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https://github.com/Markin-Wang/awesome_radiology_report_generation

Awesome radiology report generation and image captioning papers.
https://github.com/Markin-Wang/awesome_radiology_report_generation

List: awesome_radiology_report_generation

image-captioning medical-report-generation radiology-report-generation

Last synced: 3 months ago
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Awesome radiology report generation and image captioning papers.

Awesome Lists containing this project

README 

        
# read-paper-list

Radiology Report Generation/Medical Report Generation/Image Captioning



## Years:

* [2024](#2024) 

* [2023](#2023) 

* [2022](#2022) 

* [2021](#2021)

* [2020](#2020)

* [2019](#2019)



# **2024** 


* TSGET: Two-Stage Global Enhanced Transformer for Automatic Radiology Report Generation, *IEEE J-BHI*. |[pdf](https://ieeexplore.ieee.org/document/10381879)| [code](https://github.com/SKD-HPC/TSGET)|

* Bootstrapping Large Language Models for Radiology Report Generation |pdf|[code](https://github.com/synlp/R2-LLM)|



# **2023** 


* Style-Aware Radiology Report Generation with RadGraph and Few-Shot Prompting, *EMNLP*. |[pdf](https://aclanthology.org/2023.findings-emnlp.977.pdf)|

* PhenotypeCLIP: Phenotype-based Contrastive Learning for Medical Imaging Report Generation , *EMNLP*. |[pdf](https://aclanthology.org/2023.emnlp-main.989.pdf)|

* RECAP: Towards Precise Radiology Report Generation via Dynamic Disease Progression Reasoning, *EMNLP*. |[pdf](https://aclanthology.org/2023.findings-emnlp.140.pdf)| [code](https://github.com/wjhou/recap)|

* CAMANet: Class Activation Map Guided Attention Network for Radiology Report Generation, *IEEE J-BHI*. |[pdf](https://ieeexplore.ieee.org/abstract/document/10400776)| [code](https://github.com/Markin-Wang/CAMANet)|

* R2GenGPT: Radiology Report Generation with Frozen LLMs, *Meta Radiology*. |[pdf](https://arxiv.org/abs/2309.09812)| [code](https://github.com/wang-zhanyu/R2GenGPT)|

* Replace and Report: NLP Assisted Radiology Report Generation, *ACL*. |[pdf](https://aclanthology.org/2023.findings-acl.683.pdf)|

* ORGAN: Observation-Guided Radiology Report Generation via Tree Reasoning, *ACL*. |[pdf](https://aclanthology.org/2023.acl-long.451.pdf)| [code](https://github.com/wjhou/ORGan)|

* Can Prompt Learning Benefit Radiology Report Generation?, *Arxiv*. |[pdf](https://arxiv.org/abs/2308.16269)|

* A Systematic Review of Deep Learning-based Research on Radiology Report Generation, *arXiv*. |[pdf](https://arxiv.org/abs/2311.14199.pdf)|[code](https://github.com/synlp/RRG-Review)|

* METransformer: Radiology Report Generation by Transformer with Multiple Learnable Expert Tokens, *CVPR*. |[pdf](https://openaccess.thecvf.com/content/CVPR2023/papers/Wang_METransformer_Radiology_Report_Generation_by_Transformer_With_Multiple_Learnable_Expert_CVPR_2023_paper.pdf)|

* KiUT: Knowledge-injected U-Transformer for Radiology Report Generation, *CVPR*. |[pdf](https://openaccess.thecvf.com/content/CVPR2023/papers/Huang_KiUT_Knowledge-Injected_U-Transformer_for_Radiology_Report_Generation_CVPR_2023_paper.pdf)|

* Dynamic Graph Enhanced Contrastive Learning for Chest X-ray Report Generation, *CVPR*. |[pdf](https://openaccess.thecvf.com/content/CVPR2023/papers/Li_Dynamic_Graph_Enhanced_Contrastive_Learning_for_Chest_X-Ray_Report_Generation_CVPR_2023_paper.pdf)|[code](https://github.com/mlii0117/DCL)|

* Radiology report generation with a learned knowledge base and multi-modal alignment, *Medical Image Analysis*,|[pdf](https://www.sciencedirect.com/science/article/pii/S1361841523000592)|[code](https://github.com/LX-doctorAI1/M2KT)|



# **2022** 


* Injecting Semantic Concepts into End-to-End Image Captioning, *CVPR*. |[pdf](https://openaccess.thecvf.com/content/CVPR2022/papers/Fang_Injecting_Semantic_Concepts_Into_End-to-End_Image_Captioning_CVPR_2022_paper.pdf)|[code](https://github.com/jacobswan1/ViTCAP)|

* PTSN: Progressive Tree-Structured Prototype Networ, *ACM MM*. |[pdf](https://dl.acm.org/doi/abs/10.1145/3503161.3548024)|[code](https://github.com/NovaMind-Z/PTSN)| 

* Reinforced Cross-modal Alignment for Radiology Report Generation, *ACL Findings*. |[pdf](https://aclanthology.org/2022.findings-acl.38/)|

* Uncertainty-aware report generation for chest X-rays by variational topic inference, *Medical Image Analysis*. |[pdf](https://www.sciencedirect.com/science/article/pii/S1361841522002341)|[code](https://github.com/ivonajdenkoska/variational-xray-report-gen)| 

* Automated Radiographic Report Generation Purely On Transformer: A Multi-criteria Supervised Approach, *TMI*. |[pdf](https://ieeexplore.ieee.org/document/9768661)|

* Cross-modal Prototype Driven Network for Radiology Report Generation, *ECCV*. |[pdf](https://arxiv.org/abs/2207.04818)|[code](https://github.com/Markin-Wang/XProNet)| 

* Radiology Report Generation with General and Specific Knowledge, *Medical Image Analysis*,|[pdf](https://arxiv.org/pdf/2112.15009.pdf)|



# **2021** 


* Cross-modal Memory Networks for Radiology Report Generation, *ACL Main*. |[pdf](https://aclanthology.org/2021.acl-long.459.pdf)|[code](https://github.com/cuhksz-nlp/r2gencmn)|

* A Self-boosting Framework for Automated Radiographic Report Generation, *CVPR*. |[pdf](https://openaccess.thecvf.com/content/CVPR2021/papers/Wang_A_Self-Boosting_Framework_for_Automated_Radiographic_Report_Generation_CVPR_2021_paper.pdf)|

* Improving Image Captioning by Leveraging Intra- and Inter-layer Global Representation in Transformer Network, *AAAI*. |[pdf](https://ojs.aaai.org/index.php/AAAI/article/view/16258)|[code](https://github.com/luo3300612/image-captioning-DLCT)| 

* Contrastive Attention for Automatic Chest X-ray Report Generation, *ACL Findings*. |[pdf](https://aclanthology.org/2021.findings-acl.23.pdf)|

* RATCHET: Medical Transformer for Chest X-ray Diagnosis and Reporting, *MICCAI*. |[pdf](https://link.springer.com/chapter/10.1007/978-3-030-87234-2_28)|

* Competence-based Multimodal Curriculum Learning for Medical Report Generation, *ACL* | [pdf](https://aclanthology.org/2021.acl-long.234/)



# **2020** 


* Comprehensive Image Captioning via Scene Graph Decomposition, *ECCV*. |[pdf](https://dl.acm.org/doi/abs/10.1007/978-3-030-58568-6_13)|[code](https://github.com/YiwuZhong/Sub-GC)|

* Generating Radiology Reports via Memory-driven Transformer, *EMNLP Main*. |[pdf](https://aclanthology.org/2020.emnlp-main.112/)|[code](https://github.com/cuhksz-nlp/R2Gen)| 

* Improving Factual Completeness and Consistency of Image-to-text Radiology Report Generation, *NAACL Main* |[pdf](https://arxiv.org/abs/2010.10042)|[code](https://github.com/ysmiura/ifcc)| 



# **2019** 


* Fast, Diverse and Accurate Image Captioning Guided By Part-of-Speech, *CVPR*. |[pdf](https://openaccess.thecvf.com/content_CVPR_2019/papers/Deshpande_Fast_Diverse_and_Accurate_Image_Captioning_Guided_by_Part-Of-Speech_CVPR_2019_paper.pdf)|