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A Survey on Deep Learning and Explainability for Automatic Report Generation from Medical Images

arXiv 2010.10563 ↗First posted 20 Oct 2020cs.CV cs.AI cs.CLcited by 35

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Abstract (arXiv)

Every year physicians face an increasing demand of image-based diagnosis from patients, a problem that can be addressed with recent artificial intelligence methods. In this context, we survey works in the area of automatic report generation from medical images, with emphasis on methods using deep neural networks, with respect to: (1) Datasets, (2) Architecture Design, (3) Explainability and (4) Evaluation Metrics. Our survey identifies interesting developments, but also remaining challenges. Among them, the current evaluation of generated reports is especially weak, since it mostly relies on traditional Natural Language Processing (NLP) metrics, which do not accurately capture medical correctness.

Key facts. Cited by 35 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Oct 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 2; 2023: 4; 2024: 17; 2025: 4; 2026: 7.

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  1. 2021Explainable AI (XAI): A Systematic Meta-Survey of Current Challenges and Future Opportunitiescited by 125
  2. 2023Advances in Medical Image Analysis with Vision Transformers: A Comprehensive Reviewcited by 62
  3. 2024Automated Radiology Report Generation: A Review of Recent Advancescited by 43
  4. 2022Explainable Deep Learning Methods in Medical Image Classification: A Surveycited by 31
  5. 2024Has Multimodal Learning Delivered Universal Intelligence in Healthcare? A Comprehensive Surveycited by 20
  6. 2022Benchmark datasets driving artificial intelligence development fail to capture the needs of medical professionalscited by 16
  7. 2024LLMCheckup: Conversational Examination of Large Language Models via Interpretability Tools and Self-Explanationscited by 16
  8. 2024Med-2E3: A 2D-Enhanced 3D Medical Multimodal Large Language Modelcited by 15
  9. 2023A scoping review on multimodal deep learning in biomedical images and textscited by 13
  10. 2024A Survey of Medical Vision-and-Language Applications and Their Techniquescited by 11
  11. 2023Customizing General-Purpose Foundation Models for Medical Report Generationcited by 9
  12. 2024ReXErr: Synthesizing Clinically Meaningful Errors in Diagnostic Radiology Reportscited by 9
23 more
  1. 2023Radiology-Aware Model-Based Evaluation Metric for Report Generationcited by 7
  2. 2024A Survey of Deep Learning-based Radiology Report Generation Using Multimodal Datacited by 6
  3. 2024Extracting and Encoding: Leveraging Large Language Models and Medical Knowledge to Enhance Radiological Text Representationcited by 5
  4. 2024Navigating Distribution Shifts in Medical Image Analysis: A Surveycited by 5
  5. 2025UniVRSE: Unified Vision-conditioned Response Semantic Entropy for Hallucination Detection in Medical Vision-Language Modelscited by 5
  6. 2024Toward Relieving Clinician Burden by Automatically Generating Progress Notes using Interim Hospital Datacited by 4
  7. 2024EVOKE: Elevating Chest X-ray Report Generation via Multi-View Contrastive Learning and Patient-Specific Knowledgecited by 4
  8. 2025R2GenKG: Hierarchical Multi-modal Knowledge Graph for LLM-based Radiology Report Generationcited by 3
  9. 2024A Systematic Literature Review on Explainability for Machine/Deep Learning-based Software Engineering Researchcited by 2
  10. 2024Explainable Interface for Human-Autonomy Teaming: A Surveycited by 2
  11. 2024Medical Report Generation Is A Multi-label Classification Problemcited by 2
  12. 2024Anatomy-Guided Radiology Report Generation with Pathology-Aware Regional Promptscited by 2
  13. 2024LaB-RAG: Label Boosted Retrieval Augmented Generation for Radiology Report Generationcited by 2
  14. 2026TRACE: Temporal Radiology with Anatomical Change Explanation for Grounded X-ray Report Generationcited by 2
  15. 2024Dynamic Traceback Learning for Medical Report Generationcited by 1
  16. 2025Med-R2: Perception and Reflection-driven Complex Reasoning for Medical Report Generationcited by 1
  17. 2025AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generationcited by 1
  18. 2026Bridging the Skill Gap in Clinical CBCT Interpretation with CBCTRepDcited by 1
  19. 2026Trustworthy Data-driven Chronological Age Estimation from Panoramic Dental Imagescited by 0
  20. 2026Personalized Longitudinal Medical Report Generation via Temporally-Aware Federated Adaptationcited by 0
  21. 2026Region-Grounded Report Generation for 3D Medical Imaging: A Fine-Grained Dataset and Graph-Enhanced Frameworkcited by 0
  22. 2026RL-ACRGNet: Reinforcement Learning-Based Chest Radiology Report Generation Networkcited by 0
  23. 2026MAC-RRG: Iterative Multi-Agent Collaboration for X-ray Radiology Report Generationcited by 0