Artificial intelligence in functional imaging of the lung.

Artificial intelligence in functional imaging of the lung.
复制标题

肺功能成像中的人工智能。

DOI:
10.1259/bjr.20210527
复制
发表时间:
2022-04-01
期刊:
The British journal of radiology
影响因子:
--
通讯作者:
San José Estépar R
San José Estépar R
中科院分区:
其他
文献类型:
--
作者:
San José Estépar R

文献摘要

参考文献

被引文献

相似文献

人工智能(AI)正在改变我们执行高级成像的方式。从高分辨率图像重建到根据临床采集的数据预测功能反应,人工智能有望彻底改变肺性能的临床评估,推动呼吸系统疾病患者肺功能成像的界限。在这篇评论中,我们概述了目前的发展,并阐述了一些令人鼓舞的新领域。我们专注于机器学习和深度学习的最新进展,这些进展可以重建图像,量化和预测肺部的功能反应。最后,我们揭示了在临床环境中采用AI进行功能性肺成像的潜在机遇和挑战。
Artificial intelligence (AI) is transforming the way we perform advanced imaging. From high-resolution image reconstruction to predicting functional response from clinically acquired data, AI is promising to revolutionize clinical evaluation 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 frontiers. 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.
DOI: 10.1109/tmi.2018.2858202
发表时间: 2019-01
影响因子: 10.6
作者:
Gerard SE;Patton TJ;Christensen GE;Bayouth JE;Reinhardt JM
通讯作者: Reinhardt JM
DOI: 10.1073/pnas.1907377117
发表时间: 2020-12-01
影响因子: 11.1
作者:
Antun, Vegard;Renna, Francesco;Hansen, Anders C.
通讯作者: Hansen, Anders C.
DOI: 10.1016/j.media.2018.11.010
发表时间: 2019-02-01
影响因子: 10.9
作者:
de Vos, Bob D.;Berendsen, Floris F.;Isgum, Ivana
通讯作者: Isgum, Ivana
DOI: 10.1016/j.media.2019.101592
发表时间: 2020-02-01
影响因子: 10.9
作者:
Gerard, Sarah E.;Herrmann, Jacob;Reinhardt, Joseph M.
通讯作者: Reinhardt, Joseph M.
DOI: 10.1038/nature21056
发表时间: 2017-02-02
期刊: Nature
影响因子: 64.8
作者:
Esteva A;Kuprel B;Novoa RA;Ko J;Swetter SM;Blau HM;Thrun S
通讯作者: Thrun S