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⚡ News:

• [29/09/2025] 🎉 Our survey has been accepted by IEEE Reviews in Biomedical Engineering (RBME)! Cheers！
• [16/05/2025] 📖 Our survey is available on arXiv.

😊 Citation

If you find this work helpful, please ⭐ star this repo or cite our survey — your support means the world to us! 🚀💖

@misc{zhang2025generativemodelscomputationalpathology,
      title={Content Generation Models in Computational Pathology: A Comprehensive Survey on Methods, Applications, and Challenges}, 
      author={Yuan Zhang and Xinfeng Zhang and Xiaoming Qi and Xinyu Wu and Feng Chen and Guanyu Yang and Huazhu Fu},
      year={2025},
      eprint={2505.10993},
      archivePrefix={arXiv},
      primaryClass={eess.IV},
      url={https://arxiv.org/abs/2505.10993}, 
}

Note: The volume, number, pages, and DOI will be updated upon final publication.

📌 Our Contribution

We explore content generation modeling in the field of computational pathology — using generative models to create images, text, and molecular data that can help improve diagnostic tasks.

Our work organizes recent progress into four key areas:

🖼️ Image Generation – from tissue patches to whole-slide images

📝 Text Generation – clinical report synthesis and captioning

🧬 Molecular Profile ↔ Morphology – cross-modality generation

💎 Other Generation – tailored applications for pathology research

By reviewing 150+ representative studies, we trace the development of generation models — from GANs to diffusion models and vision–language models — and summarize available datasets, evaluation methods, and current challenges.

🎯 Goal: Provide researchers & practitioners with a reference roadmap for building more integrated, clinically applicable generation systems in computational pathology.

💡 The Landscape at a Glance Evolution of Generative Models (2017-2025) A timeline illustrating the major milestones and developmental trajectory of generative models in pathology.

📖 Structure & Taxonomy Overview

This repository provides a comprehensive and continuously updated list of over 150 papers discussed in our survey. The structure below follows the taxonomy proposed in our paper.

• 📚 Generative Pathology Paper List
  • 🖼️ Image Generation
    • Synthetic Image & Augmentation
    • Mask-Guided Generation
    • Artifact Restoration
    • High/Multi-Resolution Generation
    • Text-to-Image Generation
    • Stain Synthesis (Normalization & Transfer)
  • 📝 Text Generation
    • Image Captioning
    • Visual Question Answering (VQA)
    • Report Generation
    • Report Abstraction
  • 🧬 Molecular Profiles-Morphology Generation
    • Virtual Molecular Profiling
    • Reverse Morphology Generation
  • 🧭 Other Generations
    • Spatial Layout Generation
    • Semantic Output Generation
    • Latent Representation Generation
    • Cell Simulation

📚 Generative Pathology Paper List

🖼️ Image Generation

Models and methods focused on the synthesis and manipulation of histopathology images.

Synthetic Image & Augmentation

• Selective synthetic augmentation with HistoGAN for improved histopathology image classification, MIA, 2020 [Paper]
• PathologyGAN: Learning deep representations of cancer tissue, MIDL, 2020 [Paper]
• Self-supervised representation learning using visual field expansion on digital pathology, ICCV, 2021 [Paper] [Code]
• InsMix: Towards Realistic Generative Data Augmentation for Nuclei Instance Segmentation, MICCAI, 2022 [Paper] [Code]
• Multi-scale self-attention generative adversarial network for pathology image restoration, The Visual Computer, 2022 [Paper]
• Tackling stain variability using CycleGAN-based stain augmentation, Journal of Pathology Informatics, 2022 [Paper]
• ProGleason-GAN: Conditional progressive growing GAN for prostatic cancer Gleason grade patch synthesis, CMPB, 2023 [Paper] [Code]
• Diffusion-Based Data Augmentation for Nuclei Image Segmentation, MICCAI, 2023 [Paper] [Code]
• DiffMix: Diffusion Model-Based Data Synthesis for Nuclei Segmentation and Classification in Imbalanced Pathology Image Datasets, MICCAI, 2023 [Paper] [Code]
• Enhancing gland segmentation in colon histology images using an instance-aware diffusion model, CBM, 2023 [Paper]
• A Morphology Focused Diffusion Probabilistic Model for Synthesis of Histopathology Images, WACV, 2023 [Paper]
• Unified Framework for Histopathology Image Augmentation and Classification via Generative Models, DICTA, 2024 [Paper]
• ViT-DAE: Transformer-Driven Diffusion Autoencoder for Histopathology Image Analysis, MICCAI Workshop, 2024 [Paper]
• USegMix: Unsupervised Segment Mix for Efficient Data Augmentation in Pathology Images, DEMI, 2024 [Paper]
• Learned representation-guided diffusion models for large-image generation, CVPR, 2024 [Paper] [Code]
• Generating progressive images from pathological transitions via diffusion model, MICCAI, 2024 [Paper] [Code]
• Characterizing the Features of Mitotic Figures Using a Conditional Diffusion Probabilistic Model, MICCAI Workshop, 2024 [Paper] [Code]
• Optimising diffusion models for histopathology image synthesis, BMVC, 2024 [Paper]
• Counterfactual Diffusion Models for Mechanistic Explainability of Artificial Intelligence Models in Pathology, bioRxiv, 2024 [Paper] [Code]
• Diffusion models for out-of-distribution detection in digital pathology, MIA, 2024 [Paper]
• Deep Learning for Automated Detection of Breast Cancer in Deep Ultraviolet Fluorescence Images with Diffusion Probabilistic Model, ISBI, 2024 [Paper]
• Generative models improve fairness of medical classifiers under distribution shifts, Nature Medicine, 2024 [Paper]
• Generating and evaluating synthetic data in digital pathology through diffusion models, Scientific Reports, 2024 [Paper] [Code]
• Mitigating bias in prostate cancer diagnosis using synthetic data for improved AI driven Gleason grading, npj Precision Oncology, 2025 [Paper]
• Prototype-Guided Diffusion for Digital Pathology: Achieving Foundation Model Performance with Minimal Clinical Data, CVPR, 2025 [Paper]
• PDSeg: Patch-Wise Distillation and Controllable Image Generation for Weakly-Supervised Histopathology Tissue Segmentation, ICASSP, 2025 [Paper] [Code]

Mask-Guided Generation

• A multi-attribute controllable generative model for histopathology image synthesis, MICCAI, 2021 [Paper] [Code]
• Sharp-gan: Sharpness loss regularized gan for histopathology image synthesis, ISBI, 2022 [Paper]
• Realistic data enrichment for robust image segmentation in histopathology, MICCAI Workshop, 2023 [Paper]
• NASDM: Nuclei-Aware Semantic Histopathology Image Generation Using Diffusion Models, MICCAI, 2023 [Paper] [Code]
• DiffInfinite: Large Mask-Image Synthesis via Parallel Random Patch Diffusion in Histopathology, NeurIPS, 2023 [Paper] [Code]
• DISC: Latent Diffusion Models with Self-Distillation from Separated Conditions for Prostate Cancer Grading, ISBI, 2024 [Paper]
• Style-Extracting Diffusion Models for Semi-supervised Histopathology Segmentation, ECCV, 2024 [Paper] [Code]
• Co-synthesis of Histopathology Nuclei Image-Label Pairs using a Context-Conditioned Joint Diffusion Model, ECCV, 2024 [Paper] [Code]
• SynCLay: Interactive synthesis of histology images from bespoke cellular layouts, MIA, 2024 [Paper]
• HADiff: hierarchy aggregated diffusion model for pathology image segmentation, The Visual Computer, 2025 [Paper]
• Mask-guided cross-image attention for zero-shot in-silico histopathologic image generation with a diffusion model, arXiv, 2025 [Paper]
• PathoPainter: Augmenting Histopathology Segmentation via Tumor-aware Inpainting, MICCAI, 2025 [Paper] [Code]
• A robust image segmentation and synthesis pipeline for histopathology, MIA, 2025 [Paper] [Code]
• Pathdiff: Histopathology image synthesis with Text and Mask conditions that are not paired, ICCV, 2025[Paper][Code]

Artifact Restoration

• A review of artifacts in histopathology, J Oral Maxillofac Pathol., 2018 [Paper]
• Restoration of Marker Occluded Hematoxylin and Eosin Stained Whole Slide Histology Images Using Generative Adversarial Networks, ISBI, 2020 [Paper]
• Multi-scale self-attention generative adversarial network for pathology image restoration, The Visual Computer, 2022 [Paper]
• Artifact Detection and Restoration in Histology Images With Stain-Style and Structural Preservation, TMI, 2023 [Paper] [Code]
• Artifact Restoration in Histology Images with Diffusion Probabilistic Models, MICCAI, 2023 [Paper] [Code]
• Enhanced Pathology Image Quality with Restore–Generative Adversarial Network, The American Journal of Pathology, 2023 [Paper]
• A Federated Learning System for Histopathology Image Analysis With an Orchestral Stain-Normalization GAN, TMI, 2023 [Paper]
• Histology Image Artifact Restoration with Lightweight Transformer Based Diffusion Model, AIME, 2024 [Paper]
• LatentArtiFusion: An Effective and Efficient Histological Artifacts Restoration Framework, MICCAI Workshop, 2024 [Paper] [Code]
• HARP: Unsupervised histopathology artifact restoration, MIDL, 2024 [Paper] [Code]
• ArtiDiffuser: A unified framework for artifact restoration and synthesis for histology images via counterfactual diffusion model, MIA, 2025 [Paper] [Code]

High/Multi-Resolution Generation

• Synthesis of diagnostic quality cancer pathology images by generative adversarial networks, The Journal of Pathology, 2020 [Paper] [Code]
• Self-supervised representation learning using visual field expansion on digital pathology, ICCV, 2021 [Paper] [Code]
• Seamless Virtual Whole Slide Image Synthesis and Validation Using Perceptual Embedding Consistency, JBHI, 2021 [Paper]
• SAFRON: stitching across the frontier network for generating colorectal cancer histology images, MIA, 2022 [Paper] [Code]
• Diffusion-based generation of Histopathological Whole Slide Images at a Gigapixel scale, WACV, 2024 [Paper]
• URCDM: Ultra-Resolution Image Synthesis in Histopathology, MICCAI, 2024 [Paper] [Code]
• Histo-Diffusion: A Diffusion Super-Resolution Method for Digital Pathology with Comprehensive Quality Assessment, arXiv, 2024 [Paper]
• PathUp: Patch-wise Timestep Tracking for Multi-class Large Pathology Image Synthesising Diffusion Model, MM '24, 2024 [Paper]
• STAR-RL: Spatial-Temporal Hierarchical Reinforcement Learning for Interpretable Pathology Image Super-Resolution, TMI, 2024 [Paper] [Code]
• Comparative Analysis of Diffusion Generative Models in Computational Pathology, arXiv, 2024 [Paper]
• ToPoFM: Topology-Guided Pathology Foundation Model for High-Resolution Pathology Image Synthesis with Cellular-Level Control, TMI, 2025 [Paper]

Text-to-Image Generation

• PathLDM: Text conditioned Latent Diffusion Model for Histopathology, WACV, 2024 [Paper] [Code]
• VIMs: Virtual Immunohistochemistry Multiplex Staining via Text-to-Stain Diffusion Trained on Uniplex Stains, MLMI, 2024 [Paper]
• Pathdiff: Histopathology image synthesis with Text and Mask conditions that are not paired, ICCV, 2025[Paper][Code]

Stain Synthesis (Normalization & Transfer)

• Neural Stain-Style Transfer Learning using GAN for Histopathological Images, arXiv, 2017 [Paper] [Code]
• Stain normalization of histopathology images using generative adversarial networks, ISBI, 2018 [Paper]
• Normalization of HE-stained histological images using cycle consistent generative adversarial networks, Diagnostic Pathology, 2021 [Paper]
• Residual cyclegan for robust domain transformation of histopathological tissue slides, MIA, 2021 [Paper] [Code]
• Unpaired Stain Transfer Using Pathology-Consistent Constrained Generative Adversarial Networks, TMI, 2021 [Paper] [Code]
• Seamless Virtual Whole Slide Image Synthesis and Validation Using Perceptual Embedding Consistency, JBHI, 2021 [Paper]
• Colour adaptive generative networks for stain normalisation of histopathology images, MIA, 2022 [Paper] [Code]
• A Federated Learning System for Histopathology Image Analysis With an Orchestral Stain-Normalization GAN, TMI, 2023 [Paper]
• Stain normalization using score-based diffusion model through stain separation and overlapped moving window patch strategies, CBM, 2023 [Paper]
• StainDiff: Transfer Stain Styles of Histology Images with Denoising Diffusion Probabilistic Models and Self-ensemble, MICCAI, 2023 [Paper]
• Generative adversarial networks for stain normalisation in histopathology, Applications of Generative AI, 2024 [Paper]
• StainFuser: Controlling Diffusion for Faster Neural Style Transfer in Multi-Gigapixel Histology Images, arXiv, 2024 [Paper] [Code]
• Test-Time Stain Adaptation with Diffusion Models for Histopathology Image Classification, ECCV, 2024 [Paper] [Code]
• Unsupervised Latent Stain Adaptation for Computational Pathology, MICCAI, 2024 [Paper]
• Accelerating histopathology workflows with generative AI-based virtually multiplexed tumour profiling, Nature Machine Intelligence, 2024 [Paper] [Code]
• Virtual multi-staining in a single-section view for renal pathology using generative adversarial networks, CBM, 2024 [Paper]
• AV-GAN: Attention-Based Varifocal Generative Adversarial Network for Uneven Medical Image Translation, IJCNN, 2024 [Paper]
• Diffusion Models for Generative Histopathology, MICCAI Workshop, 2024 [Paper]
• PST-Diff: Achieving High-Consistency Stain Transfer by Diffusion Models With Pathological and Structural Constraints, TMI, 2024 [Paper]
• StainDiffuser: MultiTask Dual Diffusion Model for Virtual Staining, arXiv, 2024 [Paper]
• Multi-modal Denoising Diffusion Pre-training for Whole-Slide Image Classification, MM '24, 2024 [Paper] [Code]
• Deeply supervised two stage generative adversarial network for stain normalization, Scientific Reports, 2025 [Paper]
• ODA-GAN: Orthogonal Decoupling Alignment GAN Assisted by Weakly-supervised Learning for Virtual Immunohistochemistry Staining, CVPR, 2025 [Paper] [Code]
• A Value Mapping Virtual Staining Framework for Large-scale Histological Imaging, arXiv, 2025 [Paper]
• Diffusion-based Virtual Staining from Polarimetric Mueller Matrix Imaging, MICCAI, 2025 [Paper]
• F2FLDM: Latent Diffusion Models with Histopathology Pre-Trained Embeddings for Unpaired Frozen Section to FFPE Translation, WACV, 2025 [Paper] [Code]
• Unpaired Multi-Domain Histopathology Virtual Staining Using Dual Path Prompted Inversion, AAAI, 2025 [Paper] [Code]
• Versatile Stain Transfer in Histopathology Using a Unified Diffusion Framework, ISBI, 2025 [Paper]

---

📝 Text Generation

This category covers models that generate text from pathology images, such as captions or reports.

Image Captioning

• Multiple Instance Captioning: Learning Representations from Histopathology Textbooks and Articles, CVPR, 2021 [Paper] [Code]
• Inference of captions from histopathological patches, MIDL, 2022 [Paper] [Code]
• Enhanced descriptive captioning model for histopathological patches, Multimedia Tools and Applications, 2023 [Paper]
• What a Whole Slide Image Can Tell? Subtype-guided Masked Transformer for Pathological Image Captioning, arXiv, 2023 [Paper]
• PathM3: A Multimodal Multi-task Multiple Instance Learning Framework for Whole Slide Image Classification and Captioning, MICCAI, 2024 [Paper]
• HistGen: Histopathology Report Generation via Local-Global Feature Encoding and Cross-Modal Context Interaction, MICCAI, 2024 [Paper] [Code]
• In-context learning enables multimodal large language models to classify cancer pathology images, Nature Communications, 2024 [Paper]

Visual Question Answering (VQA)

• PathVQA: 30000+ Questions for Medical Visual Question Answering, arXiv preprint, 2020 [Paper] [Code]
• Vision-Language Transformer for Interpretable Pathology Visual Question Answering, JBHI, 2023 [Paper]
• WSI-VQA: Interpreting Whole Slide Images by Generative Visual Question Answering, ECCV, 2024 [Paper] [Code]
• A multimodal generative AI copilot for human pathology, Nature, 2024 [Paper]
• Quilt-LLaVA: Visual Instruction Tuning by Extracting Localized Narratives from Open-Source Histopathology Videos, CVPR, 2024 [Paper] [Code]
• A vision–language foundation model for precision oncology, Nature, 2025 [Paper]
• PathGen-1.6M: 1.6 Million Pathology Image-text Pairs Generation through Multi-agent Collaboration, ICLR, 2025 [Paper] [Code]
• Pathologyvlm: a large vision-language model for pathology image understanding, Artificial Intelligence Review, 2025 [Paper]
• SlideChat: A Large Vision-Language Assistant for Whole-Slide Pathology Image Understanding, CVPR, 2025 [Paper] [Code]
• PathCoT: Chain-of-Thought Prompting for Zero-shot Pathology Visual Reasoning, arxiv, 2025 [Paper]
• Cost-effective instruction learning for pathology vision and language analysis, Nature Computational Science, 2025 [Paper] [Code]
• Efficient Whole Slide Pathology VQA via Token Compression, arxiv, 2025 [Paper]

Report Generation

• PRISM: A Multi-Modal Generative Foundation Model for Slide-Level Histopathology, arXiv, 2024 [Paper] [Code]
• Automatic Report Generation for Histopathology images using pre-trained Vision Transformers and BERT, ISBI, 2024 [Paper]
• Generating dermatopathology reports from gigapixel whole slide images with HistoGPT, Nature Communications, 2024 [Paper] [Code]
• A Multimodal Knowledge-enhanced Whole-slide Pathology Foundation Model, arXiv, 2024 [Paper] [Code]
• WsiCaption: Multiple Instance Generation of Pathology Reports for Gigapixel Whole-Slide Images, MICCAI, 2024 [Paper] [Code]
• PathAlign: A vision-language model for whole slide images in histopathology, MICCAI, 2024 [Paper]
• PathInsight: Instruction Tuning of Multimodal Datasets and Models for Intelligence Assisted Diagnosis in Histopathology, arXiv, 2024 [Paper]
• Pathology report generation from whole slide images with knowledge retrieval and multi-level regional feature selection, CMPB, 2025 [Paper]
• Pathfinder: A multi-modal multi-agent system for medical diagnostic decision-making applied to histopathology, arXiv, 2025 [Paper]
• Pathology Report Generation and Multimodal Representation Learning for Cutaneous Melanocytic Lesions, arXiv, 2025 [Paper]
• PolyPath: Adapting a Large Multimodal Model for Multi-slide Pathology Report Generation, arXiv, 2025 [Paper]

Report Abstraction

• Using Generative AI to Extract Structured Information from Free Text Pathology Reports, Journal of Medical Systems, 2025 [Paper]
• Leveraging large language models for structured information extraction from pathology reports, arXiv, 2025 [Paper]
• Cancer Type, Stage and Prognosis Assessment from Pathology Reports using LLMs, Scientific Reports, 2025 [Paper] [Code]
• Enhancing doctor-patient communication using large language models for pathology report interpretation, BMC Medical Informatics and Decision Making, 2025 [Paper]

---

🧬 Molecular Profiles-Morphology Generation

Models that bridge the gap between histology (phenotype) and genomics (genotype).

Virtual Molecular Profiling

• Integrating spatial and single-cell transcriptomics data using deep generative models with SpatialScope, Nature Communications, 2023 [Paper] [Code]

• Cross-modal diffusion modelling for super-resolved spatial transcriptomics, MICCAI, 2024 [Paper]

• PAST: A multimodal single-cell foundation model for histopathology and spatial transcriptomics in cancer, arxiv, 2025 [Paper]

• Inference of single cell profiles from histology stains with the Single-Cell omics from Histology Analysis Framework (SCHAF), bioRxiv, 2025 [Paper]

• GenST: A Generative Cross-Modal Model for Predicting Spatial Transcriptomics from Histology Images, MICCAI workshop, 2025 [Paper]

• Diffusion Generative Modeling for Spatially Resolved Gene Expression Inference from Histology Images, ICLR, 2025 [Paper] [Code]

• Histopathology-based protein multiplex generation using deep learning, Nature Machine Intelligence, 2025 [Paper] [Code]

• Robust Multimodal Survival Prediction with Conditional Latent Differentiation Variational AutoEncoder, CVPR, 2025 [Paper] [Code]

• TCGA virtual spatial transcriptomics atlas: multimodal virtual ST (H&E + expression + coords + genes) from DeepSpot-M; 28,664 slides / 32 cancers / 295.3M spots, medRxiv, 2026 [Paper] [Dataset] [Code]

• HEST Xenium virtual spatial transcriptomics: multimodal virtual single-cell ST (H&E + expression + coords + genes) from DeepSpot-M; 59 HEST-1k Xenium samples / ~13.3M cells / 22 tissue types, medRxiv, 2026 [Paper] [Dataset] [Code]

• DeepSpot: Leveraging Spatial Context for Enhanced Spatial Transcriptomics Prediction from H&E Images, medRxiv, 2025 [Paper] [Code]

• DeepSpot2Cell: Predicting Virtual Single-Cell Spatial Transcriptomics from H&E images using Spot-Level Supervision, NeurIPS, 2025 [Paper] [Code]

• DeepSpot-M: a multimodal foundation model for transcriptome-wide virtual spatial transcriptomics from histology, medRxiv, 2026 [Paper] [Code]

Reverse Morphology Generation

• Pix2Path: Integrating Spatial Transcriptomics and Digital Pathology with Deep Learning to Score Pathological Risk and Link Gene Expression to Disease Mechanisms, bioRxiv, 2024 [Paper] [Code]
• Generation of synthetic whole-slide image tiles of tumours from RNA-sequencing data via cascaded diffusion models, Nature Biomedical Engineering, 2024 [Paper]
• Generative adversarial networks accurately reconstruct pan-cancer histology from pathologic, genomic, and radiographic latent features, Science Advances, 2024 [Paper] [Code]
• PAST: A multimodal single-cell foundation model for histopathology and spatial transcriptomics in cancer, arxiv, 2025 [Paper]
• SPATIA: Multimodal Model for Prediction and Generation of Spatial Cell Phenotypes, arxiv, 2025 [Paper]

---

💎 Other Generations

Emerging and specialized generative tasks beyond traditional image and text synthesis.

Spatial Layout Generation

• Spatial Diffusion for Cell Layout Generation, MICCAI, 2024 [Paper] [Code]
• Tertiary Lymphoid Structures Generation Through Graph-Based Diffusion, MICCAI, 2024 [Paper]
• TopoCellGen: Generating Histopathology Cell Topology with a Diffusion Model, CVPR, 2025 [Paper] [Code]
• DAMM-Diffusion: Learning Divergence-Aware Multi-Modal Diffusion Model for Nanoparticles Distribution Prediction, CVPR, 2025 [Paper] [Code]

Semantic Output Generation

• A visual–language foundation model for pathology image analysis using medical Twitter, Nature Medicine, 2023 [Paper] [Code]
• Prompting vision foundation models for pathology image analysis, CVPR, 2024 [Paper] [Code]
• Towards a Text-Based Quantitative and Explainable Histopathology Image Analysis, MICCAI, 2024 [Paper]
• MLLM4PUE: Toward Universal Embeddings in Digital Pathology through Multimodal LLMs, arXiv, 2025 [Paper]

Latent Representation Generation

• AugDiff: Diffusion-Based Feature Augmentation for Multiple Instance Learning in Whole Slide Image, TAI, 2024 [Paper] [Code]
• A whole-slide foundation model for digital pathology from real-world data, Nature, 2024 [Paper] [Code]
• DCDiff: Dual-Granularity Cooperative Diffusion Models for Pathology Image Analysis, TMI, 2024 [Paper]
• Towards A Generalizable Pathology Foundation Model via Unified Knowledge Distillation, arxiv, 2024 [Paper] [Code]
• Promptable Representation Distribution Learning and Data Augmentation for Gigapixel Histopathology WSI Analysis, AAAI, 2025 [Paper] [Code]
• MGPATH: Vision-Language Model with Multi-Granular Prompt Learning for Few-Shot WSI Classification, arxiv, 2025 [Paper] [Code]

Cell Simulation

• SynCellFactory: Generative Data Augmentation for Cell Tracking, MICCAI, 2024 [Paper] [Code]
• Improving 3D deep learning segmentation with biophysically motivated cell synthesis, Communications Biology, 2025 [Paper] [Code]

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