mlsanityData to 7 Oct 2026

Multi-view analysis of unregistered medical images using cross-view transformers

arXiv 2103.11390 ↗First posted 21 Mar 2021cs.CVcited by 35

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Abstract (arXiv)

Multi-view medical image analysis often depends on the combination of information from multiple views. However, differences in perspective or other forms of misalignment can make it difficult to combine views effectively, as registration is not always possible. Without registration, views can only be combined at a global feature level, by joining feature vectors after global pooling. We present a novel cross-view transformer method to transfer information between unregistered views at the level of spatial feature maps. We demonstrate this method on multi-view mammography and chest X-ray datasets. On both datasets, we find that a cross-view transformer that links spatial feature maps can outperform a baseline model that joins feature vectors after global pooling.

Key facts. Cited by 35 papers in the map (data through 7 Oct 2026). Builds on 8 of its 19 references that are in the map. First posted on arXiv 21 Mar 2021.

Builds on

8 of 19 references.

References · 8

  1. 2017Attention Is All You Needcited by 59,932
  2. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  3. 2019CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparisoncited by 1,410
  4. 2020Visual Transformers: Token-based Image Representation and Processing for Computer Visioncited by 333
  5. 2019Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screeningcited by 94
  6. 2018Large Scale Automated Reading of Frontal and Lateral Chest X-Rays using Dual Convolutional Neural Networkscited by 20
  7. 2020Quantifying the Value of Lateral Views in Deep Learning for Chest X-rayscited by 16
  8. 2019Cross-view Relation Networks for Mammogram Mass Detectioncited by 11

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 8; 2023: 11; 2024: 6; 2025: 6; 2026: 3.

35 papers.

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  1. 2022Transformers in Medical Imaging: A Surveycited by 245
  2. 2021A Survey of Visual Transformerscited by 117
  3. 2022A Transformer-Based Feature Segmentation and Region Alignment Method For UAV-View Geo-Localizationcited by 55
  4. 2022Transformers in Medical Image Analysis: A Reviewcited by 41
  5. 2022Surface Vision Transformers: Attention-Based Modelling applied to Cortical Analysiscited by 25
  6. 2023Towards Evaluating Explanations of Vision Transformers for Medical Imagingcited by 22
  7. 2023Transformers in Healthcare: A Surveycited by 17
  8. 2022Transformers Improve Breast Cancer Diagnosis from Unregistered Multi-View Mammogramscited by 11
  9. 2024MV-Swin-T: Mammogram Classification with Multi-view Swin Transformercited by 11
  10. 2022Cross-Field Transformer for Diabetic Retinopathy Grading on Two-field Fundus Imagescited by 9
  11. 2024Mammo-CLIP: Leveraging Contrastive Language-Image Pre-training (CLIP) for Enhanced Breast Cancer Diagnosis with Multi-view Mammographycited by 9
  12. 2024Cardiovascular Disease Detection from Multi-View Chest X-rays with BI-Mambacited by 9
23 more
  1. 2022Multi-View Hypercomplex Learning for Breast Cancer Screeningcited by 7
  2. 2023Detecting Heart Disease from Multi-View Ultrasound Images via Supervised Attention Multiple Instance Learningcited by 7
  3. 2023MoViT: Memorizing Vision Transformers for Medical Image Analysiscited by 6
  4. 2024A Deep Network for Explainable Prediction of Non-Imaging Phenotypes using Anatomical Multi-View Datacited by 6
  5. 2025XFMamba: Cross-Fusion Mamba for Multi-View Medical Image Classificationcited by 5
  6. 2023MultiNet with Transformers: A Model for Cancer Diagnosis Using Imagescited by 3
  7. 2023DisAsymNet: Disentanglement of Asymmetrical Abnormality on Bilateral Mammograms using Self-adversarial Learningcited by 3
  8. 2023M&M: Tackling False Positives in Mammography with a Multi-view and Multi-instance Learning Sparse Detectorcited by 2
  9. 2023TransReg: Cross-transformer as auto-registration module for multi-view mammogram mass detectioncited by 2
  10. 2025A Hybrid CNN-VSSM model for Multi-View, Multi-Task Mammography Analysis: Robust Diagnosis with Attention-Based Fusioncited by 2
  11. 2022Deep is a Luxury We Don't Havecited by 1
  12. 2023End-To-End Prediction of Knee Osteoarthritis Progression With Multi-Modal Transformerscited by 1
  13. 2023Case-level Breast Cancer Prediction for Real Hospital Settingscited by 1
  14. 2023HawkI: Homography & Mutual Information Guidance for 3D-free Single Image to Aerial Viewcited by 1
  15. 2025Breast Cancer Detection from Multi-View Screening Mammograms with Visual Prompt Tuningcited by 1
  16. 2025MammoClean: Toward Reproducible and Bias-Aware AI in Mammography through Dataset Harmonizationcited by 1
  17. 2024Random Token Fusion for Multi-View Medical Diagnosiscited by 0
  18. 2024Hierarchical mutual distillation for multi-view fusion: Learning from all possible view combinationscited by 0
  19. 2025Integrating AI for Human-Centric Breast Cancer Diagnostics: A Multi-Scale and Multi-View Swin Transformer Frameworkcited by 0
  20. 2025Convolutional Set Transformercited by 0
  21. 2026Axial-Centric Cross-Plane Attention for 3D Medical Image Classificationcited by 0
  22. 2026OTCHA: Optimal Transport-driven Confidence-aware Latent Hub Alignment for Multi-View Medical Image Classificationcited by 0
  23. 2026Token-Based Dual-view Fusion and Adaptation of Large Vision Models for Breast Cancer Classificationcited by 0