Volume 12 Issue 5
Sep.  2021
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HAN Xiaowei, LI Ming, ZHANG Bing. Application of Artificial Intelligence in Neuroimaging of Stroke[J]. Medical Journal of Peking Union Medical College Hospital, 2021, 12(5): 749-754. doi: 10.12290/xhyxzz.2021-0491
Citation: HAN Xiaowei, LI Ming, ZHANG Bing. Application of Artificial Intelligence in Neuroimaging of Stroke[J]. Medical Journal of Peking Union Medical College Hospital, 2021, 12(5): 749-754. doi: 10.12290/xhyxzz.2021-0491

Application of Artificial Intelligence in Neuroimaging of Stroke

doi: 10.12290/xhyxzz.2021-0491

National Natural Science Foundation of China 81720108022

National Natural Science Foundation of China 81971596

National Natural Science Foundation of China 81701672

The Project of the "Sixth Peak of Talented People" WSN-138

Nanjing Medical Science and Technology Development Fund YKK16112

Key Medical Talents of the Jiangsu Province, the"13th Five-year"Health Promotion Project of the Jiangsu Province ZDRCA2016064

More Information
  • Corresponding author: ZHANG Bing  Tel: 86-25-83106666, E-mail: zhangbing_nanjing@nju.edu.cn
  • Received Date: 2021-06-23
  • Accepted Date: 2021-07-29
  • Available Online: 2021-08-19
  • Publish Date: 2021-09-30
  • Artificial intelligence (AI) has risen rapidly in the research field of computer science. The amount of data generated in the process of medical imaging is huge, so it is very suitable to use artificial intelligence technology for related data processing. Neuroimaging of patients with stroke plays a key role in clinical diagnosis, treatment and follow-up. AI technology plays an increasingly important role in the processing and analysis of imaging data of stroke. This paper mainly reviews the research progress of AI technology in neuroimaging of ischemic and hemorrhagic stroke, focusing on the detection of ischemic stroke, judgment of ischemic state of responsible brain area and treatment evaluation, as well as the application of AI technology in the diagnosis, quantitative analysis and treatment evaluation of hemorrhagic stroke. At the same time, the current situation of its clinical transformation application was analyzed. Furthermore, it discusses the main limitations of the current application of AI in stroke neuroimaging, and prospects for future development.
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