mlsanityData to 7 Oct 2026

Label-Free Liver Tumor Segmentation

arXiv 2303.14869 ↗First posted 27 Mar 2023eess.IV cs.CV cs.LGcited by 56

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Abstract (arXiv)

We demonstrate that AI models can accurately segment liver tumors without the need for manual annotation by using synthetic tumors in CT scans. Our synthetic tumors have two intriguing advantages: (I) realistic in shape and texture, which even medical professionals can confuse with real tumors; (II) effective for training AI models, which can perform liver tumor segmentation similarly to the model trained on real tumors -- this result is exciting because no existing work, using synthetic tumors only, has thus far reached a similar or even close performance to real tumors. This result also implies that manual efforts for annotating tumors voxel by voxel (which took years to create) can be significantly reduced in the future. Moreover, our synthetic tumors can automatically generate many examples of small (or even tiny) synthetic tumors and have the potential to improve the success rate of detecting small liver tumors, which is critical for detecting the early stages of cancer. In addition to enriching the training data, our synthesizing strategy also enables us to rigorously assess the AI robustness.

Key facts. Cited by 56 papers in the map (data through 7 Oct 2026). Builds on 40 of its 77 references that are in the map. First posted on arXiv 27 Mar 2023.

Builds on

40 of 77 references.

References · 40

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28 more
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  5. 2021The Medical Segmentation Decathloncited by 620
  6. 2019UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentationcited by 583
  7. 2019The Liver Tumor Segmentation Benchmark (LiTS)cited by 504
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  20. 2020Label-Free Segmentation of COVID-19 Lesions in Lung CTcited by 37
  21. 2020Automated Synthetic-to-Real Generalizationcited by 35
  22. 2021Contrastive Syn-to-Real Generalizationcited by 32
  23. 2019Synthesizing Diverse Lung Nodules Wherever Massively: 3D Multi-Conditional GAN-based CT Image Augmentation for Object Detectioncited by 29
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 9; 2024: 24; 2025: 17; 2026: 6.

56 papers.

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  1. 2024Towards Generalizable Tumor Synthesiscited by 65
  2. 2024AbdomenAtlas: A Large-Scale, Detailed-Annotated, & Multi-Center Dataset for Efficient Transfer Learning and Open Algorithmic Benchmarkingcited by 64
  3. 2023AbdomenAtlas-8K: Annotating 8,000 CT Volumes for Multi-Organ Segmentation in Three Weekscited by 52
  4. 2023MedShapeNet -- A Large-Scale Dataset of 3D Medical Shapes for Computer Visioncited by 31
  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. 2023X-IQE: eXplainable Image Quality Evaluation for Text-to-Image Generation with Visual Large Language Modelscited by 28
  9. 2024AutoRG-Brain: Grounded Report Generation for Brain MRIcited by 23
  10. 2024From Pixel to Cancer: Cellular Automata in Computed Tomographycited by 20
  11. 2024Automatic Organ and Pan-cancer Segmentation in Abdomen CT: the FLARE 2023 Challengecited by 20
  12. 2023Towards Unifying Anatomy Segmentation: Automated Generation of a Full-body CT Dataset via Knowledge Aggregation and Anatomical Guidelinescited by 17
38 more
  1. 2023Early Detection and Localization of Pancreatic Cancer by Label-Free Tumor Synthesiscited by 17
  2. 2023Boosting Dermatoscopic Lesion Segmentation via Diffusion Models with Visual and Textual Promptscited by 17
  3. 2024LeFusion: Controllable Pathology Synthesis via Lesion-Focused Diffusion Modelscited by 15
  4. 2024Generative Enhancement for 3D Medical Imagescited by 14
  5. 2024FreeTumor: Advance Tumor Segmentation via Large-Scale Tumor Synthesiscited by 14
  6. 2024Exploiting Structural Consistency of Chest Anatomy for Unsupervised Anomaly Detection in Radiography Imagescited by 13
  7. 2025Scaling Tumor Segmentation: Best Lessons from Real and Synthetic Datacited by 13
  8. 2024Analyzing Tumors by Synthesiscited by 11
  9. 2024PairAug: What Can Augmented Image-Text Pairs Do for Radiology?cited by 10
  10. 2023FoPro-KD: Fourier Prompted Effective Knowledge Distillation for Long-Tailed Medical Image Recognitioncited by 9
  11. 2024Embracing Massive Medical Datacited by 9
  12. 2023EviPrompt: A Training-Free Evidential Prompt Generation Method for Segment Anything Model in Medical Imagescited by 8
  13. 2025MedSG-Bench: A Benchmark for Medical Image Sequences Groundingcited by 8
  14. 2025Towards Accurate Unified Anomaly Segmentationcited by 7
  15. 2024Test-time generative augmentation for medical image segmentationcited by 6
  16. 2024LIDIA: Precise Liver Tumor Diagnosis on Multi-Phase Contrast-Enhanced CT via Iterative Fusion and Asymmetric Contrastive Learningcited by 5
  17. 2025Expectation-Maximization as the Engine of Scalable Medical Intelligencecited by 5
  18. 2025LesionDiffusion: Towards Text-controlled General Lesion Synthesiscited by 4
  19. 2025Lung-DDPM+: Efficient Thoracic CT Image Synthesis using Diffusion Probabilistic Modelcited by 4
  20. 2023Adversarial Medical Image with Hierarchical Feature Hidingcited by 3
  21. 2024Contour-weighted loss for class-imbalanced image segmentationcited by 3
  22. 2024Optimizing Synthetic Data for Enhanced Pancreatic Tumor Segmentationcited by 3
  23. 2025See More, Change Less: Anatomy-Aware Diffusion for Contrast Enhancementcited by 3
  24. 2024Two-stage Cytopathological Image Synthesis for Augmenting Cervical Abnormality Screeningcited by 2
  25. 2024Knowledge-driven AI-generated data for accurate and interpretable breast ultrasound diagnosescited by 2
  26. 2024SoK: Security and Privacy Risks of Healthcare AIcited by 2
  27. 2024Meta-Transfer Derm-Diagnosis: Exploring Few-Shot Learning and Transfer Learning for Skin Disease Classification in Long-Tail Distributioncited by 1
  28. 2024Diff4MMLiTS: Advanced Multimodal Liver Tumor Segmentation via Diffusion-Based Image Synthesis and Alignmentcited by 1
  29. 2025Non-Destructive Detection of Sub-Micron Imperceptible Scratches On Laser Chips Based On Consistent Texture Entropy Recursive Optimization Semi-Supervised Networkcited by 1
  30. 2025Advancing Generalizable Tumor Segmentation with Anomaly-Aware Open-Vocabulary Attention Maps and Frozen Foundation Diffusion Modelscited by 1
  31. 2025SynBT: High-quality Tumor Synthesis for Breast Tumor Segmentation by 3D Diffusion Modelcited by 1
  32. 2025LiMT: A Multi-task Liver Image Benchmark Datasetcited by 1
  33. 2026Foundation VAEs for 3D CT Reconstruction, Augmentation, and Generationcited by 1
  34. 2024LN-Gen: Rectal Lymph Nodes Generation via Anatomical Featurescited by 0
  35. 2025CAFusion: Controllable Anatomical Synthesis of Perirectal Lymph Nodes via SDF-guided Diffusioncited by 0
  36. 2025TumorGen: Boundary-Aware Tumor-Mask Synthesis with Rectified Flow Matchingcited by 0
  37. 2025ShapeKitcited by 0
  38. 2025AURAD: Anatomy-Pathology Unified Radiology Synthesis with Progressive Representationscited by 0

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