期刊
BRITISH JOURNAL OF RADIOLOGY
卷 95, 期 1132, 页码 -出版社
BRITISH INST RADIOLOGY
DOI: 10.1259/bjr.20210527
关键词
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资金
- National Heart, Lung, and Blood Institute of the NIH [R01HL149877, R01 HL116473, R21HL140422]
- National Library Medicine [R21LM013670]
This review discusses the application of artificial intelligence in lung functional imaging, including high-resolution image reconstruction, prediction, and quantification of functional responses. Artificial intelligence has great potential in clinical lung function assessment, but also faces challenges.
Artificial intelligence (AI) is transforming the way we perform advanced imaging. From high- resolution image recon-struction to predicting functional response from clinically acquired data, AI is promising to revolutionize clinical evalua-tion of lung performance, pushing the boundary in pulmonary functional imaging for patients suffering from respiratory conditions. In this review, we overview the current developments and expound on some of the encouraging new fron-tiers. We focus on the recent advances in machine learning and deep learning that enable reconstructing images, quantitating, and predicting functional responses of the lung. Finally, we shed light on the potential opportunities and challenges ahead in adopting AI for functional lung imaging in clinical settings.
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