mlsanityData to 14 Oct 2026

On the Automatic Generation of Medical Imaging Reports

arXiv 1711.08195 ↗First posted 22 Nov 2017cs.CL cs.CVcited by 216

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Cited by 21 in Multimodal LLMs / vision-language models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Medical imaging is widely used in clinical practice for diagnosis and treatment. Report-writing can be error-prone for unexperienced physicians, and time- consuming and tedious for experienced physicians. To address these issues, we study the automatic generation of medical imaging reports. This task presents several challenges. First, a complete report contains multiple heterogeneous forms of information, including findings and tags. Second, abnormal regions in medical images are difficult to identify. Third, the re- ports are typically long, containing multiple sentences. To cope with these challenges, we (1) build a multi-task learning framework which jointly performs the pre- diction of tags and the generation of para- graphs, (2) propose a co-attention mechanism to localize regions containing abnormalities and generate narrations for them, (3) develop a hierarchical LSTM model to generate long paragraphs. We demonstrate the effectiveness of the proposed methods on two publicly available datasets.

Key facts. Cited by 216 papers in the map (data through 14 Oct 2026). First posted on arXiv 22 Nov 2017.

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Citing papers per year: 2021: 27; 2022: 31; 2023: 45; 2024: 50; 2025: 31; 2026: 32.

216 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. 2021VisualGPT: Data-efficient Adaptation of Pretrained Language Models for Image Captioningcited by 191
  4. 2022Cross-modal Memory Networks for Radiology Report Generationcited by 185
  5. 2022Translation between Molecules and Natural Languagecited by 177
  6. 2023A Survey of Large Language Models for Healthcare: from Data, Technology, and Applications to Accountability and Ethicscited by 163
  7. 2021Exploring and Distilling Posterior and Prior Knowledge for Radiology Report Generationcited by 162
  8. 2021Explainable artificial intelligence (XAI) in deep learning-based medical image analysiscited by 147
  9. 2023Interactive and Explainable Region-guided Radiology Report Generationcited by 140
  10. 2021From Show to Tell: A Survey on Deep Learning-based Image Captioningcited by 138
  11. 2023A Survey of Large Language Models in Medicine: Progress, Application, and Challengecited by 124
  12. 2023R2GenGPT: Radiology Report Generation with Frozen LLMscited by 114
38 more
  1. 2023METransformer: Radiology Report Generation by Transformer with Multiple Learnable Expert Tokenscited by 101
  2. 2024CT2Rep: Automated Radiology Report Generation for 3D Medical Imagingcited by 96
  3. 2022Improving Chest X-Ray Report Generation by Leveraging Warm Startingcited by 95
  4. 2023PromptMRG: Diagnosis-Driven Prompts for Medical Report Generationcited by 95
  5. 2024MMed-RAG: Versatile Multimodal RAG System for Medical Vision Language Modelscited by 85
  6. 2022Improving the Factual Correctness of Radiology Report Generation with Semantic Rewardscited by 83
  7. 2022Competence-based Multimodal Curriculum Learning for Medical Report Generationcited by 76
  8. 2021Radiology Report Generation with a Learned Knowledge Base and Multi-modal Alignmentcited by 73
  9. 2021Contrastive Attention for Automatic Chest X-ray Report Generationcited by 71
  10. 2024FairCLIP: Harnessing Fairness in Vision-Language Learningcited by 69
  11. 2021Knowledge Matters: Radiology Report Generation with General and Specific Knowledgecited by 68
  12. 2022AlignTransformer: Hierarchical Alignment of Visual Regions and Disease Tags for Medical Report Generationcited by 65
  13. 2022A General Survey on Attention Mechanisms in Deep Learningcited by 64
  14. 2023KiUT: Knowledge-injected U-Transformer for Radiology Report Generationcited by 62
  15. 2022Cross-modal Prototype Driven Network for Radiology Report Generationcited by 59
  16. 2022Improving Radiology Report Generation Systems by Removing Hallucinated References to Non-existent Priorscited by 48
  17. 2021Auto-Encoding Knowledge Graph for Unsupervised Medical Report Generationcited by 47
  18. 2022A Medical Semantic-Assisted Transformer for Radiographic Report Generationcited by 44
  19. 2021Progressive Transformer-Based Generation of Radiology Reportscited by 43
  20. 2024Automated Radiology Report Generation: A Review of Recent Advancescited by 43
  21. 2023ORGAN: Observation-Guided Radiology Report Generation via Tree Reasoningcited by 42
  22. 2021Weakly Supervised Contrastive Learning for Chest X-Ray Report Generationcited by 41
  23. 2023Multimodal Image-Text Matching Improves Retrieval-based Chest X-Ray Report Generationcited by 37
  24. 2023Utilizing Longitudinal Chest X-Rays and Reports to Pre-Fill Radiology Reportscited by 35
  25. 2022M^4I: Multi-modal Models Membership Inferencecited by 34
  26. 2024HERGen: Elevating Radiology Report Generation with Longitudinal Datacited by 33
  27. 2022Explainable Deep Learning Methods in Medical Image Classification: A Surveycited by 32
  28. 2023WsiCaption: Multiple Instance Generation of Pathology Reports for Gigapixel Whole-Slide Imagescited by 31
  29. 2023Style-Aware Radiology Report Generation with RadGraph and Few-Shot Promptingcited by 29
  30. 2024MEIT: Multimodal Electrocardiogram Instruction Tuning on Large Language Models for Report Generationcited by 29
  31. 2022Faithfulness in Natural Language Generation: A Systematic Survey of Analysis, Evaluation and Optimization Methodscited by 27
  32. 2022Inference of captions from histopathological patchescited by 26
  33. 2024CoMT: Chain-of-Medical-Thought Reduces Hallucination in Medical Report Generationcited by 25
  34. 2021Medical-VLBERT: Medical Visual Language BERT for COVID-19 CT Report Generation With Alternate Learningcited by 24
  35. 2021Automated Generation of Accurate & Fluent Medical X-ray Reportscited by 24
  36. 2022Cross-modal Clinical Graph Transformer for Ophthalmic Report Generationcited by 24
  37. 2023Unify, Align and Refine: Multi-Level Semantic Alignment for Radiology Report Generationcited by 23
  38. 2022Vision Transformers in Medical Computer Vision -- A Contemplative Retrospectioncited by 22

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