Trust it or not: Confidence-guided automatic radiology report generation

Author:

Wang YixinORCID,Lin Zihao,Xu ZheORCID,Dong Haoyu,Luo Jie,Tian Jiang,Shi Zhongchao,Huang Lifu,Zhang YangORCID,Fan Jianping,He Zhiqiang

Publisher

Elsevier BV

Reference72 articles.

1. On the automatic generation of medical imaging reports;Jing,2018

2. X. Wang, Y. Peng, L. Lu, Z. Lu, R.M. Summers, TieNet: Text-Image Embedding Network for Common Thorax Disease Classification and Reporting in Chest X-Rays, in: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018, pp. 9049–9058, http://dx.doi.org/10.1109/CVPR.2018.00943.

3. Multimodal recurrent model with attention for automated radiology report generation;Xue,2018

4. Y. Li, X. Liang, Z. Hu, E.P. Xing, Hybrid Retrieval-Generation Reinforced Agent for Medical Image Report Generation, in: S. Bengio, H.M. Wallach, H. Larochelle, K. Grauman, N. Cesa-Bianchi, R. Garnett (Eds.), Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, December 3-8, 2018, MontrÉAl, Canada, 2018, pp. 1537–1547, URL.

5. Baselines for Chest X-Ray Report Generation;Boag,2020

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