Current Status of Medical Imaging Databases
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-8441-1_3
Reference19 articles.
1. Cardio-thoracic Working Group of Chinese Society of Radiology, National Institutes for Food and Drug Control. Expert consensus on the rule and quality control of pulmonary nodule annotation based on thoracic CT. Chin J Radiol. 2019;53(1):9–15. https://doi.org/10.3760/cma.j.issn.1005-1201.2019.01.004.
2. Chinese Society of Radiology, National Institutes for Food and Drug Control, National Health Commission Capacity Building and Continuing Education Center, et al. Expert consensus on the construction and quality control of thoracic CT datasets for pulmonary nodules. Chin J Radiol. 2021;55(02):104–10. https://doi.org/10.3760/cma.j.cn112149-20200713-00915.
3. Liu SY. Attach importance to and strengthen the construction of medical image database to promote the rapid development of medical imaging. Chin J Radiol. 2022;56(09):931–4. https://doi.org/10.3760/cma.j.cn112149-20220521-00453.
4. Liu SY. The development trend and challenge of artificial intelligence in medical imaging. Chin J Radiol. 2021;55(07):700–2. https://doi.org/10.3760/cma.j.cn112149-20201011-01142.
5. Zhang H, Xiao Y, Hong N, et al. The report of status and needs in medical imaging artificial intelligence industry. Chin J Radiol. 2019;53(6):507–11. https://doi.org/10.3760/cma.j.issn.1005-1201.2019.06.013.
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