mlsanityData to 7 Oct 2026

Segment Anything in Medical Images

arXiv 2304.12306 ↗First posted 24 Apr 2023eess.IV cs.CVcited by 226

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Abstract (arXiv)

Medical image segmentation is a critical component in clinical practice, facilitating accurate diagnosis, treatment planning, and disease monitoring. However, existing methods, often tailored to specific modalities or disease types, lack generalizability across the diverse spectrum of medical image segmentation tasks. Here we present MedSAM, a foundation model designed for bridging this gap by enabling universal medical image segmentation. The model is developed on a large-scale medical image dataset with 1,570,263 image-mask pairs, covering 10 imaging modalities and over 30 cancer types. We conduct a comprehensive evaluation on 86 internal validation tasks and 60 external validation tasks, demonstrating better accuracy and robustness than modality-wise specialist models. By delivering accurate and efficient segmentation across a wide spectrum of tasks, MedSAM holds significant potential to expedite the evolution of diagnostic tools and the personalization of treatment plans.

Key facts. Cited by 226 papers in the map (data through 7 Oct 2026). Builds on 27 of its 54 references that are in the map. First posted on arXiv 24 Apr 2023.

Builds on

27 of 54 references.

References · 27

  1. 2017Attention Is All You Needcited by 59,932
  2. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  3. 2020Language Models are Few-Shot Learnerscited by 32,199
  4. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  5. 2023Segment Anythingcited by 8,158
  6. 2021Masked Autoencoders Are Scalable Vision Learnerscited by 7,339
  7. 2016Layer Normalizationcited by 5,579
  8. 2018Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentationcited by 3,210
  9. 2016V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentationcited by 2,284
  10. 2020Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domainscited by 2,170
  11. 2020Image Segmentation Using Deep Learning: A Surveycited by 659
  12. 2021The Medical Segmentation Decathloncited by 620
15 more
  1. 2023Segment Everything Everywhere All at Oncecited by 546
  2. 2018Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challengecited by 508
  3. 2017Deep Learning for Medical Image Analysiscited by 399
  4. 2023Segment Anything Model for Medical Image Analysis: an Experimental Studycited by 291
  5. 2023Segment Anything Model (SAM) for Digital Pathology: Assess Zero-shot Segmentation on Whole Slide Imagingcited by 161
  6. 2023Segment Anything Is Not Always Perfect: An Investigation of SAM on Different Real-world Applicationscited by 121
  7. 2017DeepIGeoS: A Deep Interactive Geodesic Framework for Medical Image Segmentationcited by 110
  8. 2017Interactive Medical Image Segmentation using Deep Learning with Image-specific Fine-tuningcited by 110
  9. 2023Can SAM Segment Anything? When SAM Meets Camouflaged Object Detectioncited by 99
  10. 2023SAM Struggles in Concealed Scenes -- Empirical Study on Segment Anythingcited by 75
  11. 2023Can SAM Segment Polyps?cited by 59
  12. 2023When SAM Meets Medical Images: An Investigation of Segment Anything Model (SAM) on Multi-phase Liver Tumor Segmentationcited by 52
  13. 2021MIDeepSeg: Minimally Interactive Segmentation of Unseen Objects from Medical Images Using Deep Learningcited by 45
  14. 2023SAM vs BET: A Comparative Study for Brain Extraction and Segmentation of Magnetic Resonance Images using Deep Learningcited by 24
  15. 2023Learning to "Segment Anything" in Thermal Infrared Images through Knowledge Distillation with a Large Scale Dataset SATIRcited by 11

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 18; 2024: 82; 2025: 95; 2026: 31.

226 papers.

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  1. 2023Multimodal Foundation Models: From Specialists to General-Purpose Assistantscited by 247
  2. 2024BiomedParse: a biomedical foundation model for image parsing of everything everywhere all at oncecited by 107
  3. 2023Large-Vocabulary Segmentation for Medical Images with Text Promptscited by 60
  4. 2024TotalSegmentator MRI: Robust Sequence-independent Segmentation of Multiple Anatomic Structures in MRIcited by 58
  5. 2023Annotation-free Audio-Visual Segmentationcited by 44
  6. 2023Are Natural Domain Foundation Models Useful for Medical Image Classification?cited by 44
  7. 2024A large-scale multicenter breast cancer DCE-MRI benchmark dataset with expert segmentationscited by 40
  8. 2023The Multi-modality Cell Segmentation Challenge: Towards Universal Solutionscited by 39
  9. 2024MedCLIP-SAMv2: Towards Universal Text-Driven Medical Image Segmentationcited by 37
  10. 2024Multi-Scale and Detail-Enhanced Segment Anything Model for Salient Object Detectioncited by 29
  11. 2024Foundation Models for Biomedical Image Segmentation: A Surveycited by 28
  12. 2024Data-Centric Foundation Models in Computational Healthcare: A Surveycited by 27
38 more
  1. 2024Foundation Models in Radiology: What, How, When, Why and Why Notcited by 26
  2. 2025Scaling up self-supervised learning for improved surgical foundation modelscited by 25
  3. 2024UltraSam: A Foundation Model for Ultrasound using Large Open-Access Segmentation Datasetscited by 23
  4. 2024EVA-X: A Foundation Model for General Chest X-ray Analysis with Self-supervised Learningcited by 22
  5. 2024Knowledge-enhanced Pretraining for Vision-language Pathology Foundation Model on Cancer Diagnosiscited by 21
  6. 2025EdgeTAM: On-Device Track Anything Modelcited by 21
  7. 2024Exploring Deeper! Segment Anything Model with Depth Perception for Camouflaged Object Detectioncited by 20
  8. 2023Learning the What and How of Annotation in Video Object Segmentationcited by 19
  9. 2023Self-Sampling Meta SAM: Enhancing Few-shot Medical Image Segmentation with Meta-Learningcited by 18
  10. 2023SAM-DA: UAV Tracks Anything at Night with SAM-Powered Domain Adaptationcited by 17
  11. 2024On Efficient Variants of Segment Anything Model: A Surveycited by 16
  12. 2024ICH-SCNet: Intracerebral Hemorrhage Segmentation and Prognosis Classification Network Using CLIP-guided SAM mechanismcited by 16
  13. 2023AnyStar: Domain randomized universal star-convex 3D instance segmentationcited by 14
  14. 2023Open-NeRF: Towards Open Vocabulary NeRF Decompositioncited by 13
  15. 2024Frontiers in Intelligent Colonoscopycited by 13
  16. 2024SAM Fewshot Finetuning for Anatomical Segmentation in Medical Imagescited by 12
  17. 2024HICEScore: A Hierarchical Metric for Image Captioning Evaluationcited by 12
  18. 2024ASI-Seg: Audio-Driven Surgical Instrument Segmentation with Surgeon Intention Understandingcited by 12
  19. 2025Enhancing SAM with Efficient Prompting and Preference Optimization for Semi-supervised Medical Image Segmentationcited by 12
  20. 2025CRISP-SAM2: SAM2 with Cross-Modal Interaction and Semantic Prompting for Multi-Organ Segmentationcited by 12
  21. 2023RigNet++: Semantic Assisted Repetitive Image Guided Network for Depth Completioncited by 11
  22. 2024VIBESegmentator: Full Body MRI Segmentation for the NAKO and UK Biobankcited by 11
  23. 2025Noise-Inspired Diffusion Model for Generalizable Low-Dose CT Reconstructioncited by 11
  24. 2025GAMED-Snake: Gradient-aware Adaptive Momentum Evolution Deep Snake Model for Multi-organ Segmentationcited by 10
  25. 20253D Foundation Model for Generalizable Disease Detection in Head Computed Tomographycited by 10
  26. 2023When 3D Bounding-Box Meets SAM: Point Cloud Instance Segmentation with Weak-and-Noisy Supervisioncited by 9
  27. 2025Building a General SimCLR Self-Supervised Foundation Model Across Neurological Diseases to Advance 3D Brain MRI Diagnosescited by 9
  28. 2023Using Unreliable Pseudo-Labels for Label-Efficient Semantic Segmentationcited by 8
  29. 2024Surgical-DeSAM: Decoupling SAM for Instrument Segmentation in Robotic Surgerycited by 8
  30. 2024Polyp SAM 2: Advancing Zero shot Polyp Segmentation in Colorectal Cancer Detectioncited by 8
  31. 2024PSFHS Challenge Report: Pubic Symphysis and Fetal Head Segmentation from Intrapartum Ultrasound Imagescited by 8
  32. 2024Pixel super-resolved virtual staining of label-free tissue using diffusion modelscited by 8
  33. 2025MediSee: Reasoning-based Pixel-level Perception in Medical Imagescited by 8
  34. 2025CenterMamba-SAM: Center-Prioritized Scanning and Temporal Prototypes for Brain Lesion Segmentationcited by 8
  35. 2023Zero-Shot Segmentation of Eye Features Using the Segment Anything Model (SAM)cited by 7
  36. 2023How to Efficiently Annotate Images for Best-Performing Deep Learning Based Segmentation Models: An Empirical Study with Weak and Noisy Annotations and Segment Anything Modelcited by 7
  37. 2024Augmenting Efficient Real-time Surgical Instrument Segmentation in Video with Point Tracking and Segment Anythingcited by 7
  38. 2024Embedded Visual Prompt Tuningcited by 7

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