mlsanityData to 7 Oct 2026

Uncertainty-aware Self-ensembling Model for Semi-supervised 3D Left Atrium Segmentation

arXiv 1907.07034 ↗First posted 16 Jul 2019cs.CVcited by 378

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Abstract (arXiv)

Training deep convolutional neural networks usually requires a large amount of labeled data. However, it is expensive and time-consuming to annotate data for medical image segmentation tasks. In this paper, we present a novel uncertainty-aware semi-supervised framework for left atrium segmentation from 3D MR images. Our framework can effectively leverage the unlabeled data by encouraging consistent predictions of the same input under different perturbations. Concretely, the framework consists of a student model and a teacher model, and the student model learns from the teacher model by minimizing a segmentation loss and a consistency loss with respect to the targets of the teacher model. We design a novel uncertainty-aware scheme to enable the student model to gradually learn from the meaningful and reliable targets by exploiting the uncertainty information. Experiments show that our method achieves high performance gains by incorporating the unlabeled data. Our method outperforms the state-of-the-art semi-supervised methods, demonstrating the potential of our framework for the challenging semi-supervised problems.

Key facts. Cited by 378 papers in the map (data through 7 Oct 2026). First posted on arXiv 16 Jul 2019.

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Citing papers per year: 2021: 55; 2022: 58; 2023: 78; 2024: 64; 2025: 83; 2026: 40.

378 papers.

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  1. 2021In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learningcited by 301
  2. 2022Revisiting Weak-to-Strong Consistency in Semi-Supervised Semantic Segmentationcited by 177
  3. 2023Bidirectional Copy-Paste for Semi-Supervised Medical Image Segmentationcited by 115
  4. 2022LViT: Language meets Vision Transformer in Medical Image Segmentationcited by 110
  5. 2021Mutual Consistency Learning for Semi-supervised Medical Image Segmentationcited by 107
  6. 2021Semi-supervised Left Atrium Segmentation with Mutual Consistency Trainingcited by 104
  7. 2021Recent advances and clinical applications of deep learning in medical image analysiscited by 104
  8. 2021Semi-Supervised Medical Image Segmentation via Cross Teaching between CNN and Transformercited by 99
  9. 2022Exploring Smoothness and Class-Separation for Semi-supervised Medical Image Segmentationcited by 93
  10. 2021SimCVD: Simple Contrastive Voxel-Wise Representation Distillation for Semi-Supervised Medical Image Segmentationcited by 86
  11. 2022Learning with Limited Annotations: A Survey on Deep Semi-Supervised Learning for Medical Image Segmentationcited by 74
  12. 2022Scribble-Supervised Medical Image Segmentation via Dual-Branch Network and Dynamically Mixed Pseudo Labels Supervisioncited by 64
38 more
  1. 2022Trustworthy clinical AI solutions: a unified review of uncertainty quantification in deep learning models for medical image analysiscited by 62
  2. 2023Advances in Medical Image Analysis with Vision Transformers: A Comprehensive Reviewcited by 62
  3. 2021Inconsistency-aware Uncertainty Estimation for Semi-supervised Medical Image Segmentationcited by 61
  4. 2023A Review of Uncertainty Estimation and its Application in Medical Imagingcited by 59
  5. 2024UniMatch V2: Pushing the Limit of Semi-Supervised Semantic Segmentationcited by 53
  6. 2022Enhancing Pseudo Label Quality for Semi-Supervised Domain-Generalized Medical Image Segmentationcited by 51
  7. 2021Momentum Contrastive Voxel-wise Representation Learning for Semi-supervised Volumetric Medical Image Segmentationcited by 49
  8. 2024Unleashing the Potential of SAM for Medical Adaptation via Hierarchical Decodingcited by 48
  9. 2021Diminishing Uncertainty within the Training Pool: Active Learning for Medical Image Segmentationcited by 44
  10. 2021Local contrastive loss with pseudo-label based self-training for semi-supervised medical image segmentationcited by 43
  11. 2023Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspectivecited by 43
  12. 2021Federated Semi-supervised Medical Image Classification via Inter-client Relation Matchingcited by 42
  13. 2023A review of uncertainty quantification in medical image analysis: probabilistic and non-probabilistic methodscited by 39
  14. 2021Spatial Uncertainty-Aware Semi-Supervised Crowd Countingcited by 38
  15. 2023Towards Generic Semi-Supervised Framework for Volumetric Medical Image Segmentationcited by 35
  16. 2023Continual Self-supervised Learning: Towards Universal Multi-modal Medical Data Representation Learningcited by 34
  17. 2022Class-Aware Adversarial Transformers for Medical Image Segmentationcited by 33
  18. 2021Self-Paced Contrastive Learning for Semi-supervised Medical Image Segmentation with Meta-labelscited by 32
  19. 2022RSCFed: Random Sampling Consensus Federated Semi-supervised Learningcited by 32
  20. 2022Mine yOur owN Anatomy: Revisiting Medical Image Segmentation with Extremely Limited Labelscited by 30
  21. 2023Correlation-Aware Mutual Learning for Semi-supervised Medical Image Segmentationcited by 30
  22. 2021Uncertainty Estimation via Response Scaling for Pseudo-mask Noise Mitigation in Weakly-supervised Semantic Segmentationcited by 28
  23. 2022Calibrating Label Distribution for Class-Imbalanced Barely-Supervised Knee Segmentationcited by 27
  24. 2022LE-UDA: Label-efficient unsupervised domain adaptation for medical image segmentationcited by 27
  25. 2023RCPS: Rectified Contrastive Pseudo Supervision for Semi-Supervised Medical Image Segmentationcited by 27
  26. 2021Medical Image Analysis on Left Atrial LGE MRI for Atrial Fibrillation Studies: A Reviewcited by 26
  27. 2022Bootstrapping Semi-supervised Medical Image Segmentation with Anatomical-aware Contrastive Distillationcited by 26
  28. 2022NP-Match: When Neural Processes meet Semi-Supervised Learningcited by 25
  29. 2023DHC: Dual-debiased Heterogeneous Co-training Framework for Class-imbalanced Semi-supervised Medical Image Segmentationcited by 25
  30. 2021All-Around Real Label Supervision: Cyclic Prototype Consistency Learning for Semi-supervised Medical Image Segmentationcited by 24
  31. 2022MT-UDA: Towards Unsupervised Cross-modality Medical Image Segmentation with Limited Source Labelscited by 24
  32. 2023Co-training with High-Confidence Pseudo Labels for Semi-supervised Medical Image Segmentationcited by 24
  33. 2021Dual-Consistency Semi-Supervised Learning with Uncertainty Quantification for COVID-19 Lesion Segmentation from CT Imagescited by 22
  34. 2021Uncertainty-Guided Mutual Consistency Learning for Semi-Supervised Medical Image Segmentationcited by 22
  35. 2022MagicNet: Semi-Supervised Multi-Organ Segmentation via Magic-Cube Partition and Recoverycited by 22
  36. 2023Calibrating Uncertainty for Semi-Supervised Crowd Countingcited by 22
  37. 2024Learnable Prompting SAM-induced Knowledge Distillation for Semi-supervised Medical Image Segmentationcited by 22
  38. 2021Medical Image Segmentation with Limited Supervision: A Review of Deep Network Modelscited by 21

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