mlsanityData to 7 Oct 2026

SA-Med2D-20M Dataset: Segment Anything in 2D Medical Imaging with 20 Million masks

arXiv 2311.11969 ↗First posted 20 Nov 2023eess.IV cs.CVcited by 54

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Abstract (arXiv)

Segment Anything Model (SAM) has achieved impressive results for natural image segmentation with input prompts such as points and bounding boxes. Its success largely owes to massive labeled training data. However, directly applying SAM to medical image segmentation cannot perform well because SAM lacks medical knowledge -- it does not use medical images for training. To incorporate medical knowledge into SAM, we introduce SA-Med2D-20M, a large-scale segmentation dataset of 2D medical images built upon numerous public and private datasets. It consists of 4.6 million 2D medical images and 19.7 million corresponding masks, covering almost the whole body and showing significant diversity. This paper describes all the datasets collected in SA-Med2D-20M and details how to process these datasets. Furthermore, comprehensive statistics of SA-Med2D-20M are presented to facilitate the better use of our dataset, which can help the researchers build medical vision foundation models or apply their models to downstream medical applications. We hope that the large scale and diversity of SA-Med2D-20M can be leveraged to develop medical artificial intelligence for enhancing diagnosis, medical image analysis, knowledge sharing, and education. The data with the redistribution license is publicly available at https://github.com/OpenGVLab/SAM-Med2D.

Key facts. Cited by 54 papers in the map (data through 7 Oct 2026). Builds on 68 of its 143 references that are in the map. First posted on arXiv 20 Nov 2023.

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68 of 143 references.

References · 68

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  4. 2023Segment Anythingcited by 8,158
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  12. 2019Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)cited by 657
38 more
  1. 2021The Medical Segmentation Decathloncited by 620
  2. 2022TotalSegmentator: robust segmentation of 104 anatomical structures in CT imagescited by 597
  3. 2019Kvasir-SEG: A Segmented Polyp Datasetcited by 588
  4. 2017Skin Lesion Analysis Toward Melanoma Detection: A Challenge at the 2017 International Symposium on Biomedical Imaging (ISBI), Hosted by the International Skin Imaging Collaboration (ISIC)cited by 549
  5. 2023Segment Everything Everywhere All at Oncecited by 546
  6. 2018Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challengecited by 508
  7. 2021The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classificationcited by 507
  8. 2023Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentationcited by 485
  9. 2019A large annotated medical image dataset for the development and evaluation of segmentation algorithmscited by 371
  10. 2022AMOS: A Large-Scale Abdominal Multi-Organ Benchmark for Versatile Medical Image Segmentationcited by 347
  11. 2020CHAOS Challenge -- Combined (CT-MR) Healthy Abdominal Organ Segmentationcited by 307
  12. 2023Customized Segment Anything Model for Medical Image Segmentationcited by 277
  13. 2019REFUGE Challenge: A Unified Framework for Evaluating Automated Methods for Glaucoma Assessment from Fundus Photographscited by 226
  14. 2020AbdomenCT-1K: Is Abdominal Organ Segmentation A Solved Problem?cited by 222
  15. 2016Gland Segmentation in Colon Histology Images: The GlaS Challenge Contestcited by 203
  16. 2016Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: the LUNA16 challengecited by 198
  17. 2023SegGPT: Segmenting Everything In Contextcited by 193
  18. 2019The KiTS19 Challenge Data: 300 Kidney Tumor Cases with Clinical Context, CT Semantic Segmentations, and Surgical Outcomescited by 168
  19. 2016Multivariate mixture model for myocardium segmentation combining multi-source imagescited by 133
  20. 2016The Importance of Skip Connections in Biomedical Image Segmentationcited by 126
  21. 2020Shape-aware Meta-learning for Generalizing Prostate MRI Segmentation to Unseen Domainscited by 124
  22. 2020MS-Net: Multi-Site Network for Improving Prostate Segmentation with Heterogeneous MRI Datacited by 121
  23. 2019Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challengecited by 115
  24. 2020VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Imagescited by 111
  25. 2022ISLES 2022: A multi-center magnetic resonance imaging stroke lesion segmentation datasetcited by 104
  26. 2020COVID-19 Image Data Collectioncited by 100
  27. 2020COVID-19 Image Data Collection: Prospective Predictions Are the Futurecited by 100
  28. 2023Can SAM Segment Anything? When SAM Meets Camouflaged Object Detectioncited by 99
  29. 2023STU-Net: Scalable and Transferable Medical Image Segmentation Models Empowered by Large-Scale Supervised Pre-trainingcited by 96
  30. 2023MA-SAM: Modality-agnostic SAM Adaptation for 3D Medical Image Segmentationcited by 82
  31. 2023SAM Struggles in Concealed Scenes -- Empirical Study on Segment Anythingcited by 75
  32. 2018Joint Optic Disc and Cup Segmentation Based on Multi-label Deep Network and Polar Transformationcited by 73
  33. 20233DSAM-adapter: Holistic adaptation of SAM from 2D to 3D for promptable tumor segmentationcited by 70
  34. 2020An automatic multi-tissue human fetal brain segmentation benchmark using the Fetal Tissue Annotation Datasetcited by 59
  35. 2022CrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwannoma and Cochlea Segmentationcited by 58
  36. 2023How to Efficiently Adapt Large Segmentation Model(SAM) to Medical Imagescited by 53
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  38. 2020Deep Learning to Segment Pelvic Bones: Large-scale CT Datasets and Baseline Modelscited by 45

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Citing papers per year: 2023: 1; 2024: 21; 2025: 20; 2026: 12.

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  1. 2024VisionLLM v2: An End-to-End Generalist Multimodal Large Language Model for Hundreds of Vision-Language Taskscited by 136
  2. 2024Segment Anything Model for Medical Image Segmentation: Current Applications and Future Directionscited by 97
  3. 2024GMAI-MMBench: A Comprehensive Multimodal Evaluation Benchmark Towards General Medical AIcited by 96
  4. 2024MedTrinity-25M: A Large-scale Multimodal Dataset with Multigranular Annotations for Medicinecited by 79
  5. 2023ScribblePrompt: Fast and Flexible Interactive Segmentation for Any Biomedical Imagecited by 47
  6. 2024Interactive Medical Image Segmentation: A Benchmark Dataset and Baselinecited by 30
  7. 2024Towards a Multimodal Large Language Model with Pixel-Level Insight for Biomedicinecited by 28
  8. 2024Interpretable Bilingual Multimodal Large Language Model for Diverse Biomedical Taskscited by 24
  9. 2024GMAI-VL & GMAI-VL-5.5M: A Large Vision-Language Model and A Comprehensive Multimodal Dataset Towards General Medical AIcited by 23
  10. 2024Uni-Med: A Unified Medical Generalist Foundation Model For Multi-Task Learning Via Connector-MoEcited by 18
  11. 2024A Refer-and-Ground Multimodal Large Language Model for Biomedicinecited by 14
  12. 2024Towards a vision foundation model for comprehensive assessment of Cardiac MRIcited by 13
38 more
  1. 2025SAM2 for Image and Video Segmentation: A Comprehensive Surveycited by 13
  2. 2024MultiverSeg: Scalable Interactive Segmentation of Biomedical Imaging Datasets with In-Context Guidancecited by 11
  3. 2025SegAnyPET: Universal Promptable Segmentation from Positron Emission Tomography Imagescited by 11
  4. 2025UniBiomed: A Universal Foundation Model for Grounded Biomedical Image Interpretationcited by 10
  5. 2025DrVD-Bench: Do Vision-Language Models Reason Like Human Doctors in Medical Image Diagnosis?cited by 10
  6. 2025MedReasoner: Reinforcement Learning Drives Reasoning Grounding from Clinical Thought to Pixel-Level Precisioncited by 10
  7. 2025MedQ-Bench: Evaluating and Exploring Medical Image Quality Assessment Abilities in MLLMscited by 9
  8. 2025MediSee: Reasoning-based Pixel-level Perception in Medical Imagescited by 8
  9. 2025PRS-Med: Position Reasoning Segmentation in Medical Imagingcited by 8
  10. 2025Ophiuchus: Incentivizing Tool-augmented "Think with Images" for Joint Medical Segmentation, Understanding and Reasoningcited by 8
  11. 2025Guiding Medical Vision-Language Models with Explicit Visual Prompts: Framework Design and Comprehensive Exploration of Prompt Variationscited by 7
  12. 2024SimTxtSeg: Weakly-Supervised Medical Image Segmentation with Simple Text Cuescited by 6
  13. 2024Sam2Rad: A Segmentation Model for Medical Images with Learnable Promptscited by 6
  14. 2025MedicoSAM: Robust Improvement of SAM for Medical Imagingcited by 6
  15. 2025RadSAM: Segmenting 3D radiological images with a 2D promptable modelcited by 6
  16. 2024OpenMEDLab: An Open-source Platform for Multi-modality Foundation Models in Medicinecited by 5
  17. 2024SegICL: A Multimodal In-context Learning Framework for Enhanced Segmentation in Medical Imagingcited by 5
  18. 2026When Models Learn to Ask Why: Adaptive Causal Reasoning for Trustworthy Medical Vision-Language Modelscited by 5
  19. 2025MedM-VL: What Makes a Good Medical LVLM?cited by 4
  20. 2024Towards Ground-truth-free Evaluation of Any Segmentation in Medical Imagescited by 3
  21. 2024Zero-shot capability of SAM-family models for bone segmentation in CT scanscited by 3
  22. 2025MedSAMix: A Training-Free Model Merging Approach for Medical Image Segmentationcited by 3
  23. 2026CARE: Towards Clinical Accountability in Multi-Modal Medical Reasoning with an Evidence-Grounded Agentic Frameworkcited by 3
  24. 2026Beyond Medical Diagnostics: How Medical Multimodal Large Language Models Think in Spacecited by 3
  25. 2025ClinKD: Cross-Modal Clinical Knowledge Distiller For Multi-Task Medical Imagescited by 2
  26. 2025The Application of Deep Learning for Lymph Node Segmentation: A Systematic Reviewcited by 2
  27. 2025Multi-Modal Explainable Medical AI Assistant for Trustworthy Human-AI Collaborationcited by 2
  28. 2026UniReason-Med: A Shared Grounded Reasoning Interface for 2D-to-3D Transfer in Medical VQAcited by 2
  29. 2025MediRound: Multi-Round Entity-Level Reasoning Segmentation in Medical Imagescited by 1
  30. 2026CORE-Seg: Reasoning-Driven Segmentation for Complex Lesions via Reinforcement Learningcited by 1
  31. 2024Does SAM dream of EIG? Characterizing Interactive Segmenter Performance using Expected Information Gaincited by 0
  32. 2024Improved Baselines with Synchronized Encoding for Universal Medical Image Segmentationcited by 0
  33. 2024Intuitive Axial Augmentation Using Polar-Sine-Based Piecewise Distortion for Medical Slice-Wise Segmentationcited by 0
  34. 2025SpinalSAM-R1: A Vision-Language Multimodal Interactive System for Spine CT Segmentationcited by 0
  35. 2025MedGEN-Bench: A Contextually Entangled Benchmark for Open-ended Multimodal Medical Generationcited by 0
  36. 2026MedVeriSeg: Teaching LISA-Like Medical Segmentation Models to Verify Query Validity Without Extra Trainingcited by 0
  37. 2026From Boundaries to Semantics: Prompt-Guided Multi-Task Learning for Petrographic Thin-section Segmentationcited by 0
  38. 2026Med-R2: An Adversarial Benchmark for Evidence-Grounded Reasoning in Medical VLMscited by 0

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