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https://github.com/Clearloveyuan/awesome-Radiology-Report-Generation

Paper List about Radiology Report Generation and also some medical image captioning
https://github.com/Clearloveyuan/awesome-Radiology-Report-Generation

List: awesome-Radiology-Report-Generation

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Paper List about Radiology Report Generation and also some medical image captioning

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README 

        
# Awesome Radiology Report Generation[![Awesome](https://awesome.re/badge.svg)](https://awesome.re)





  




A curated list of radiology report generation (medical report generation) and related areas. :-)



## Table of Contents

- [Papers](#papers)

  - [Survey](#survey)

  - [2016](#2016) - [2017](#2017) - [2018](#2018) - [2019](#2019) - [2020](#2020) - [2021](#2021)

- [Dataset](#dataset)



## Papers

### Survey

* [A Survey on Biomedical Image Captioning](https://arxiv.org/pdf/1905.13302) - Kougia V et al, `arXiv preprint 2019`.

* [Deep learning in generating radiology reports: A survey](https://www.sciencedirect.com/science/article/pii/S0933365719302635?casa_token=r5ldLjKGr9gAAAAA:f4qB7XVPFx9BAug8xI09K_Na82cg4torsrelJ89J3uBZJBl251CTGcRghkoY_kIAbz9ne8pJU3AJ) - Monshi et al, `arXiv preprint 2020`.

* [Diagnostic Captioning: A Survey](https://arxiv.org/pdf/2101.07299) - Pavlopoulos et al, `arXiv preprint 2021`.



### 2016

* [Learning to read chest x-rays: Recurrent neural cascade model for automated image annotation](http://openaccess.thecvf.com/content_cvpr_2016/papers/Shin_Learning_to_Read_CVPR_2016_paper.pdf) - Shin H C et al, `CVPR 2016`.[[code]](https://github.com/khcs/learning-to-read).



### 2017

* [Mdnet: A semantically and visually interpretable medical image diagnosis network](http://openaccess.thecvf.com/content_cvpr_2017/papers/Zhang_MDNet_A_Semantically_CVPR_2017_paper.pdf) - Zhang Z et al, `CVPR 2017`.

* [Chestx-ray8: Hospital-scale chest x-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases](http://openaccess.thecvf.com/content_cvpr_2017/papers/Wang_ChestX-ray8_Hospital-Scale_Chest_CVPR_2017_paper.pdf) - Wang X et al, `CVPR 2017`.

* [Tandemnet: Distilling knowledge from medical images using diagnostic reports as optional semantic references](http://openaccess.thecvf.com/content_cvpr_2017/papers/Zhang_MDNet_A_Semantically_CVPR_2017_paper.pdf) - Zhang Z et al, `MICCAI 2017`.



### 2018

* [On the automatic generation of medical imaging reports](https://arxiv.org/pdf/1711.08195) - Jing B et al, `ACL 2018` [[code]](https://github.com/ZexinYan/Medical-Report-Generation).

* [Textray: Mining clinical reports to gain a broad understanding of chest x-rays](https://arxiv.org/pdf/1806.02121) - Laserson J et al, `MICCAI 2018`.

* [Hybrid retrieval-generation reinforced agent for medical image report generation](http://papers.nips.cc/paper/7426-hybrid-retrieval-generation-reinforced-agent-for-medical-image-report-generation.pdf) - Li Y et al, `NIPS 2018`.



### 2019

* [Show, Describe and Conclude: On Exploiting the Structure Information of Chest X-ray Reports](https://www.aclweb.org/anthology/P19-1657.pdf) - Jing B et al, `ACL 2019`.

* [Automatic radiology report generation based on multi-view image fusion and medical concept enrichment](https://arxiv.org/pdf/1907.09085) - Yuan et al, `MICCA 2019`.

* [Addressing data bias problems for chest x-ray image report generation](https://arxiv.org/pdf/1908.02123) - Harzig P et al, `BMVC 2019`.

* [Knowledge-driven encode, retrieve, paraphrase for medical image report generation](https://www.aaai.org/ojs/index.php/AAAI/article/download/4637/4515) - Li C Y et al, `AAAI 2019`.

* [Automatic Generation of Medical Imaging Diagnostic Report with Hierarchical Recurrent Neural Network](https://ieeexplore.ieee.org/iel7/8961330/8970627/08970668.pdf?casa_token=zMmkGsvlcI8AAAAA:SbNyODTWZI1l5kNG_E6SkOs2r5HMhKrGnu8B1CoxPB7kuvtZmvxS7KIoaZMPA2pysI6VcvmBJ426cQ) - Yin et al, `ICDM 2019`.

* [EEGtoText: Learning to Write Medical Reports from EEG Recordings](http://proceedings.mlr.press/v106/biswal19a/biswal19a.pdf) - Biswal S et al, `PMLR 2019`.

* [Multi-Attention and Incorporating Background Information Model for Chest X-Ray Image Report Generation](https://ieeexplore.ieee.org/iel7/6287639/8600701/08867873.pdf) - Huang X et al, `ACCESS 2019`.

* [Baselines for Chest X-Ray Report Generation](https://ml4health.github.io/2019/pdf/175_ml4h_preprint.pdf) - Boag W et al, `arXiv preprint 2019`.

* [Clinically accurate chest X-ray report generation](https://arxiv.org/pdf/1904.02633) - Liu G et al, `arXiv preprint 2019`.[[code]](https://github.com/RAAIL/clinically-accurate-chest-x-ray-report-generation)

* [Optimizing the Factual Correctness of a Summary: A Study of Summarizing Radiology Reports](https://arxiv.org/pdf/1911.02541) - Zhang Y et al, `arXiv preprint 2019`.

* [Automatic Radiology Report Generation based on Multi-view Image Fusion and Medical Concept Enrichment](https://arxiv.org/pdf/1907.09085.pdf) -Jianbo Yuan et, `arXiv preprint 2019`.



### 2020

* [Generating Radiology Reports via Memory-driven Transformer](https://www.aclweb.org/anthology/2020.emnlp-main.112.pdf) - Chen Z et al, `EMNLP 2020`. [[code]](https://github.com/cuhksz-nlp/R2Gen)

* [When Radiology Report Generation Meets Knowledge Graph](https://ojs.aaai.org/index.php/AAAI/article/view/6989/6843) - Zhang Y et al, `AAAI 2020`.

* [Reinforcement Learning with Imbalanced Dataset for Data-to-Text Medical Report Generation](https://aclanthology.org/2020.findings-emnlp.202/) -	Toru Nishino et al. `EMNLP 2020`

* [WIRE: An Automated Report Generation System using Topical and Temporal Summarization](https://dl.acm.org/doi/10.1145/3397271.3401409) `sigir2020`

* 



### 2021

* [Exploring and Distilling Posterior and Prior Knowledge for Radiology Report Generation](https://openaccess.thecvf.com/content/CVPR2021/papers/Liu_Exploring_and_Distilling_Posterior_and_Prior_Knowledge_for_Radiology_Report_CVPR_2021_paper.pdf) - Liu F et al, `CVPR 2021`.

* [A Self-Boosting Framework for Automated Radiographic Report Generation](https://openaccess.thecvf.com/content/CVPR2021/papers/Wang_A_Self-Boosting_Framework_for_Automated_Radiographic_Report_Generation_CVPR_2021_paper.pdf) - Wang Z et al, `CVPR 2021`.

* [Cross-modal Memory Networks for Radiology Report Generation](https://aclanthology.org/2021.acl-long.459.pdf) -Chen Z et al, `ACL 2021`

* [Contrastive Attention for Automatic Chest X-ray Report Generation](https://arxiv.org/pdf/2106.06965.pdf) -Fenglin Liu et al, `Arxiv 2021`

* [Improving Factual Completeness and Consistency of Image-to-Text Radiology Report Generation](https://aclanthology.org/2021.naacl-main.416.pdf) -Yasuhide Miura et al, `NACCL 2021`

* [A Self-boosting Framework for Automated Radiographic Report Generation](https://openaccess.thecvf.com/content/CVPR2021/papers/Wang_A_Self-Boosting_Framework_for_Automated_Radiographic_Report_Generation_CVPR_2021_paper.pdf) -Zhanyu Wang et al, `CVPR 2021`.

* [Exploring and Distilling Posterior and Prior Knowledge for Radiology Report Generation](https://openaccess.thecvf.com/content/CVPR2021/papers/Liu_Exploring_and_Distilling_Posterior_and_Prior_Knowledge_for_Radiology_Report_CVPR_2021_paper.pdf) -Fenglin Liu et al., `CVPR 2021`.

* [Competence-based Multimodal Curriculum Learning for Medical Report Generation (Short)](https://web.pkusz.edu.cn/adsp/files/2021/07/ACL2021_CMCL.pdf) -Fenglin Liu et al. `ACL 2021`

* [Writing by Memorizing: Hierarchical Retrieval-based Medical Report Generation](https://aclanthology.org/2021.acl-long.387.pdf) -Xingyi Yang et al. `ACL 2021`

* [Unifying Relational Sentence Generation and Retrieval for Medical Image Report Composition](https://arxiv.org/pdf/2101.03287.pdf) -Fuyu Wang et al. `IEEE CYB 2021`

* [Progressive Transformer-Based Generation of Radiology Reports](https://github.com/uzh-dqbm-cmi/ARGON) -Farhad Nooralahzadeh et al. `EMNLP 2021`

* [Variational Topic Inference for Chest X-Ray Report Generation](https://arxiv.org/pdf/2107.07314.pdf) -Ivona Najdenkoska et al. `Arxiv 2021`

* [Confidence-Guided Radiology Report Generation](https://arxiv.org/pdf/2106.10887.pdf) -Yixin Wang et al. `NIPS 2021`

* 



## Related Word/Topic

#### Textual labeling of medical images

#### Image captioning



## Dataset

* [Preparing a collection of radiology examinations for distribution and retrieval](https://academic.oup.com/jamia/article/23/2/304/2572395) - Demner-Fushman D et al, `JAMIA 2016`.

* [MIMIC-CXR: a large publicly available database of labeled chest radiographs](https://deepai.org/publication/mimic-cxr-a-large-publicly-available-database-of-labeled-chest-radiographs) - Johnson A E W et al, `arXiv preprint 2019`.

* [Padchest: A large chest x-ray image dataset with multi-label annotated reports](https://arxiv.org/pdf/1901.07441) - Bustos A et al, `arXiv preprint 2019`.



## Popular Implementations

### PyTorch

* [cuhksz-nlp/R2Gen](https://github.com/cuhksz-nlp/R2Gen)



## Licenses



[![CC0](http://i.creativecommons.org/p/zero/1.0/88x31.png)](http://creativecommons.org/publicdomain/zero/1.0/)



To the extent possible under law, [Zhihong Chen](https://github.com/zhjohnchan) has waived all copyright and related or neighboring rights to this work.