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FocalMix: Semi-Supervised Learning for 3D Medical Image Detection

arXiv 2003.09108 ↗First posted 20 Mar 2020cs.CVcited by 52

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Abstract (arXiv)

Applying artificial intelligence techniques in medical imaging is one of the most promising areas in medicine. However, most of the recent success in this area highly relies on large amounts of carefully annotated data, whereas annotating medical images is a costly process. In this paper, we propose a novel method, called FocalMix, which, to the best of our knowledge, is the first to leverage recent advances in semi-supervised learning (SSL) for 3D medical image detection. We conducted extensive experiments on two widely used datasets for lung nodule detection, LUNA16 and NLST. Results show that our proposed SSL methods can achieve a substantial improvement of up to 17.3% over state-of-the-art supervised learning approaches with 400 unlabeled CT scans.

Key facts. Cited by 52 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Mar 2020.

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Citing papers per year: 2021: 20; 2022: 11; 2023: 11; 2024: 2; 2025: 5; 2026: 3.

52 papers.

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  1. 2021Big Self-Supervised Models Advance Medical Image Classificationcited by 320
  2. 2021Recent advances and clinical applications of deep learning in medical image analysiscited by 104
  3. 2025MedAgent-Pro: Towards Evidence-based Multi-modal Medical Diagnosis via Reasoning Agentic Workflowcited by 71
  4. 2022CycleMix: A Holistic Strategy for Medical Image Segmentation from Scribble Supervisioncited by 64
  5. 2021Preservational Learning Improves Self-supervised Medical Image Models by Reconstructing Diverse Contextscited by 59
  6. 2022BoostMIS: Boosting Medical Image Semi-supervised Learning with Adaptive Pseudo Labeling and Informative Active Annotationcited by 54
  7. 2021Federated Semi-supervised Medical Image Classification via Inter-client Relation Matchingcited by 42
  8. 2022Robust and Efficient Medical Imaging with Self-Supervisioncited by 40
  9. 2023CLIP in Medical Imaging: A Surveycited by 40
  10. 2021Survey: Image Mixing and Deleting for Data Augmentationcited by 25
  11. 2021Dual-Consistency Semi-Supervised Learning with Uncertainty Quantification for COVID-19 Lesion Segmentation from CT Imagescited by 22
  12. 2021SSMD: Semi-Supervised Medical Image Detection with Adaptive Consistency and Heterogeneous Perturbationcited by 19
38 more
  1. 2021Combating Noise: Semi-supervised Learning by Region Uncertainty Quantificationcited by 18
  2. 2021TOHAN: A One-step Approach towards Few-shot Hypothesis Adaptationcited by 17
  3. 2021Medical Image Segmentation with 3D Convolutional Neural Networks: A Surveycited by 16
  4. 2022Joint Self-Supervised Image-Volume Representation Learning with Intra-Inter Contrastive Clusteringcited by 16
  5. 2023Label-Efficient Deep Learning in Medical Image Analysis: Challenges and Future Directionscited by 14
  6. 2024Sparse Semi-DETR: Sparse Learnable Queries for Semi-Supervised Object Detectioncited by 13
  7. 2021SCPM-Net: An Anchor-free 3D Lung Nodule Detection Network using Sphere Representation and Center Points Matchingcited by 12
  8. 2023Confidence-based Visual Dispersal for Few-shot Unsupervised Domain Adaptationcited by 9
  9. 2021BioFors: A Large Biomedical Image Forensics Datasetcited by 8
  10. 2022Temporal Context Matters: Enhancing Single Image Prediction with Disease Progression Representationscited by 8
  11. 2023ZScribbleSeg: Zen and the Art of Scribble Supervised Medical Image Segmentationcited by 8
  12. 2021Learning Inductive Attention Guidance for Partially Supervised Pancreatic Ductal Adenocarcinoma Predictioncited by 7
  13. 2023Data efficient deep learning for medical image analysis: A surveycited by 6
  14. 2021OXnet: Omni-supervised Thoracic Disease Detection from Chest X-rayscited by 5
  15. 2021Semi-supervised classification of radiology images with NoTeacher: A Teacher that is not Meancited by 5
  16. 2022ORF-Net: Deep Omni-supervised Rib Fracture Detection from Chest CT Scanscited by 4
  17. 2023Rapid Image Labeling via Neuro-Symbolic Learningcited by 4
  18. 2023ASLseg: Adapting SAM in the Loop for Semi-supervised Liver Tumor Segmentationcited by 4
  19. 2021GuidedMix-Net: Learning to Improve Pseudo Masks Using Labeled Images as Referencecited by 3
  20. 2021AI-Based Detection, Classification and Prediction/Prognosis in Medical Imaging: Towards Radiophenomicscited by 2
  21. 2023Medical supervised masked autoencoders: Crafting a better masking strategy and efficient fine-tuning schedule for medical image classificationcited by 2
  22. 2023LORD: Leveraging Open-Set Recognition with Unknown Datacited by 2
  23. 2024Minimally Supervised Learning using Topological Projections in Self-Organizing Mapscited by 2
  24. 2026Towards Next-Generation Healthcare: A Survey of Medical Embodied AI for Perception, Decision-Making, and Actioncited by 2
  25. 2021Hetero-Modal Learning and Expansive Consistency Constraints for Semi-Supervised Detection from Multi-Sequence Datacited by 1
  26. 2023Deep Omni-supervised Learning for Rib Fracture Detection from Chest Radiology Imagescited by 1
  27. 2023Self-Supervised and Semi-Supervised Polyp Segmentation using Synthetic Datacited by 1
  28. 2021About Explicit Variance Minimization: Training Neural Networks for Medical Imaging With Limited Data Annotationscited by 0
  29. 2021Organ localisation using supervised and semi supervised approaches combining reinforcement learning with imitation learningcited by 0
  30. 2022Lesion Localization in OCT by Semi-Supervised Object Detectioncited by 0
  31. 2022Contrastive Credibility Propagation for Reliable Semi-Supervised Learningcited by 0
  32. 2022Simultaneous Multiple Object Detection and Pose Estimation using 3D Model Infusion with Monocular Visioncited by 0
  33. 2022Introduction to Machine Learning for Physicians: A Survival Guide for Data Delugecited by 0
  34. 2022VertMatch: A Semi-supervised Framework for Vertebral Structure Detection in 3D Ultrasound Volumecited by 0
  35. 2025From Slices to Sequences: Autoregressive Tracking Transformer for Cohesive and Consistent 3D Lymph Node Detection in CT Scanscited by 0
  36. 2025Towards Precise Action Spotting: Addressing Temporal Misalignment in Labels with Dynamic Label Assignmentcited by 0
  37. 2025Deep Learning Approaches for Medical Imaging Under Varying Degrees of Label Availability: A Comprehensive Surveycited by 0
  38. 2025Stronger is not better: Better Augmentations in Contrastive Learning for Medical Image Segmentationcited by 0

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