mlsanityData to 7 Oct 2026

Towards Generalizable Tumor Synthesis

arXiv 2402.19470 ↗First posted 29 Feb 2024eess.IV cs.CVcited by 65

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Abstract (arXiv)

Tumor synthesis enables the creation of artificial tumors in medical images, facilitating the training of AI models for tumor detection and segmentation. However, success in tumor synthesis hinges on creating visually realistic tumors that are generalizable across multiple organs and, furthermore, the resulting AI models being capable of detecting real tumors in images sourced from different domains (e.g., hospitals). This paper made a progressive stride toward generalizable tumor synthesis by leveraging a critical observation: early-stage tumors (< 2cm) tend to have similar imaging characteristics in computed tomography (CT), whether they originate in the liver, pancreas, or kidneys. We have ascertained that generative AI models, e.g., Diffusion Models, can create realistic tumors generalized to a range of organs even when trained on a limited number of tumor examples from only one organ. Moreover, we have shown that AI models trained on these synthetic tumors can be generalized to detect and segment real tumors from CT volumes, encompassing a broad spectrum of patient demographics, imaging protocols, and healthcare facilities.

Key facts. Cited by 65 papers in the map (data through 7 Oct 2026). Builds on 52 of its 101 references that are in the map. First posted on arXiv 29 Feb 2024.

Builds on

52 of 101 references.

References · 52

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  3. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  4. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
  5. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
  6. 2022Generative Adversarial Networkscited by 5,603
  7. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,736
  8. 2020Taming Transformers for High-Resolution Image Synthesiscited by 3,229
  9. 2021ViViT: A Video Vision Transformercited by 1,610
  10. 2021Is Space-Time Attention All You Need for Video Understanding?cited by 1,609
  11. 2019Normalizing Flows for Probabilistic Modeling and Inferencecited by 1,315
  12. 2021Palette: Image-to-Image Diffusion Modelscited by 1,296
38 more
  1. 2019An Introduction to Variational Autoencoderscited by 997
  2. 2022Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Imagescited by 823
  3. 2021Score-based Generative Modeling in Latent Spacecited by 634
  4. 2021The Medical Segmentation Decathloncited by 620
  5. 2017Generative Adversarial Networks: An Overviewcited by 588
  6. 2021Solving Inverse Problems in Medical Imaging with Score-Based Generative Modelscited by 514
  7. 2019The Liver Tumor Segmentation Benchmark (LiTS)cited by 504
  8. 2014Semi-Supervised Learning with Deep Generative Modelscited by 494
  9. 2021SynthSeg: Segmentation of brain MRI scans of any contrast and resolution without retrainingcited by 235
  10. 2021FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing Flowscited by 225
  11. 2023CLIP-Driven Universal Model for Organ Segmentation and Tumor Detectioncited by 224
  12. 2021Diffusion Models for Implicit Image Segmentation Ensemblescited by 198
  13. 2022Unsupervised Medical Image Translation with Adversarial Diffusion Modelscited by 191
  14. 2016Energy-based Generative Adversarial Networkcited by 119
  15. 2022Conversion Between CT and MRI Images Using Diffusion and Score-Matching Modelscited by 69
  16. 2022Measurement-conditioned Denoising Diffusion Probabilistic Model for Under-sampled Medical Image Reconstructioncited by 64
  17. 2022PET image denoising based on denoising diffusion probabilistic modelscited by 57
  18. 2023Label-Free Liver Tumor Segmentationcited by 56
  19. 2022Diffusion Adversarial Representation Learning for Self-supervised Vessel Segmentationcited by 55
  20. 2023AbdomenAtlas-8K: Annotating 8,000 CT Volumes for Multi-Organ Segmentation in Three Weekscited by 52
  21. 2023Continual Learning for Abdominal Multi-Organ and Tumor Segmentationcited by 43
  22. 2019Learning Fixed Points in Generative Adversarial Networks: From Image-to-Image Translation to Disease Detection and Localizationcited by 38
  23. 2020Deflating Dataset Bias Using Synthetic Data Augmentationcited by 37
  24. 2020Label-Free Segmentation of COVID-19 Lesions in Lung CTcited by 37
  25. 2022Can segmentation models be trained with fully synthetically generated data?cited by 37
  26. 2021SQUID: Deep Feature In-Painting for Unsupervised Anomaly Detectioncited by 34
  27. 2019Synthesizing Diverse Lung Nodules Wherever Massively: 3D Multi-Conditional GAN-based CT Image Augmentation for Object Detectioncited by 29
  28. 2022A Novel Unified Conditional Score-based Generative Framework for Multi-modal Medical Image Completioncited by 23
  29. 2021Label-Assemble: Leveraging Multiple Datasets with Partial Labelscited by 20
  30. 2019Multi-Domain Adaptation in Brain MRI through Paired Consistency and Adversarial Learningcited by 18
  31. 2023Early Detection and Localization of Pancreatic Cancer by Label-Free Tumor Synthesiscited by 17
  32. 2023Boosting Dermatoscopic Lesion Segmentation via Diffusion Models with Visual and Textual Promptscited by 17
  33. 2021Free-form tumor synthesis in computed tomography images via richer generative adversarial networkcited by 16
  34. 2023CancerUniT: Towards a Single Unified Model for Effective Detection, Segmentation, and Diagnosis of Eight Major Cancers Using a Large Collection of CT Scanscited by 15
  35. 2022Synthetic Tumors Make AI Segment Tumors Bettercited by 14
  36. 2021METGAN: Generative Tumour Inpainting and Modality Synthesis in Light Sheet Microscopycited by 9
  37. 2023Acquiring Weak Annotations for Tumor Localization in Temporal and Volumetric Datacited by 9
  38. 2023Synthetic Data as Validationcited by 9

50 most cited of 52 All 52 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 22; 2025: 30; 2026: 13.

65 papers.

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  1. 2024MAISI: Medical AI for Synthetic Imagingcited by 86
  2. 2024AbdomenAtlas: A Large-Scale, Detailed-Annotated, & Multi-Center Dataset for Efficient Transfer Learning and Open Algorithmic Benchmarkingcited by 64
  3. 2024Large-Scale 3D Medical Image Pre-training with Geometric Context Priorscited by 34
  4. 2025RadGPT: Constructing 3D Image-Text Tumor Datasetscited by 34
  5. 2024Universal and Extensible Language-Vision Models for Organ Segmentation and Tumor Detection from Abdominal Computed Tomographycited by 31
  6. 2024Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?cited by 31
  7. 2025Medical World Model: Generative Simulation of Tumor Evolution for Treatment Planningcited by 31
  8. 2025Noise-Consistent Siamese-Diffusion for Medical Image Synthesis and Segmentationcited by 21
  9. 2024From Pixel to Cancer: Cellular Automata in Computed Tomographycited by 20
  10. 2024Automatic Organ and Pan-cancer Segmentation in Abdomen CT: the FLARE 2023 Challengecited by 20
  11. 2024LeFusion: Controllable Pathology Synthesis via Lesion-Focused Diffusion Modelscited by 15
  12. 2024Mask Factory: Towards High-quality Synthetic Data Generation for Dichotomous Image Segmentationcited by 15
38 more
  1. 2024Generative Enhancement for 3D Medical Imagescited by 14
  2. 2024FreeTumor: Advance Tumor Segmentation via Large-Scale Tumor Synthesiscited by 14
  3. 2024Frontiers in Intelligent Colonoscopycited by 13
  4. 2025MedSegFactory: Text-Guided Generation of Medical Image-Mask Pairscited by 13
  5. 2025Scaling Tumor Segmentation: Best Lessons from Real and Synthetic Datacited by 13
  6. 2024Analyzing Tumors by Synthesiscited by 11
  7. 2024Embracing Massive Medical Datacited by 9
  8. 2025Polyp-Gen: Realistic and Diverse Polyp Image Generation for Endoscopic Dataset Expansioncited by 9
  9. 2025Speckle2Self: Self-Supervised Ultrasound Speckle Reduction Without Clean Datacited by 9
  10. 2025MedSG-Bench: A Benchmark for Medical Image Sequences Groundingcited by 8
  11. 2025Learning Patient-Specific Disease Dynamics with Latent Flow Matching for Longitudinal Imaging Generationcited by 8
  12. 2024MedDiff-FM: A Diffusion-based Foundation Model for Versatile Medical Image Applicationscited by 7
  13. 2025Are Pixel-Wise Metrics Reliable for Sparse-View Computed Tomography Reconstruction?cited by 6
  14. 2024Ctrl-GenAug: Controllable Generative Augmentation for Medical Sequence Classificationcited by 4
  15. 2025LesionDiffusion: Towards Text-controlled General Lesion Synthesiscited by 4
  16. 2025Latent Diffusion Autoencoders: Toward Efficient and Meaningful Unsupervised Representation Learning in Medical Imagingcited by 4
  17. 2025Lung-DDPM+: Efficient Thoracic CT Image Synthesis using Diffusion Probabilistic Modelcited by 4
  18. 2026Early and Prediagnostic Detection of Pancreatic Cancer from Computed Tomographycited by 4
  19. 2026RadThinking: A Dataset for Longitudinal Clinical Reasoning in Radiologycited by 4
  20. 2024Optimizing Synthetic Data for Enhanced Pancreatic Tumor Segmentationcited by 3
  21. 2024MRGen: Segmentation Data Engine for Underrepresented MRI Modalitiescited by 3
  22. 2025PathoPainter: Augmenting Histopathology Segmentation via Tumor-aware Inpaintingcited by 3
  23. 2025See More, Change Less: Anatomy-Aware Diffusion for Contrast Enhancementcited by 3
  24. 2026The autoPET3 Challenge: Automated Lesion Segmentation in Whole-Body PET/CT unicodex2013 Multitracer Multicenter Generalizationcited by 3
  25. 2024AutoPET Challenge: Tumour Synthesis for Data Augmentationcited by 2
  26. 2025High Volume Rate 3D Ultrasound Reconstruction with Diffusion Modelscited by 2
  27. 2025CLAIM: Clinically-Guided LGE Augmentation for Realistic and Diverse Myocardial Scar Synthesis and Segmentationcited by 2
  28. 2025RainDiff: End-to-end Precipitation Nowcasting Via Token-wise Attention Diffusioncited by 2
  29. 2024Diff4MMLiTS: Advanced Multimodal Liver Tumor Segmentation via Diffusion-Based Image Synthesis and Alignmentcited by 1
  30. 2025Layer Separation: Adjustable Joint Space Width Images Synthesis in Conventional Radiographycited by 1
  31. 2025Interactive Tumor Progression Modeling via Sketch-Based Image Editingcited by 1
  32. 2025MExD: An Expert-Infused Diffusion Model for Whole-Slide Image Classificationcited by 1
  33. 2025Advancing Generalizable Tumor Segmentation with Anomaly-Aware Open-Vocabulary Attention Maps and Frozen Foundation Diffusion Modelscited by 1
  34. 2025ViCTr: Vital Consistency Transfer for Pathology Aware Image Synthesiscited by 1
  35. 2025SynBT: High-quality Tumor Synthesis for Breast Tumor Segmentation by 3D Diffusion Modelcited by 1
  36. 2026Glance and Focus Reinforcement for Pan-cancer Screeningcited by 1
  37. 2026Foundation VAEs for 3D CT Reconstruction, Augmentation, and Generationcited by 1
  38. 2026Knowledge-Guided 3D CT Generation: A Conditioning-Centric Taxonomycited by 1

50 most cited of 65 All 65 (JSON)

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  2. 2023Generative AI for Medical Imaging: extending the MONAI Framework
  3. 2023Latent Diffusion Models with Image-Derived Annotations for Enhanced AI-Assisted Cancer Diagnosis in Histopathology
  4. 2025A Biophysically-Conditioned Generative Framework for 3D Brain Tumor MRI Synthesis
  5. 2024Multi-Conditioned Denoising Diffusion Probabilistic Model (mDDPM) for Medical Image Synthesis
  6. 2022Medical Diffusion: Denoising Diffusion Probabilistic Models for 3D Medical Image Generation
  7. 2023Brain tumor segmentation using synthetic MR images -- A comparison of GANs and diffusion models
  8. 2025Generative Artificial Intelligence in Medical Imaging: Foundations, Progress, and Clinical Translation