mlsanityData to 7 Oct 2026

A Survey on Biomedical Image Captioning

arXiv 1905.13302 ↗First posted 26 May 2019cs.CV cs.AIcited by 30

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Abstract (arXiv)

Image captioning applied to biomedical images can assist and accelerate the diagnosis process followed by clinicians. This article is the first survey of biomedical image captioning, discussing datasets, evaluation measures, and state of the art methods. Additionally, we suggest two baselines, a weak and a stronger one; the latter outperforms all current state of the art systems on one of the datasets.

Key facts. Cited by 30 papers in the map (data through 7 Oct 2026). First posted on arXiv 26 May 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 3; 2022: 7; 2023: 6; 2024: 6; 2025: 7; 2026: 1.

30 papers.

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  1. 2022Transformers in Medical Imaging: A Surveycited by 245
  2. 2023BiomedGPT: A Generalist Vision-Language Foundation Model for Diverse Biomedical Taskscited by 201
  3. 2022Translation between Molecules and Natural Languagecited by 173
  4. 2022Plausible May Not Be Faithful: Probing Object Hallucination in Vision-Language Pre-trainingcited by 71
  5. 2022Deep Learning Approaches on Image Captioning: A Reviewcited by 43
  6. 2024Automated Radiology Report Generation: A Review of Recent Advancescited by 43
  7. 2025Ask in Any Modality: A Comprehensive Survey on Multimodal Retrieval-Augmented Generationcited by 42
  8. 2023CLIP in Medical Imaging: A Surveycited by 40
  9. 2022Medical Image Captioning via Generative Pretrained Transformerscited by 20
  10. 2023Large-scale Long-tailed Disease Diagnosis on Radiology Imagescited by 17
  11. 2024Medical Multimodal Foundation Models in Clinical Diagnosis and Treatment: Applications, Challenges, and Future Directionscited by 17
  12. 2024Large Language Model Benchmarks in Medical Taskscited by 16
18 more
  1. 2021Natural Language Processing for Smart Healthcarecited by 14
  2. 2023A Systematic Review of Deep Learning-based Research on Radiology Report Generationcited by 14
  3. 20233D-MIR: A Benchmark and Empirical Study on 3D Medical Image Retrieval in Radiologycited by 12
  4. 2021Neural Attention for Image Captioning: Review of Outstanding Methodscited by 11
  5. 2024DENEB: A Hallucination-Robust Automatic Evaluation Metric for Image Captioningcited by 11
  6. 2025UMIT: Unifying Medical Imaging Tasks via Vision-Language Modelscited by 11
  7. 2021Diagnostic Captioning: A Surveycited by 6
  8. 2024MedMax: Mixed-Modal Instruction Tuning for Training Biomedical Assistantscited by 6
  9. 2025Scaling Up Biomedical Vision-Language Models: Fine-Tuning, Instruction Tuning, and Multi-Modal Learningcited by 6
  10. 2022IDEAL: Improved DEnse locAL Contrastive Learning for Semi-Supervised Medical Image Segmentationcited by 5
  11. 2025Structured Spectral Graph Representation Learning for Multi-label Abnormality Analysis from 3D CT Scanscited by 3
  12. 2023Medical visual question answering using joint self-supervised learningcited by 2
  13. 2025Contrastive Regularization over LoRA for Multimodal Biomedical Image Incremental Learningcited by 2
  14. 2025How to make Medical AI Systems safer? Simulating Vulnerabilities, and Threats in Multimodal Medical RAG Systemcited by 2
  15. 2022A Comprehensive Survey of Natural Language Generation Advances from the Perspective of Digital Deceptioncited by 1
  16. 2024UIT-DarkCow team at ImageCLEFmedical Caption 2024: Diagnostic Captioning for Radiology Images Efficiency with Transformer Modelscited by 0
  17. 2025Image-to-Text for Medical Reports Using Adaptive Co-Attention and Triple-LSTM Modulecited by 0
  18. 2026Captioning Daily Activity Images in Early Childhood Education: Benchmark and Algorithmcited by 0