mlsanityData to 14 Oct 2026

Learning with Limited Annotations: A Survey on Deep Semi-Supervised Learning for Medical Image Segmentation

arXiv 2207.14191 ↗First posted 28 Jul 2022cs.CVcited by 76

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Abstract (arXiv)

Medical image segmentation is a fundamental and critical step in many image-guided clinical approaches. Recent success of deep learning-based segmentation methods usually relies on a large amount of labeled data, which is particularly difficult and costly to obtain especially in the medical imaging domain where only experts can provide reliable and accurate annotations. Semi-supervised learning has emerged as an appealing strategy and been widely applied to medical image segmentation tasks to train deep models with limited annotations. In this paper, we present a comprehensive review of recently proposed semi-supervised learning methods for medical image segmentation and summarized both the technical novelties and empirical results. Furthermore, we analyze and discuss the limitations and several unsolved problems of existing approaches. We hope this review could inspire the research community to explore solutions for this challenge and further promote the developments in medical image segmentation field.

Key facts. Cited by 76 papers in the map (data through 14 Oct 2026). Builds on 104 of its 220 references that are in the map. First posted on arXiv 28 Jul 2022.

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104 of 220 references.

References · 104

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  3. 2015Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learningcited by 4,448
  4. 2016Simple and Scalable Predictive Uncertainty Estimation using Deep Ensemblescited by 3,926
  5. 2017What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?cited by 2,352
  6. 2016V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentationcited by 2,292
  7. 2020FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidencecited by 2,085
  8. 2021TransUNet: Transformers Make Strong Encoders for Medical Image Segmentationcited by 1,558
  9. 20163D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotationcited by 1,476
  10. 2018Attention U-Net: Learning Where to Look for the Pancreascited by 1,435
  11. 2019CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparisoncited by 1,423
  12. 2019MixMatch: A Holistic Approach to Semi-Supervised Learningcited by 1,391
38 more
  1. 2017A Survey on Deep Learning in Medical Image Analysiscited by 1,186
  2. 2016Temporal Ensembling for Semi-Supervised Learningcited by 1,057
  3. 2017Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learningcited by 920
  4. 2019Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)cited by 669
  5. 2017Deep Mutual Learningcited by 628
  6. 2021The Medical Segmentation Decathloncited by 628
  7. 2018ADVENT: Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentationcited by 623
  8. 2019Kvasir-SEG: A Segmented Polyp Datasetcited by 589
  9. 2019UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentationcited by 586
  10. 2017Understanding the Effective Receptive Field in Deep Convolutional Neural Networkscited by 553
  11. 2019The Liver Tumor Segmentation Benchmark (LiTS)cited by 509
  12. 2016Regularization With Stochastic Transformations and Perturbations for Deep Semi-Supervised Learningcited by 441
  13. 2019Uncertainty-aware Self-ensembling Model for Semi-supervised 3D Left Atrium Segmentationcited by 379
  14. 2020Semi-Supervised Semantic Segmentation with Cross-Consistency Trainingcited by 376
  15. 2019A large annotated medical image dataset for the development and evaluation of segmentation algorithmscited by 373
  16. 2020CHAOS Challenge -- Combined (CT-MR) Healthy Abdominal Organ Segmentationcited by 309
  17. 2018Attention Gated Networks: Learning to Leverage Salient Regions in Medical Imagescited by 272
  18. 2019Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentationcited by 260
  19. 2021A Survey on Deep Semi-supervised Learningcited by 251
  20. 2021CoTr: Efficiently Bridging CNN and Transformer for 3D Medical Image Segmentationcited by 227
  21. 2020AbdomenCT-1K: Is Abdominal Organ Segmentation A Solved Problem?cited by 224
  22. 2020Semi-supervised Medical Image Segmentation through Dual-task Consistencycited by 216
  23. 2016Gland Segmentation in Colon Histology Images: The GlaS Challenge Contestcited by 203
  24. 2016Skin Lesion Analysis toward Melanoma Detection: A Challenge at the International Symposium on Biomedical Imaging (ISBI) 2016, hosted by the International Skin Imaging Collaboration (ISIC)cited by 198
  25. 2019The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 Challengecited by 190
  26. 2018Not-so-supervised: a survey of semi-supervised, multi-instance, and transfer learning in medical image analysiscited by 179
  27. 2019The KiTS19 Challenge Data: 300 Kidney Tumor Cases with Clinical Context, CT Semantic Segmentations, and Surgical Outcomescited by 172
  28. 2020Shape-aware Semi-supervised 3D Semantic Segmentation for Medical Imagescited by 152
  29. 2018Deep Co-Training for Semi-Supervised Image Recognitioncited by 147
  30. 2019Transformation Consistent Self-ensembling Model for Semi-supervised Medical Image Segmentationcited by 140
  31. 2019A Topological Loss Function for Deep-Learning based Image Segmentation using Persistent Homologycited by 134
  32. 2020An Overview of Deep Semi-Supervised Learningcited by 121
  33. 2021Mutual Consistency Learning for Semi-supervised Medical Image Segmentationcited by 108
  34. 2021Semi-supervised Left Atrium Segmentation with Mutual Consistency Trainingcited by 104
  35. 2020Efficient Semi-Supervised Gross Target Volume of Nasopharyngeal Carcinoma Segmentation via Uncertainty Rectified Pyramid Consistencycited by 102
  36. 2021Semi-Supervised Medical Image Segmentation via Cross Teaching between CNN and Transformercited by 100
  37. 2019Prior-aware Neural Network for Partially-Supervised Multi-Organ Segmentationcited by 88
  38. 2021SimCVD: Simple Contrastive Voxel-Wise Representation Distillation for Semi-Supervised Medical Image Segmentationcited by 86

50 most cited of 104 All 104 (JSON)

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Citing papers per year: 2022: 1; 2023: 16; 2024: 23; 2025: 23; 2026: 13.

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  1. 2024Mamba-UNet: UNet-Like Pure Visual Mamba for Medical Image Segmentationcited by 133
  2. 2024Segment Anything Model for Medical Image Segmentation: Current Applications and Future Directionscited by 97
  3. 2024Adaptive Bidirectional Displacement for Semi-Supervised Medical Image Segmentationcited by 30
  4. 2024Weak-Mamba-UNet: Visual Mamba Makes CNN and ViT Work Better for Scribble-based Medical Image Segmentationcited by 29
  5. 2024Learnable Prompting SAM-induced Knowledge Distillation for Semi-supervised Medical Image Segmentationcited by 23
  6. 2023Towards Segment Anything Model (SAM) for Medical Image Segmentation: A Surveycited by 21
  7. 2023SemiSAM: Enhancing Semi-Supervised Medical Image Segmentation via SAM-Assisted Consistency Regularizationcited by 19
  8. 2024DiffRect: Latent Diffusion Label Rectification for Semi-supervised Medical Image Segmentationcited by 15
  9. 2023Anatomically-aware Uncertainty for Semi-supervised Image Segmentationcited by 13
  10. 2023Segment Together: A Versatile Paradigm for Semi-Supervised Medical Image Segmentationcited by 12
  11. 2023Semi-supervised Segmentation of Histopathology Images with Noise-Aware Topological Consistencycited by 11
  12. 2025SegAnyPET: Universal Promptable Segmentation from Positron Emission Tomography Imagescited by 11
38 more
  1. 2024A Multispectral Automated Transfer Technique (MATT) for machine-driven image labeling utilizing the Segment Anything Model (SAM)cited by 8
  2. 2023Data efficient deep learning for medical image analysis: A surveycited by 6
  3. 2024Test-time generative augmentation for medical image segmentationcited by 6
  4. 2024PMT: Progressive Mean Teacher via Exploring Temporal Consistency for Semi-Supervised Medical Image Segmentationcited by 6
  5. 2025Uncertainty-aware Cross-training for Semi-supervised Medical Image Segmentationcited by 6
  6. 2023Weakly Semi-Supervised Detection in Lung Ultrasound Videoscited by 5
  7. 2023Competitive Ensembling Teacher-Student Framework for Semi-Supervised Left Atrium MRI Segmentationcited by 4
  8. 2024MatchSeg: Towards Better Segmentation via Reference Image Matchingcited by 4
  9. 2024Beyond Pixel-Wise Supervision for Medical Image Segmentation: From Traditional Models to Foundation Modelscited by 4
  10. 2024Predictive Accuracy-Based Active Learning for Medical Image Segmentationcited by 4
  11. 2025Text-driven Multiplanar Visual Interaction for Semi-supervised Medical Image Segmentationcited by 4
  12. 2023Towards more precise automatic analysis: a comprehensive survey of deep learning-based multi-organ segmentationcited by 3
  13. 2023Inherent Consistent Learning for Accurate Semi-supervised Medical Image Segmentationcited by 3
  14. 2024Segmenting Medical Images with Limited Datacited by 3
  15. 2024In-context learning for medical image segmentationcited by 3
  16. 2025SSS: Semi-Supervised SAM-2 with Efficient Prompting for Medical Imaging Segmentationcited by 3
  17. 2023Multi-organ segmentation: a progressive exploration of learning paradigms under scarce annotationcited by 2
  18. 2023Adaptive Semi-Supervised Segmentation of Brain Vessels with Ambiguous Labelscited by 2
  19. 2023Semi-Supervised Semantic Segmentation of Cell Nuclei via Diffusion-based Large-Scale Pre-Training and Collaborative Learningcited by 2
  20. 2023UCM-Net: A Lightweight and Efficient Solution for Skin Lesion Segmentation using MLP and CNNcited by 2
  21. 2025Context-Aware Doubly-Robust Semi-Supervised Learningcited by 2
  22. 2025Unlocking the Potential of Unlabeled Data in Semi-Supervised Domain Generalizationcited by 2
  23. 2025Semi-Supervised Medical Image Segmentation via Dual Networkscited by 2
  24. 2025SAM2-3dMed: Empowering SAM2 for 3D Medical Image Segmentationcited by 2
  25. 2026VQ-Seg: Vector-Quantized Token Perturbation for Semi-Supervised Medical Image Segmentationcited by 2
  26. 2022Analysing the effectiveness of a generative model for semi-supervised medical image segmentationcited by 1
  27. 2024Leveraging Fixed and Dynamic Pseudo-labels for Semi-supervised Medical Image Segmentationcited by 1
  28. 2024Probing Perfection: The Relentless Art of Meddling for Pulmonary Airway Segmentation from HRCT via a Human-AI Collaboration Based Active Learning Methodcited by 1
  29. 2025Knowledge Consultation for Semi-Supervised Semantic Segmentationcited by 1
  30. 2025MSA-UNet3+: Multi-Scale Attention UNet3+ with New Supervised Prototypical Contrastive Loss for Coronary DSA Image Segmentationcited by 1
  31. 2025Diversity-enhanced Collaborative Mamba for Semi-supervised Medical Image Segmentationcited by 1
  32. 2026Fully Differentiable Bidirectional Dual-Task Synergistic Learning for Semi-Supervised 3D Medical Image Segmentationcited by 1
  33. 2023Diagonal Hierarchical Consistency Learning for Semi-supervised Medical Image Segmentationcited by 0
  34. 2023Benefit from public unlabeled data: A Frangi filtering-based pretraining network for 3D cerebrovascular segmentationcited by 0
  35. 2024Self and Mixed Supervision to Improve Training Labels for Multi-Class Medical Image Segmentationcited by 0
  36. 2024SM2C: Boost the Semi-supervised Segmentation for Medical Image by using Meta Pseudo Labels and Mixed Imagescited by 0
  37. 2024Guidelines for Cerebrovascular Segmentation: Managing Imperfect Annotations in the context of Semi-Supervised Learningcited by 0
  38. 2024Dual-Teacher Ensemble Models with Double-Copy-Paste for 3D Semi-Supervised Medical Image Segmentationcited by 0

50 most cited of 76 All 76 (JSON)