id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-347984-iqsbrw88	Shi, Feng	Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation and Diagnosis for COVID-19	2020-04-06		.txt	text/plain	6946	411	50	In the pre-scan preparation stage, each subject is instructed and assisted by a technician to pose on the Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation and Diagnosis for COVID-19 patient bed according to a given protocol. Recent AI-empowered applications in COVID-19 mainly include the dedicated imaging platform, the lung and infection region segmentation, the clinical assessment and diagnosis, as well as the pioneering basic and clinical research. [57] propose a two-stage pipeline for screening COVID-19 in CT images, in which the whole lung region is first detected by an efficient segmentation network based on UNet++. [58] propose a VB-Net for segmentation of lung, lung lobes and lung infection, which provide accurate quantification data for medical studies, including quantitative assessment of progression in the follow-up, comprehensive prediction of severity in the enrollment, and visualization of lesion distribution using percentage of infection (POI). [11] propose a deep convolutional neural network based model (COVID-Net) to detect COVID-19 cases using X-ray images.	./cache/cord-347984-iqsbrw88.txt	./txt/cord-347984-iqsbrw88.txt