mlsanityData to 14 Oct 2026

CheXFusion: Effective Fusion of Multi-View Features using Transformers for Long-Tailed Chest X-Ray Classification

arXiv 2308.03968 ↗First posted 8 Aug 2023cs.CV cs.AIcited by 12

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Abstract (arXiv)

Medical image classification poses unique challenges due to the long-tailed distribution of diseases, the co-occurrence of diagnostic findings, and the multiple views available for each study or patient. This paper introduces our solution to the ICCV CVAMD 2023 Shared Task on CXR-LT: Multi-Label Long-Tailed Classification on Chest X-Rays. Our approach introduces CheXFusion, a transformer-based fusion module incorporating multi-view images. The fusion module, guided by self-attention and cross-attention mechanisms, efficiently aggregates multi-view features while considering label co-occurrence. Furthermore, we explore data balancing and self-training methods to optimize the model's performance. Our solution achieves state-of-the-art results with 0.372 mAP in the MIMIC-CXR test set, securing 1st place in the competition. Our success in the task underscores the significance of considering multi-view settings, class imbalance, and label co-occurrence in medical image classification. Public code is available at https://github.com/dongkyuk/CXR-LT-public-solution

Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). Builds on 26 of its 41 references that are in the map. First posted on arXiv 8 Aug 2023.

Builds on

26 of 41 references.

References · 26

  1. 2017Attention Is All You Needcited by 60,361
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  3. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
  4. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  5. 2020End-to-End Object Detection with Transformerscited by 7,414
  6. 2017Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layercited by 3,509
  7. 2019RandAugment: Practical automated data augmentation with a reduced search spacecited by 2,269
  8. 2019CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparisoncited by 1,423
  9. 2019Self-training with Noisy Student improves ImageNet classificationcited by 1,311
  10. 2016Deep Networks with Stochastic Depthcited by 979
  11. 2017ChestX-ray8: Hospital-scale Chest X-ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseasescited by 972
  12. 2019Decoupling Representation and Classifier for Long-Tailed Recognitioncited by 809
14 more
  1. 2019MIMIC-CXR-JPG, a large publicly available database of labeled chest radiographscited by 597
  2. 2021Deep Long-Tailed Learning: A Surveycited by 417
  3. 2020Asymmetric Loss For Multi-Label Classificationcited by 381
  4. 2020CheXbert: Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERTcited by 337
  5. 2020VinDr-CXR: An open dataset of chest X-rays with radiologist's annotationscited by 239
  6. 2020A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promisescited by 231
  7. 2021Query2Label: A Simple Transformer Way to Multi-Label Classificationcited by 128
  8. 2020Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasetscited by 122
  9. 2019Learning Semantic-Specific Graph Representation for Multi-Label Image Recognitioncited by 116
  10. 2017Multi-label Image Recognition by Recurrently Discovering Attentional Regionscited by 83
  11. 2020Attention-Driven Dynamic Graph Convolutional Network for Multi-Label Image Recognitioncited by 80
  12. 2021ML-Decoder: Scalable and Versatile Classification Headcited by 79
  13. 2022Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark Studycited by 45
  14. 2018Large Scale Automated Reading of Frontal and Lateral Chest X-Rays using Dual Convolutional Neural Networkscited by 20

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 5; 2025: 5; 2026: 1.

12 papers.

  1. 2023Towards long-tailed, multi-label disease classification from chest X-ray: Overview of the CXR-LT challengecited by 22
  2. 2025CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-raycited by 10
  3. 2024Cardiovascular Disease Detection from Multi-View Chest X-rays with BI-Mambacited by 9
  4. 2025Efficient Medical Vision-Language Alignment Through Adapting Masked Vision Modelscited by 5
  5. 2024LTCXNet: Advancing Chest X-Ray Analysis with Solutions for Long-Tailed Multi-Label Classification and Fairness Challengescited by 1
  6. 2025Hierarchical Corpus-View-Category Refinement for Carotid Plaque Risk Grading in Ultrasoundcited by 1
  7. 2024Ensemble of ConvNeXt V2 and MaxViT for Long-Tailed CXR Classification with View-Based Aggregationcited by 0
  8. 2024Random Token Fusion for Multi-View Medical Diagnosiscited by 0
  9. 2024Hierarchical mutual distillation for multi-view fusion: Learning from all possible view combinationscited by 0
  10. 2025CheX-DS: Improving Chest X-ray Image Classification with Ensemble Learning Based on DenseNet and Swin Transformercited by 0
  11. 2025SP-Det: Self-Prompted Dual-Text Fusion for Generalized Multi-Label Lesion Detectioncited by 0
  12. 2026Trusted Multi-View Deep Learning Classification of Fetal Congenital Heart Disease with Feature-level and Decision-level Fusioncited by 0