@article {1674821,
	title = {Artificial intelligence in functional imaging of the lung},
	journal = {Br J Radiol},
	volume = {95},
	number = {1132},
	year = {2022},
	month = {2022 Apr 01},
	pages = {20210527},
	abstract = {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.},
	keywords = {Artificial Intelligence, Deep Learning, Diagnostic Imaging, Humans, Lung, machine learning},
	issn = {1748-880X},
	doi = {10.1259/bjr.20210527},
	author = {San Jos{\'e} Est{\'e}par, Ra{\'u}l}
}