited by 18
  12. 2023Synthetic Augmentation with Large-scale Unconditional Pre-trainingcited by 18
38 more
  1. 2024Generative Modelling of Structurally Constrained Graphscited by 17
  2. 2023ViT-DAE: Transformer-driven Diffusion Autoencoder for Histopathology Image Analysiscited by 15
  3. 2024ZoomLDM: Latent Diffusion Model for multi-scale image generationcited by 15
  4. 2023Synthesising Rare Cataract Surgery Samples with Guided Diffusion Modelscited by 14
  5. 2024Enhancing Label-efficient Medical Image Segmentation with Text-guided Diffusion Modelscited by 13
  6. 2024Generative AI-Driven Human Digital Twin in IoT-Healthcare: A Comprehensive Surveycited by 11
  7. 2025PixCell: A generative foundation model for digital histopathology imagescited by 11
  8. 2023Diffusion-based generation of Histopathological Whole Slide Images at a Gigapixel scalecited by 9
  9. 2024Cascaded Multi-path Shortcut Diffusion Model for Medical Image Translationcited by 9
  10. 2023Multi-Level Global Context Cross Consistency Model for Semi-Supervised Ultrasound Image Segmentation with Diffusion Modelcited by 8
  11. 2024Diff-Def: Diffusion-Generated Deformation Fields for Conditional Atlasescited by 8
  12. 2024VM-DDPM: Vision Mamba Diffusion for Medical Image Synthesiscited by 8
  13. 2024Co-synthesis of Histopathology Nuclei Image-Label Pairs using a Context-Conditioned Joint Diffusion Modelcited by 8
  14. 2025A Review on Generative AI For Text-To-Image and Image-To-Image Generation and Implications To Scientific Imagescited by 8
  15. 2025PathDiff: Histopathology Image Synthesis with Unpaired Text and Mask Conditionscited by 8
  16. 2023Bi-parametric prostate MR image synthesis using pathology and sequence-conditioned stable diffusioncited by 7
  17. 2024Exploring Privacy and Fairness Risks in Sharing Diffusion Models: An Adversarial Perspectivecited by 6
  18. 2024F2FLDM: Latent Diffusion Models with Histopathology Pre-Trained Embeddings for Unpaired Frozen Section to FFPE Translationcited by 6
  19. 2024Deep learning for automated detection of breast cancer in deep ultraviolet fluorescence images with diffusion probabilistic modelcited by 6
  20. 2023A Recycling Training Strategy for Medical Image Segmentation with Diffusion Denoising Modelscited by 5
  21. 2024BSDA: Bayesian Random Semantic Data Augmentation for Medical Image Classificationcited by 5
  22. 2025Content Generation Models in Computational Pathology: A Comprehensive Survey on Methods, Applications, and Challengescited by 5
  23. 2025Multimodal LLM-Guided Semantic Correction in Text-to-Image Diffusioncited by 5
  24. 2023MedAugment: Universal Automatic Data Augmentation Plug-in for Medical Image Analysiscited by 4
  25. 2023A Unified Framework for Generative Data Augmentation: A Comprehensive Surveycited by 4
  26. 2023Improving Robustness and Reliability in Medical Image Classification with Latent-Guided Diffusion and Nested-Ensemblescited by 4
  27. 2023Generating Progressive Images from Pathological Transitions via Diffusion Modelcited by 4
  28. 2024URCDM: Ultra-Resolution Image Synthesis in Histopathologycited by 4
  29. 2023GenSelfDiff-HIS: Generative Self-Supervision Using Diffusion for Histopathological Image Segmentationcited by 3
  30. 2023Latent Diffusion Models with Image-Derived Annotations for Enhanced AI-Assisted Cancer Diagnosis in Histopathologycited by 3
  31. 2024Style-Extracting Diffusion Models for Semi-Supervised Histopathology Segmentationcited by 3
  32. 2024DISC: Latent Diffusion Models with Self-Distillation from Separated Conditions for Prostate Cancer Gradingcited by 3
  33. 2025PosDiffAE: Position-aware Diffusion Auto-encoder For High-Resolution Brain Tissue Classification Incorporating Artifact Restorationcited by 3
  34. 2025Semantic and Visual Crop-Guided Diffusion Models for Heterogeneous Tissue Synthesis in Histopathologycited by 3
  35. 2023Tertiary Lymphoid Structures Generation through Graph-based Diffusioncited by 2
  36. 2024HAGAN: Hybrid Augmented Generative Adversarial Network for Medical Image Synthesiscited by 2
  37. 2024Mask-guided cross-image attention for zero-shot in-silico histopathologic image generation with a diffusion modelcited by 2
  38. 2024Synthetic Augmentation for Anatomical Landmark Localization using DDPMscited by 2

50 most cited of 74 All 74 (JSON)

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  1. 2025Graph Conditioned Diffusion for Controllable Histopathology Image Generation
  2. 2025Prototype-Guided Diffusion for Digital Pathology: Achieving Foundation Model Performance with Minimal Clinical Data
  3. 2026Assessment of Conditional Diffusion Model for Synthetic Histopathology Image Generation
  4. 2022Improved HER2 Tumor Segmentation with Subtype Balancing using Deep Generative Networks
  5. 2024Improving text-conditioned latent diffusion for cancer pathology
  6. 2026CytoSyn: a Foundation Diffusion Model for Histopathology -- Tech Report
  7. 2026Controllable Histopathology Image Synthesis with Training-free Structural Initialization and Textural Modulation
  8. 2026A Generative Foundation Model for Multimodal Histopathology