mlsanityData to 7 Oct 2026

Deep learning for unsupervised domain adaptation in medical imaging: Recent advancements and future perspectives

arXiv 2308.01265 ↗First posted 18 Jul 2023eess.IV cs.CV cs.LGcited by 24

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Abstract (arXiv)

Deep learning has demonstrated remarkable performance across various tasks in medical imaging. However, these approaches primarily focus on supervised learning, assuming that the training and testing data are drawn from the same distribution. Unfortunately, this assumption may not always hold true in practice. To address these issues, unsupervised domain adaptation (UDA) techniques have been developed to transfer knowledge from a labeled domain to a related but unlabeled domain. In recent years, significant advancements have been made in UDA, resulting in a wide range of methodologies, including feature alignment, image translation, self-supervision, and disentangled representation methods, among others. In this paper, we provide a comprehensive literature review of recent deep UDA approaches in medical imaging from a technical perspective. Specifically, we categorize current UDA research in medical imaging into six groups and further divide them into finer subcategories based on the different tasks they perform. We also discuss the respective datasets used in the studies to assess the divergence between the different domains. Finally, we discuss emerging areas and provide insights and discussions on future research directions to conclude this survey.

Key facts. Cited by 24 papers in the map (data through 7 Oct 2026). Builds on 141 of its 305 references that are in the map. First posted on arXiv 18 Jul 2023.

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141 of 305 references.

References · 141

  1. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  2. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,282
  3. 2015Domain-Adversarial Training of Neural Networkscited by 3,023
  4. 2013Rich feature hierarchies for accurate object detection and semantic segmentationcited by 2,160
  5. 2014Unsupervised Domain Adaptation by Backpropagationcited by 1,906
  6. 2018Continual Lifelong Learning with Neural Networks: A Reviewcited by 1,313
  7. 2017A Survey on Deep Learning in Medical Image Analysiscited by 1,182
  8. 2017CyCADA: Cycle-Consistent Adversarial Domain Adaptationcited by 1,079
  9. 2017ChestX-ray8: Hospital-scale Chest X-ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseasescited by 969
  10. 2014Deep Visual-Semantic Alignments for Generating Image Descriptionscited by 966
  11. 2017Learning to Generalize: Meta-Learning for Domain Generalizationcited by 762
  12. 2021Domain Generalization: A Surveycited by 760
38 more
  1. 2017Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networkscited by 707
  2. 2018Deep Visual Domain Adaptation: A Surveycited by 634
  3. 2019Kvasir-SEG: A Segmented Polyp Datasetcited by 588
  4. 2018Learning to Adapt Structured Output Space for Semantic Segmentationcited by 584
  5. 2022Continual Test-Time Domain Adaptationcited by 520
  6. 2018Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challengecited by 508
  7. 2021Dynamic Neural Networks: A Surveycited by 405
  8. 2018HoVer-Net: Simultaneous Segmentation and Classification of Nuclei in Multi-Tissue Histology Imagescited by 387
  9. 2019A large annotated medical image dataset for the development and evaluation of segmentation algorithmscited by 371
  10. 2016EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videoscited by 366
  11. 2018A Survey of Unsupervised Deep Domain Adaptationcited by 361
  12. 2021Domain Adaptation for Medical Image Analysis: A Surveycited by 351
  13. 2016Dynamic Filter Networkscited by 318
  14. 2016Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networkscited by 307
  15. 2019CondConv: Conditionally Parameterized Convolutions for Efficient Inferencecited by 273
  16. 2020A Comprehensive Survey of Neural Architecture Search: Challenges and Solutionscited by 253
  17. 2019REFUGE Challenge: A Unified Framework for Evaluating Automated Methods for Glaucoma Assessment from Fundus Photographscited by 226
  18. 2016A Benchmark for Endoluminal Scene Segmentation of Colonoscopy Imagescited by 220
  19. 2020Universal Source-Free Domain Adaptationcited by 219
  20. 2016Gland Segmentation in Colon Histology Images: The GlaS Challenge Contestcited by 203
  21. 2020Universal Domain Adaptation through Self Supervisioncited by 172
  22. 20192017 Robotic Instrument Segmentation Challengecited by 166
  23. 2020Unsupervised Bidirectional Cross-Modality Adaptation via Deeply Synergistic Image and Feature Alignment for Medical Image Segmentationcited by 134
  24. 2016Multivariate mixture model for myocardium segmentation combining multi-source imagescited by 133
  25. 20202018 Robotic Scene Segmentation Challengecited by 123
  26. 2023EcoTTA: Memory-Efficient Continual Test-time Adaptation via Self-distilled Regularizationcited by 123
  27. 2020Multi-site fMRI Analysis Using Privacy-preserving Federated Learning and Domain Adaptation: ABIDE Resultscited by 122
  28. 2019Synergistic Image and Feature Adaptation: Towards Cross-Modality Domain Adaptation for Medical Image Segmentationcited by 121
  29. 2020A Survey on Negative Transfercited by 120
  30. 2021Causality-inspired Single-source Domain Generalization for Medical Image Segmentationcited by 118
  31. 2019Unsupervised Domain Adaptation through Self-Supervisioncited by 116
  32. 2019Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challengecited by 115
  33. 2018An introduction to domain adaptation and transfer learningcited by 112
  34. 2018Deep Cocktail Network: Multi-source Unsupervised Domain Adaptation with Category Shiftcited by 109
  35. 2020Test-Time Adaptable Neural Networks for Robust Medical Image Segmentationcited by 102
  36. 2019Evaluation of Algorithms for Multi-Modality Whole Heart Segmentation: An Open-Access Grand Challengecited by 100
  37. 2021OVANet: One-vs-All Network for Universal Domain Adaptationcited by 92
  38. 2020Self-Path: Self-supervision for Classification of Pathology Images with Limited Annotationscited by 89

50 most cited of 141 All 141 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 2; 2024: 6; 2025: 11; 2026: 5.

24 papers.

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  1. 2024Advancing UWF-SLO Vessel Segmentation with Source-Free Active Domain Adaptation and a Novel Multi-Center Datasetcited by 11
  2. 2024A Systematic Review of Generalization Research in Medical Image Classificationcited by 8
  3. 2023Data efficient deep learning for medical image analysis: A surveycited by 6
  4. 2023Domain Adaptive Graph Neural Networks for Constraining Cosmological Parameters Across Multiple Data Setscited by 6
  5. 2025CACTUS: An Open Dataset and Framework for Automated Cardiac Assessment and Classification of Ultrasound Images Using Deep Transfer Learningcited by 6
  6. 2025Augmentation-based Domain Generalization and Joint Training from Multiple Source Domains for Whole Heart Segmentationcited by 2
  7. 2024AdaptDiff: Cross-Modality Domain Adaptation via Weak Conditional Semantic Diffusion for Retinal Vessel Segmentationcited by 1
  8. 2025Leveraging Modified Ex Situ Tomography Data for Segmentation of In Situ Synchrotron X-Ray Computed Tomographycited by 1
  9. 2026A3-TTA: Adaptive Anchor Alignment Test-Time Adaptation for Image Segmentationcited by 1
  10. 2024Curvature Diversity-Driven Deformation and Domain Alignment for Point Cloudcited by 0
  11. 2024Gaussian Process Emulators for Few-Shot Segmentation in Cardiac MRIcited by 0
  12. 2024Multi-Source Unsupervised Domain Adaptation with Prototype Aggregationcited by 0
12 more
  1. 2025Color-Quality Invariance for Robust Medical Image Segmentationcited by 0
  2. 2025Bridging Synthetic-to-Real Gaps: Frequency-Aware Perturbation and Selection for Single-shot Multi-Parametric Mapping Reconstructioncited by 0
  3. 2025Efficient Self-Supervised Adaptation for Medical Image Analysiscited by 0
  4. 2025Domain-Adversarial Neural Network and Explainable AI for Reducing Tissue-of-Origin Signal in Pan-cancer Mortality Classificationcited by 0
  5. 2025Targeted Unlearning Using Perturbed Sign Gradient Methods With Applications On Medical Imagescited by 0
  6. 2025ADAptation: Reconstruction-based Unsupervised Active Learning for Breast Ultrasound Diagnosiscited by 0
  7. 2025Unsupervised Domain Adaptation via Content Alignment for Hippocampus Segmentationcited by 0
  8. 2025Semantic-aware Random Convolution and Source Matching for Domain Generalization in Medical Image Segmentationcited by 0
  9. 2026DDS-UDA: Dual-Domain Synergy for Unsupervised Domain Adaptation in Joint Segmentation of Optic Disc and Optic Cupcited by 0
  10. 2026Improving Generalization of Deep Learning for Brain Metastases Segmentation Across Institutionscited by 0
  11. 2026A cross-process welding penetration status prediction algorithm based on unsupervised domain adaptation in laser and TIG weldingcited by 0
  12. 2026Towards Practical Algorithm Selection for Unsupervised Domain Adaptation in Medical Imagingcited by 0